{"task_type": "generation", "dataset": "mams", "input": ["The decor is not special at all but their food and amazing prices make up for it."], "output": "[['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["when tables opened up, the manager sat another party before us."], "output": "[['tables', 'neutral'], ['manager', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Though the menu includes some unorthodox offerings (a peanut butter roll, for instance), the classics are pure and great--we've never had better sushi anywhere, including Japan."], "output": "[['menu', 'neutral'], ['peanut butter roll', 'negative'], ['classics', 'positive'], ['sushi', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["service is good although a bit in your face, we were asked every five mins if food was ok, but better that than being ignored."], "output": "[['service', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["PS- I just went for brunch on Saturday and the eggs served with onions and rosemary were amazing."], "output": "[['brunch', 'neutral'], ['eggs served with onions', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["they didn't have to change anything about the menu except add a leg of chicken seperatley and the guy mumbled very rudely that I had already ordered and I should've decided earlier."], "output": "[['menu', 'neutral'], ['guy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The server came to us and was sooo hot, he went over the menu and specials with us."], "output": "[['server', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food The best surprises on the El Salvadorean menu are the appetizers."], "output": "[['Food', 'neutral'], ['appetizers', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["12/24/03  Dinner was ok, service was so- so,the worst part was the hostess - we made reservations a month before Christmas Eve for three people, you would think the table would be large enough for all three of us."], "output": "[['Dinner', 'positive'], ['service', 'neutral'], ['hostess', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Still, after all the fuss, the food makes you forget about the wait."], "output": "[['food', 'positive'], ['wait', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had to physically get out of my seat and find the waitress twice just to ask for more water."], "output": "[['seat', 'neutral'], ['waitress', 'negative'], ['water', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When we finally got to order, we were told the bartender wasn't there, so we couldn't order any drinks."], "output": "[['bartender', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Three course meal for lunch was $13, the prices for dinner were just as great!"], "output": "[['course meal', 'neutral'], ['lunch', 'neutral'], ['prices', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["but such remark depicts the worldly somelier/owner/janitor of LPF, who is a true gourmand savvy not only in wine but in the basics of good eat."], "output": "[['wine', 'neutral'], ['eat', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service was impeccible, the menu traditional but inventive and presentation for the mostpart excellent but the food itself came up short."], "output": "[['service', 'positive'], ['menu', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When our entrees came, at least 3 or 4 waiters / waitresses came by at different times to wish us bon apetit."], "output": "[['entrees', 'neutral'], ['waitresses', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our last experience: Waiting for a table at the bar (we always make reservations), the bartender ignored us until my husband intervened with one of the owners."], "output": "[['table', 'neutral'], ['reservations', 'neutral'], ['owners', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu features classic French bistro fare, like steamed mussels with French fries and hangar steak with a green peppercorn sauce."], "output": "[['menu', 'neutral'], ['French bistro fare', 'positive'], ['steamed mussels with French fries', 'neutral'], ['green peppercorn sauce', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene A stone-faced facade welcomes diners to a restaurant that feels barely touched by the neighborhood's rapid transformation into a nighttime hot spot."], "output": "[['Scene', 'neutral'], ['spot', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Get in before peak dinner time (7-8 PM) to avoid harried service."], "output": "[['dinner', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My family and I enjoy spicy food so towards the end of the meal, we were tearing and had runny noses."], "output": "[['food', 'positive'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Dinner highlights include succulent salmon fillet, drenched in roasted tomato shallot sauce and grilled hangar steak with light fries and caramelized onions."], "output": "[['Dinner', 'neutral'], ['succulent salmon fillet', 'positive'], ['caramelized onions', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The drinks, served with a little extra in the shaker, anticipate the aptly executed menu, which emphasizes comfort foods of a bygone era--veggies, for example, include crisp Brussels sprouts, shredded beets and bubbling-hot scalloped potatoes."], "output": "[['drinks', 'neutral'], ['menu', 'neutral'], ['foods', 'positive'], ['veggies', 'neutral'], ['sprouts', 'positive'], ['beets', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After sitting at the table with empty glasses for a 1/2 hour, we had to ask the busboys to get us drinks as our waiter was nowhere to be found."], "output": "[['table', 'neutral'], ['drinks', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food is pretty good but the service is horrific."], "output": "[['Food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The hostess made sure we knew where the lounge was since all the seats at the bar were full and had the waiter come over to take our drink order."], "output": "[['hostess', 'negative'], ['lounge', 'neutral'], ['seats', 'neutral'], ['bar', 'neutral'], ['order', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["last time, the waiter told my roommate he'd have to charge her $5 for mushrooms as one of her omelette choices (never heard that at my other favorite brunch places."], "output": "[['waiter', 'negative'], ['places', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Summary - good food which they rush you through and do everything to up your bill."], "output": "[['food', 'positive'], ['bill', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A huge Coca-Cola sign dominates the bar, and cute waiters whisk plates of 'cue across the dining room and to the sidewalk patio."], "output": "[['bar', 'neutral'], ['waiters', 'positive'], ['plates', 'neutral'], ['dining room', 'neutral'], ['patio', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["warm orangey glow, nice old mexican prints, wee bar that my bf and i vowed to go back and linger at."], "output": "[['mexican', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The server seemed drunk, he forgot mixed up our food with some other table, ignored our requests for more water, drinks etc."], "output": "[['server', 'negative'], ['food', 'neutral'], ['table', 'neutral'], ['water', 'neutral'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["sushi a big hamburger and good coctails."], "output": "[['sushi', 'neutral'], ['hamburger', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Go for drinks, but not food it will leave you asking, where's the beef?"], "output": "[['drinks', 'positive'], ['beef', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Without reservations on a Friday night at 8:30 I was promptly seated and given top-notch recommendations from both the host and my waiter."], "output": "[['reservations', 'neutral'], ['host', 'positive'], ['waiter', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["And the waitstaff has very little knowledge of the food, they served me the wrong dish and no one could identify what it was that they gave me, someone said pork chop, someone said lamb, and then they insisted it should be fine since it was the same price."], "output": "[['waitstaff', 'negative'], ['food', 'neutral'], ['served', 'neutral'], ['dish', 'negative'], ['pork chop', 'negative'], ['lamb', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["-4 waiters bustling around though no table was actually being helped -25 minutes to take our order -15 minutes to get the drinks we order -another 20 minutes to get our food -NO apology from the waiter In between our lunch, a man burst out shouting in anger at the lousy service (he asked for ketchup 20 minutes ago and never got it)."], "output": "[['waiters', 'negative'], ['drinks', 'neutral'], ['lunch', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When we asked if the waiter could put the lights back on, he said:we have this complaint every night but the owner thinks it's more 'Parisian'!"], "output": "[['waiter', 'negative'], ['lights', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The portions are not HUGE, but you are very full by the end of your meal."], "output": "[['portions', 'negative'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["we were full and ordered just coffee and tea, but the chef sent us some of his home made ice cream, saying he couldnt send us home without trying any of his dessert so that was the most unexpected part: lemongrass vanilla, five spices chinese chocolat (unbelivable)and coconut with citrus zests."], "output": "[['coffee', 'neutral'], ['tea', 'neutral'], ['cream', 'neutral'], ['dessert', 'neutral'], ['chinese chocolat', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I'm not sure how he's managed to stay in the restaurant business for 40 years with his attitude (and the food's not good enough to rate the Seinfeld treatment), but he's definitely lost one customer for good!"], "output": "[['food', 'negative'], ['Seinfeld', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I don't usually go there over the weekends or during prime dinner hours--but for a weekday dinner it's great, and I've never had any problems with crowds, waiting, or bad service."], "output": "[['prime dinner', 'neutral'], ['crowds', 'neutral'], ['waiting', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["All of the drinks that we tried were As for desserts, my favorite is the chocolate cake and my boyfriend really liked their pumpkin cheesecake."], "output": "[['drinks', 'neutral'], ['desserts', 'neutral'], ['chocolate cake', 'positive'], ['cheesecake', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is also good although there are a few kinks to work out - the soft shell crab appetizer wasn't quite as 'soft' as it should be and the halibut was a little too peppery, but my friend loved his cod and said it was perfect."], "output": "[['food', 'positive'], ['soft shell crab appetizer', 'negative'], ['cod', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I can't even remember if they serve anything else -- a busy hole in the wall sized place and atmosphere."], "output": "[['place', 'negative'], ['atmosphere', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The beginning of the meal wasnt bad, the hostess was very nice, we got our drinks about every 10 minutes and the appetizers we good."], "output": "[['hostess', 'positive'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter was nice once he got to us, it took about 5 minutes to get a glass of water and someone to get us started even though it was very slow."], "output": "[['waiter', 'positive'], ['glass of water', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The whole table must participate and you have to be willing to let the chef cook for you with no menu."], "output": "[['whole table', 'positive'], ['chef', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Great food, but tiny portions and inexcusable service - disorganized, amateurish and definitely overpriced by a long shot."], "output": "[['food', 'positive'], ['portions', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The signature of the Indian Tandoor-Oven chet seems to be the total absence of spices   The pakoras were somewhere between red and purple in color and dripping with oil."], "output": "[['spices', 'negative'], ['oil', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The decor in the dinin room is a bit bland, but the service is always friendly."], "output": "[['decor', 'negative'], ['dinin room', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Don't go for the decor or the location, go for the food!"], "output": "[['decor', 'negative'], ['location', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although the sides at Lugers are delicious (the bacon is out of this world) the steak is entirely priced way too high."], "output": "[['sides', 'positive'], ['Lugers', 'neutral'], ['bacon', 'positive'], ['steak', 'negative'], ['priced', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our dinner special included dessert, but our slow and unhelpful waitress didn't bother asking if we wanted any."], "output": "[['dessert', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitress came to our table and told us about their tempting specials."], "output": "[['waitress', 'positive'], ['table', 'neutral'], ['specials', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I ordered chicken vindaloo, the delivery took about an hour, and it cost me $13 with tip."], "output": "[['chicken vindaloo', 'neutral'], ['cost', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The best part of our dining experience was, when our burgers were ordered with NOTHING on them, and they came with some mysterious Houston's secret hickory sauce!"], "output": "[['burgers', 'negative'], ['secret hickory sauce', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["i think the $5 dollar breakfast is great hangover food, but then again, it's hard to mess up eggs, right?"], "output": "[['breakfast', 'positive'], ['eggs', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["With 5 items on the menu and prices this low, you'd think turnover would be a priority -- think again!!!"], "output": "[['menu', 'neutral'], ['prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter set down my companion's meal and didn't return with my dish for some time."], "output": "[['waiter', 'negative'], ['meal', 'neutral'], ['dish', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There are decent selections if you are a seafood person, but not a lot if you aren't!"], "output": "[['selections', 'negative'], ['seafood', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["From the appetizers to the spectacular and always improving wine list, to the delicious entrees."], "output": "[['appetizers', 'neutral'], ['wine list', 'positive'], ['entrees', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is wonderful and reasonably priced, (so hard to find in NY) and the wait staff is very attentive and helpful when choosing an entree."], "output": "[['food', 'positive'], ['priced', 'positive'], ['wait staff', 'positive'], ['entree', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu features mild versions of Lone Star state favorites, from double-basted baby back ribs and steak fajitas to red-beef chili and deep-fried onions."], "output": "[['menu', 'neutral'], ['baby back ribs', 'positive'], ['red-beef chili', 'positive'], ['deep-fried onions', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although Sweet Melissa's food and pastries are very tasty, the unfriendly folks who work there sour the experience."], "output": "[['Melissa', 'positive'], ['food', 'positive'], ['pastries', 'positive'], ['experience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The bean burritos and the cheese enchiladas are to die for and don't get me started on their refried beans."], "output": "[['bean burritos', 'positive'], ['beans', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The drinks are quite strong, so I recommend having one of their wines by the glass to accompany dinner instead of a cocktail."], "output": "[['drinks', 'positive'], ['wines by the glass to', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The first time, the food was decent for lunch, but remember mediocre service."], "output": "[['lunch', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waitress hardly spoken English - and not because she spoke French - and she spilled wine all over me and didn't try to make any amends."], "output": "[['waitress', 'negative'], ['wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Just finished a tasty jerked chicken dinner that was too pricey for the subpar service and good, but not great food."], "output": "[['jerked chicken dinner', 'positive'], ['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I often go to ISE for lunch and I am always very happy with the food."], "output": "[['lunch', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My husband and I ate dinner there last weekend and the food was very good, and very reasonably priced, we thought."], "output": "[['dinner', 'neutral'], ['food', 'positive'], ['priced', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our food was delivered in a timely fashion but if you wanted another drink or your check you had to hunt down your server."], "output": "[['food', 'positive'], ['check', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Teenie weenie overpriced appetizers were served at an agonizingly slow pace, one at a time 30 minutes between each."], "output": "[['appetizers', 'negative'], ['served', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We both got soup, and appetizer, and a main course (fabulous duck), so we didnt have space for dessert."], "output": "[['appetizer', 'neutral'], ['duck', 'positive'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food other than sushi is also very nice."], "output": "[['Food', 'positive'], ['sushi', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The portions are now very small, the sauces are overly-ambitious usually inedible while the service is still good, the restaurant, due to its popularity, seems frantic."], "output": "[['portions', 'negative'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter was a real pro; knew a lot about ingredients and allowed us to take our time."], "output": "[['waiter', 'positive'], ['ingredients', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The place wasn't at all busy, and we were shown a table in the back, given our menus, and promptly forgotten about."], "output": "[['place', 'negative'], ['menus', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For dessert you must try the baklava, chocolate mousse cake, strawberry shortcake."], "output": "[['dessert', 'neutral'], ['baklava', 'positive'], ['chocolate mousse cake', 'positive'], ['strawberry shortcake', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have been to Blue Ribbon Sushi at least 75 times and have never ordered the same dish twice, that's how awesome the menu is."], "output": "[['Sushi', 'neutral'], ['dish', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I got there with my husband aspecting nothing but delicious landmark Italian food,instead, we got tasteless pizza, salty pasta dishes and over cooked Expensive prices, not compatible with the service they offer."], "output": "[['Italian food', 'positive'], ['pasta dishes', 'negative'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had a great tiem watching the shows and characters and ar food was just what we were looking for."], "output": "[['shows', 'positive'], ['characters', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This was followed by various wacky hijinks: overly sweet foie de gras, lack of extra ginger/soy sauce, minute portions even for sushi, appetizers arriving at different times."], "output": "[['portions', 'negative'], ['appetizers', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We ordered a variety of appetizers including the crabcakes, lobster rolls and poached shrimp-- one was better than the next."], "output": "[['appetizers', 'positive'], ['lobster rolls and poached shrimp', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I expected professionals, but was instead met with an amateur waitstaff that made several ominous errors during the course of the meal."], "output": "[['waitstaff', 'negative'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had a crab and roasted red pepper dip along with a beef empinada for our appetizers, which set the tone of delicious worldly cuisine that we were about to experience."], "output": "[['crab and roasted red pepper dip', 'neutral'], ['beef', 'neutral'], ['appetizers', 'neutral'], ['worldly cuisine', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Service is one thing but a restaurant like Craft needs to have much better quality food for the price they charge."], "output": "[['Service', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went there for lunch with co-workers and found the service to be prompt and very friendly."], "output": "[['lunch', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went for lunch and the staff does not welcome you upon entering."], "output": "[['lunch', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There are specials and it's the kind of place sure to please, whether you're seated at the window near the bar or in the outdoor (covered heated when needed) garden in the rear."], "output": "[['place', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food A good way to judge a Thai spot is by its green curry: The all-Thai staff here fashions it spicy and smooth, filled to bursting with meat and thin-sliced bamboo shoots."], "output": "[['Food', 'neutral'], ['green curry', 'neutral'], ['staff', 'neutral'], ['meat', 'neutral'], ['shoots', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is right out of heaven, arrive hungry because the portions are huge but not the prices."], "output": "[['food', 'positive'], ['portions', 'positive'], ['prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Even at lunch, when lawyers and publishers flock in to wheel and deal over the justly-popular lunch buffet, the atmosphere remains serene."], "output": "[['justly-popular lunch buffet', 'neutral'], ['atmosphere', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["And to end the meal try some hazelnut gelato."], "output": "[['meal', 'neutral'], ['gelato', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu showcases Thai-French favorites: fresh chopped hai (white fish) and salmon with Chinese black olives and basil oil; mussels in coconut-lemon grass broth; and garlicky octopus sauteed with ground pork, broccoli rabe and lime juice."], "output": "[['menu', 'neutral'], ['chopped hai (white fish)', 'positive'], ['octopus sauteed with ground pork', 'positive'], ['rabe', 'neutral'], ['lime juice', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["From having an appetizer, a glass of wine and reading a magazine to sitting by a table to work on my grades, to meeting other fellow teachers for a book club to partying with the owners all my experiences at Futura have always been extremely postive!"], "output": "[['appetizer', 'neutral'], ['glass of wine', 'neutral'], ['table', 'neutral'], ['owners', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Please try to order a dish that is served with the corn cake."], "output": "[['dish', 'positive'], ['corn cake', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This past Memorial day weekend was hot and I asked the waiter why was the air condition not working and he responded doens't know why."], "output": "[['waiter', 'negative'], ['air', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The place was practically empty when my friends and I got there for dinner."], "output": "[['place', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The wine list is short and the wine glasses suck (not spigleau or riedel, in addition they are small for the big italian wines on the menu)."], "output": "[['wine list', 'negative'], ['italian wines', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Its good to go there for drinks if you don't want to get drunk because you'll be lucky if you can get one drink an hour the service is so bad."], "output": "[['drinks', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We ate here once and the waiter was very aggressive about pushing the specials instead of what was on the menu."], "output": "[['waiter', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["On the table you will also find individual bottles of fine imported olive oil which we put on the bread-fantastic!"], "output": "[['table', 'neutral'], ['olive oil', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our group of 8 had about five small plates that we thought were the best on the menu."], "output": "[['plates', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the bread they served as we sat down had a pastry-like crunch on the outside and still warm."], "output": "[['bread', 'positive'], ['served', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Buffet fare is better than the regular menu and you don't have to deal with the waitstaff."], "output": "[['menu', 'neutral'], ['waitstaff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The chef insisted that the meat was cooked properly!?"], "output": "[['chef', 'negative'], ['meat', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["With some good sake, I tried the salmon, yellowtail, king crab, eel (thought this would turn my stomach), red white tuna."], "output": "[['sake', 'positive'], ['salmon', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have had some bad meals in my day, but the way we were treated here, takes the cake."], "output": "[['meals', 'negative'], ['cake', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": [" Staple entrees like moussaka more than make the grade, but the selection of clay pot-cooked dishes--tender lamb with orzo, or fish of the day with eggplant and zucchini--take comfort food to a new level."], "output": "[['entrees', 'neutral'], ['lamb with orzo', 'positive'], ['fish', 'neutral'], ['eggplant and zucchini', 'neutral'], ['comfort food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This pizza is the BEST anywhere for grandma slices!"], "output": "[['pizza', 'positive'], ['grandma slices', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My date and I were excited to go, and didn't even mind the 25 minute wait (EVEN WITH OUR RESERVATION) to get a table."], "output": "[['wait', 'negative'], ['RESERVATION', 'neutral'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Well on a friday or sat, i think this place should take reservations as it gets pretty busy."], "output": "[['place', 'negative'], ['reservations', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Unfortunately, our waiter set quite a different tone; he disappeared until the end of our meal, when we had to beg for coffees and desserts."], "output": "[['waiter', 'negative'], ['meal', 'neutral'], ['desserts', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the manager will be very defensive and tell you the chef, his brother, has not changed in 4 years."], "output": "[['manager', 'negative'], ['chef', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is consistantly great, but the wait is often long and the noise is often deafening."], "output": "[['food', 'positive'], ['wait', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the most expensive dish on the menu was $14!!!"], "output": "[['dish', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The manager then told us we could order from whatever menu we wanted but by that time we were so annoyed with the waiter and the resturant that we let and went some place else."], "output": "[['manager', 'neutral'], ['menu', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They also have great vegearian sushi options, try the AAC (avocado, asparagus and cucumber) roll!"], "output": "[['sushi options', 'positive'], ['asparagus and cucumber', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was very good, especially for the Restaurant Week menu price, although it seemed like the 'hits' would be the ceviche and other small dishes that weren't part of the menu."], "output": "[['food', 'positive'], ['ceviche', 'neutral'], ['dishes', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For dinner: I always go for the fish and it's always cooked just right."], "output": "[['dinner', 'neutral'], ['fish', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When the hostess finally appears she tells me that she can't seat us on the mostly empty patio because all the open tables are for dinner not drinks."], "output": "[['hostess', 'negative'], ['patio', 'neutral'], ['open tables', 'neutral'], ['dinner', 'neutral'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["An amazing combination of a place to sit down with the family and have a good time or have a drink at the bar with some friends."], "output": "[['place', 'positive'], ['drink', 'neutral'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My prefix dinner was composed of garlic shrimp appetizer followed by a yummy skirt steak complete with handcut fries."], "output": "[['prefix dinner', 'neutral'], ['garlic shrimp appetizer', 'neutral'], ['steak', 'positive'], ['fries', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Deborah, the chef and co-owner, is an extraordinary talent - she has not received the notoriety she deserves - and her food, while not expensive, really merits a two or three star rating."], "output": "[['chef', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Friendly staff happily accepted a reservation (for 10), and when only 6 showed up, they couldn't have been more understanding!"], "output": "[['staff', 'positive'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We should have had the entire restaurant, but the manager let some random lady sit up at the bar because she was a regular."], "output": "[['manager', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["mistake on the check, overly salty morels stuffed with foie gras) but overall, Daniel's dishes are revelations in taste."], "output": "[['check', 'neutral'], ['dishes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A special appetizer called Vegetable Carpaccio with Salmon was delicious."], "output": "[['Vegetable Carpaccio', 'positive'], ['Salmon', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The manager refused to talk to me sending the waiter to tell me to tell me that he was not available, when I had previously seen him doing absolutely nothing at the bar."], "output": "[['manager', 'negative'], ['waiter', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is average and the service is insulting."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter accidently spilled water on our table, and the manager checked up on our meal periodically and offered us a free after diner drink."], "output": "[['waiter', 'negative'], ['water', 'neutral'], ['table', 'neutral'], ['manager', 'positive'], ['meal', 'neutral'], ['diner drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Last night the dining room was crammed and seemingly only had one waiter which is ludicrous."], "output": "[['dining room', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It is so difficult to choose a favorite on the menu, because the bolognese, the salmon, the chicken with mushroom, and the telephono are all too good to rank."], "output": "[['menu', 'neutral'], ['salmon', 'positive'], ['chicken with mushroom', 'positive'], ['telephono', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Amarin's food is always fresh, although the quality does vary--avoid ordering on Friday Saturday nights, prime dining hours, when they seem to throw things togehter a little too haphazardly."], "output": "[['food', 'positive'], ['quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We tried to place the order and the waiter had no clue what we wanted even though we pointed it out on the menu."], "output": "[['waiter', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["One of the waitstaff spilled a huge drink on the floor that splattered everyone nearby, no offering of apology was made or to foot the drycleaning bill and no comp was offered either."], "output": "[['waitstaff', 'negative'], ['drink', 'positive'], ['drycleaning bill', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We arrived, were greeeted and sked by the hostess I think if we were there for the Brunch, that was starting up again on today(3/12) the cost $25 per person."], "output": "[['hostess', 'positive'], ['Brunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["And after we ordered our food, their wine guy suggested the wine that he thought would go best with our selections, and it was surprisingly not a high-priced bottle."], "output": "[['food', 'neutral'], ['bottle', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Ordered a beer from the bartender, she opened it and the told me that she didn't know the price !!"], "output": "[['beer', 'neutral'], ['bartender', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Nice decor poor food poor service."], "output": "[['decor', 'positive'], ['food', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Went to dinner for a law firm recruiting event, and the service was abysmal."], "output": "[['dinner', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["She also has to beg for water refills squeeze her smallish rear-end between crowded tables."], "output": "[['water', 'neutral'], ['tables', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Appetizers were good - we had the scallops and a salad."], "output": "[['Appetizers', 'positive'], ['scallops', 'neutral'], ['salad', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Also, neither our waiter or busboy ever came back to ask if we wanted more to drink or even refill our WATER glasses."], "output": "[['waiter', 'negative'], ['drink', 'neutral'], ['WATER glasses', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The restaurant has a modern look with remarkable tables and bar."], "output": "[['tables', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the service was inattentive (didn't bring us wine til our main course was already served and didn't open the bottle in front of us!!!"], "output": "[['service', 'negative'], ['wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Servers struggle to explain the menu to those who can't tell an idli from a chapathi, but the mostly Indian clientele is completely at home with the vegetarian South Indian fare."], "output": "[['Servers', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They brought my mother a chicken enchiladas instead of cheese and then it took her 10 minutes to explain what the error was to the waiter and bus boy who then finally had to tell the manager who was also confused and my mother is fluent in Spanish."], "output": "[['cheese', 'neutral'], ['waiter', 'negative'], ['manager', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["we ordered filets, and ny steaks eventhough our waiter kept pushing up to get the porterhouse."], "output": "[['steaks', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The House salad is big enough to split, The Fried Calamari is some of the best I ever ate, the bowties broccoli, broccoli rabe, square slices, broiled filet of sole, clam sauce."], "output": "[['House salad', 'positive'], ['Fried Calamari', 'positive'], ['slices', 'neutral'], ['sole', 'neutral'], ['clam sauce', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The wine kept coming and we were having such a great time, we didn't realize our entree still had not come an hour later."], "output": "[['wine', 'positive'], ['entree', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Prompt local delivery, minimal seating and counter space."], "output": "[['delivery', 'positive'], ['seating', 'neutral'], ['counter space', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Cheese on the bottom, sauce on top - not too thick or doughy."], "output": "[['Cheese', 'negative'], ['bottom', 'neutral'], ['sauce', 'neutral'], ['top', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Called to make a reservation and b/c the man who answered was so nice decided to chance it."], "output": "[['reservation', 'neutral'], ['man', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter seemed truly disinterested (he forgot to bring the bread basket and the wine was served after he delivered the entrees."], "output": "[['waiter', 'negative'], ['bread', 'neutral'], ['wine', 'neutral'], ['served', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After arriving we were told to wait at the bar, where there wasn't an inch of space so we remained in the tiny area near the coat check."], "output": "[['bar', 'neutral'], ['space', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitress even gave us a complimentary dessert- warm chocolate lava cake with a scoop of cinnamon ice cream, what a perfect end to a perfect dinner!"], "output": "[['waitress', 'positive'], ['ice cream', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Once the waitress cursed our table for not tipping enough after we had waited an hour to order and another half an hour just to get a drink, on top of this I had to find my own cutlery."], "output": "[['waitress', 'negative'], ['table', 'neutral'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was equally outstanding: I had the fois gras and rack of lamb, along with the Brooklyn Bridge for dessert."], "output": "[['food', 'positive'], ['fois gras', 'neutral'], ['rack of lamb', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We started with some drinks on the front porch and then continued at our table with a bottle of delicious red wine."], "output": "[['table', 'neutral'], ['wine', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It also has great ice cream and spumoni ices."], "output": "[['cream', 'positive'], ['ices', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter's knowledge of the menu and ability to make recommendations were ridiculously bad, requests weren't observed effectively, and our water and wine glasses were not kept full."], "output": "[['waiter', 'negative'], ['menu', 'neutral'], ['water and wine glasses', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They have Boylan's root beer, coffee that's freshly ground that day, and a relaxed casual atmosphere with friendly waitresses."], "output": "[['root beer', 'neutral'], ['coffee', 'neutral'], ['ground', 'positive'], ['atmosphere', 'positive'], ['waitresses', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had the Margarita pizza, calamari appetizer, salmon entree and the tira misu for dessert."], "output": "[['Margarita pizza', 'neutral'], ['calamari appetizer', 'neutral'], ['salmon entree', 'neutral'], ['dessert', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["On ouor visit, our reservation was ignored and then we were asked to move from our seats at the bar, where we were told to wait, because we were not drinking enough."], "output": "[['reservation', 'negative'], ['seats', 'neutral'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Love the pizza here (although the slices aren't as fresh at 3am, but who's that picky when you're drunk), and there's plenty of other good stuff."], "output": "[['slices', 'negative'], ['stuff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["These guys do not skimp on drinks or quality of food."], "output": "[['drinks', 'negative'], ['quality', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The party space worked out well for our rehearsal dinner."], "output": "[['party space', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu is informatively presented with facts about the ingredients, and is divided into Starting and Sharing plates, which allows one to sample a few items during the meal."], "output": "[['menu', 'positive'], ['ingredients', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Service was slow (20 minutes wait time before they came back with our drinks, not including 10 minute wait for them to take our drink order)."], "output": "[['Service', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I am allergic to certain types of foods and he was very knowledgeable about the menu and brought our drinks and food very fast."], "output": "[['foods', 'positive'], ['menu', 'neutral'], ['drinks', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Atmosphere in the formal room was nice, but the informal dining room was extremely loud which ultimately made the formal room louder than my perference."], "output": "[['Atmosphere', 'positive'], ['informal dining room', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The goat cheese and sun dried tomato ravioli is great, the bread may be a little weak, but the calamari is nice."], "output": "[['goat cheese', 'positive'], ['sun dried tomato ravioli', 'positive'], ['bread', 'negative'], ['calamari', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The manager was very thoughtful to have the chef make me a dish not on the menu to my liking."], "output": "[['manager', 'positive'], ['chef', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["mapQuest before you go and you'll arrive early enough start off at the bar with a fabulous old school cocktail."], "output": "[['bar', 'neutral'], ['school cocktail', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The wait could be long because of the limited number of seats but it is worth it, especially if you leave your cell phone # with them and go off for a drink at any one fo the excellent bars nearby, like lokie, great lake, etc."], "output": "[['wait', 'negative'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Even though it's a trek for me to get there and the place is a little of a Hole in the wall, I've gone many times for the food alone."], "output": "[['place', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["But overall loved the place, outside of our waiter who literally tried to force us into ordering drinks."], "output": "[['waiter', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Ambiance is nice; music is CD 101."], "output": "[['Ambiance', 'positive'], ['music', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you want great Italian food, fairly price, good service, in Brooklyn, a couple of subway stops from Union Square,(where you should complain about the prices) go to Al Di La."], "output": "[['Italian food', 'positive'], ['service', 'positive'], ['prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service was slow (10 minutes for drinks??)"], "output": "[['service', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The former generally succeeds quite well: Rich tarragon-scented macaroni and cheese is a big crowd-pleaser, served steaming in hefty individual casseroles; likewise the sizeable burger and herbed fries, and the dense milkshakes."], "output": "[['individual casseroles', 'positive'], ['fries', 'neutral'], ['dense milkshakes', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene There are no rules at Sarge's: It's open 24/7 and serves every kind of food--from potato latkes to chicken and ribs--to every kind of customer, from businesspeople at breakfast to recuperating club kids at 4am."], "output": "[['food', 'positive'], ['breakfast', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter actually said he would check with the chef, like they might force us to share our food."], "output": "[['waiter', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Service was good, except for a very long gap between appetizers (which came out too quickly) and entree (whick took another 45 minutes to arrive)."], "output": "[['Service', 'positive'], ['entree', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Try the Phothe Broth look like soy sauce), spring rolls(can't compare any other vietnamese restaurant, Fish sauce(too much lime, Beef vermecelli ( Blanb and chewie)."], "output": "[['Fish sauce', 'negative'], ['Beef', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food : A++ Service : A++ Value : A++ No other steakhouse in Manhattan can beat Ruth's Chris."], "output": "[['Food', 'neutral'], ['Service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service is more than attentive, and they also have a $10 corking fee so you can bring your own wine."], "output": "[['service', 'positive'], ['wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My greek salad cost about $9 and for that price, I would not have expected chopped olive (as opposed to whole), and shredded bits of lettuce."], "output": "[['price', 'neutral'], ['chopped olive', 'negative'], ['lettuce', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["since it is kinda small less than 20 tables, but room downstairs for private parties."], "output": "[['tables', 'negative'], ['downstairs', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["they waited to get us water after they took our food orders, which took the waitstaff a long time to do."], "output": "[['food', 'neutral'], ['waitstaff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the manager said that they were just starting with a preview menu."], "output": "[['manager', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The bartender virtually ignored us while we waited, took 15 minutes to get drinks."], "output": "[['bartender', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Needless to say I will rather go spend $400 on dinner somewhere else wirh better service."], "output": "[['dinner', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Thankfully, the steak was good, but the food couldn't save the restaurant from a bad rating."], "output": "[['steak', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Decor is simple yet functional and although the staff are not the most attentive in the world, you don't feel rushed and the food is good, hot with decent portion sizes and a good selection to suit most tastes."], "output": "[['Decor', 'positive'], ['staff', 'negative'], ['food', 'positive'], ['portion', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Expect to get average food, a big bill and lots of attitude from the service."], "output": "[['food', 'neutral'], ['bill', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It's in a less travelled spot on 3rd, but the intimate setting is great and romantic."], "output": "[['spot', 'negative'], ['setting', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Lost reservations, out of liquor, jam-packed, waiting room, out of wine, sent steak out raw, no choices for dessert, no room to breathe, terrible service, etc."], "output": "[['reservations', 'negative'], ['waiting room', 'neutral'], ['steak', 'negative'], ['dessert', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service was lacking a bit, we waited about 20 mins for a waiter and water to come to us once we were sat and we had to ask for everything twice, even drink orders - I think maybe we just got stuck with a bad waiter though."], "output": "[['service', 'negative'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Fresh fish, tender milk fed veal and outrageous Veal Chops adorn their menu and special list."], "output": "[['fish', 'positive'], ['menu', 'neutral'], ['list', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They served the main course before the appetizers eventhough we asked for the latter first, to which our waiter responded that they don't serve them separately without telling us beforehand while ordering."], "output": "[['appetizers', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Pupusas, filled with pork, beans, chicken or cheese, are sumptuous pancakes bursting with the flavor of fresh corn."], "output": "[['beans', 'neutral'], ['chicken', 'neutral'], ['pancakes', 'positive'], ['flavor', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Chef Anthony is warm and is always fixing up something unique and tasty in the kitchen to send to your table."], "output": "[['Chef', 'positive'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our appetizers arrived soon after, and a few minutes later were followed by our main courses."], "output": "[['appetizers', 'positive'], ['courses', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My reservation for 2 was during lunch and it seemed that because I was literally 2 minutes late, the hostess felt the need to seat every party before mine."], "output": "[['reservation', 'neutral'], ['lunch', 'neutral'], ['hostess', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The garden is lovely, too, but the staff seems a bit condescending."], "output": "[['garden', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Customers MUST order one entre each if dining outdoors, they will not seat you unless your entire group is present (nor will they hold a table) and they make it clear that they want to turn tables."], "output": "[['dining outdoors', 'neutral'], ['seat', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Though the wait staff was attentive, when the raw (really, not al dente) potatoes were brought to our server's attention, she listened but didn't respond."], "output": "[['wait staff', 'positive'], ['potatoes', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I loved my kimchee stew with bits of shredded pork and just enough hotness to clear the sinuses, but not kill all other flavors."], "output": "[['stew', 'positive'], ['shredded pork', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["However the casual atmosphere comes in handy if you want a good place to drop in and get food."], "output": "[['atmosphere', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When we showed up at the restaurant, the manager claimed that I made reservation for TWO instead of TEN and flat out told us we don't seat that many and refused to even apologize for the miss communication."], "output": "[['manager', 'negative'], ['reservation', 'neutral'], ['communication', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu offered unique options and my friends enjoyed their food, but my lentil avacado salad was not better or more interesting than the lunch counter at Saks and my John Dory was overcooked."], "output": "[['menu', 'positive'], ['lentil avacado salad', 'negative'], ['lunch counter', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you are a person who wants perfect service, you should probably skip it, you may wait for your server to sing a song before you get your drinks but that is half the fun."], "output": "[['service', 'positive'], ['server', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My favorite part of dinner was the Oyster Quail Egg Shooters."], "output": "[['dinner', 'neutral'], ['Oyster Quail Egg Shooters', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The bar seemed like a good place to sit and have some food as we were not even offered a table."], "output": "[['bar', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When we proceeded to order our food, the waitress interrupted and told us that maybe we had ordered enough for now."], "output": "[['food', 'neutral'], ['waitress', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Walked in on Chinese New Year Sunday late in the afternoon, around 5 or 6 -- seating was not a problem the dim sum was deliciously fresh -- very likely a by-product of their not using carts."], "output": "[['seating', 'neutral'], ['carts', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Never will you taste sicilian Pizza and Spumoni like LBs."], "output": "[['sicilian Pizza', 'negative'], ['LBs', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Get a Big beer to wash it all down and a side of potatoes and garlic bread."], "output": "[['beer', 'positive'], ['garlic bread', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Do not use this place unless you want to waste your money on horrible stale cheese and food, service which takes your drinks away from the table once you've placed it on the table, waiters that eat your desert while its on the table, non working faucets in the bathroom, and overall very unporfessional service and food."], "output": "[['cheese', 'negative'], ['drinks', 'neutral'], ['waiters', 'negative'], ['bathroom', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The owner was rude to us from the moment we sat down until he told us we had to leave because he had another table waiting, and this despite ordering the pricier entrees from the menu and a bottle of wine that we hadn't yet finished."], "output": "[['owner', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When we finally ordered our wine, the waitress brought the bottle of wine over with ONE GLASS MISSING - meaning, we'd have to wait even longer for the final glass to arrive - which were all piping hot from the dishwasher."], "output": "[['waitress', 'negative'], ['bottle of wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While the drinks didn't come in large glasses and the arepas were not large in size, they had a taste about them that made you only want more."], "output": "[['drinks', 'negative'], ['arepas', 'negative'], ['taste', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Don't expect trendy atmosphere: room looks like it could have been designed in 1940s, but who cares - it's actually comfortable and inviting; with great food and unbeatable value, you can't go wrong."], "output": "[['atmosphere', 'negative'], ['food', 'positive'], ['value', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["As for price, there are plenty of Shanghai restaurants in Chinatown that are just as inexpensive with better food and without a doubt much better customer service."], "output": "[['price', 'neutral'], ['food', 'positive'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Also, the staff will not allow you to substitute a side dish or accommodate anything that differs from what's on the menu."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Interestingly, cost only becomes truly apparent when dinner is over, as there is no menu before that presented for deserts."], "output": "[['cost', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When one compares the quality of the food to some of the city's other italian restaurants, and then particularly when one factors in the very reasonable prices here, I feel that this restaurant comes out a winner."], "output": "[['quality of the food', 'neutral'], ['prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Egg and Cheese on a bagel here is HUGE."], "output": "[['Egg and Cheese', 'positive'], ['bagel', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The first time I went, and was completely taken by the live jazz band and atmosphere, I ordered the Lobster Cobb Salad."], "output": "[['live jazz band', 'positive'], ['atmosphere', 'positive'], ['Lobster Cobb Salad', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu might have well been written in a foreign language and the wait staff didnt have a translation dictionary!"], "output": "[['menu', 'neutral'], ['wait staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My party of 8 had a seafood feast sampling Sammy's menu and we couldn't believe how great the food was."], "output": "[['seafood', 'neutral'], ['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our server didn't have the sommelier stop by when we were trying to decide on wines, he never brought the bread we requested and didn't crack a smile the whole evening until he saw that I was paying the tab when he suddenly became nicer."], "output": "[['server', 'negative'], ['wines', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["But if you're looking for a fun time at a place that isnt trying so hard to be the next it place, then just hang at rice to riches instead where they actually value their patrons and dont make you wait."], "output": "[['rice', 'neutral'], ['patrons', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["our appetizers came out relatively quickly, but it was near impossible to get a hold of a waiter to order and get our drinks."], "output": "[['appetizers', 'positive'], ['waiter', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The entertainment was great they have shows that go on through out the dinner."], "output": "[['entertainment', 'positive'], ['shows', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Portions were certainly substantial for lunch."], "output": "[['Portions', 'negative'], ['lunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu of Afghani favorites includes mantoo, the spicy beef dumplings in yogurt sauce; chicken with walnuts and pomegranate juice; saffron-marinated filet mignon; grilled Cornish game hen; meat and fish kebabs in various combinations; and a number of vegetarian rice- and bean-based dishes."], "output": "[['menu', 'neutral'], ['filet mignon', 'positive'], ['grilled Cornish', 'positive'], ['hen', 'positive'], ['fish kebabs', 'positive'], ['dishes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The restaurant has a somewhat unique decor, with portrait of the owner meditating and books about meditation."], "output": "[['decor', 'positive'], ['owner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Their cappuccino's are served in a generous mug with a bit too much milk and too-sudsy foam."], "output": "[['served', 'positive'], ['milk', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiters do not tell you that and our large party wound up with over $100 extra food because all members thought dessert, coffee/tea were included - which they lead you to believe - and they weren't."], "output": "[['waiters', 'negative'], ['dessert', 'neutral'], ['coffee/tea', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My friends and I tried practically every strange, inventive dish on the menu, most of which are very tasty."], "output": "[['dish', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Apple sourdough pie, and orange cake are good, as is the bundt cake with a rich chocolaty filling and the cupcakes."], "output": "[['Apple sourdough pie', 'positive'], ['orange cake', 'positive'], ['bundt cake', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was not terrible but with the prices as high as they are, I should expect better."], "output": "[['food', 'positive'], ['prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When she wasn't being sarcastic or downright rude, she spent her time studiously ignoring our table or pointing us out to the other waitstaff."], "output": "[['table', 'negative'], ['waitstaff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is worth going for, but the boys in behind the bar in the lounge are what keep me coming back!"], "output": "[['food', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For entrees, the Ground Lamb in Spicy Sauce (can't remember the name on the menu) was perfectly cooked and had just enough kick for the average person."], "output": "[['Ground Lamb in Spicy Sauce', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["why go there to deal with staffs' attitude and eat bad food?"], "output": "[['staffs', 'neutral'], ['attitude', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The owner sat with us and asked us what fish we liked and prepared an entree for each of us with an array of seafood."], "output": "[['owner', 'positive'], ['fish', 'neutral'], ['entree', 'neutral'], ['seafood', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After dinner I thanked the bartender and told him how this was the only good French food we had found in Manhattan."], "output": "[['dinner', 'neutral'], ['bartender', 'positive'], ['French food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Because its kindly sushi chief and his co-worker, it makes me want to have my dinner there all the time."], "output": "[['sushi', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were seated quickly (and had reservations, but they didnt seem to be absolutely necessary) and our waitress offered much insight into menu bests and worsts."], "output": "[['reservations', 'neutral'], ['waitress', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In the 20 minutes we spent waiting just for a server to take our wine order, the host of this establishment proceeded to let couple after couple walk right in in-front of us because he obviously knew them."], "output": "[['server', 'neutral'], ['wine', 'neutral'], ['host', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["B/c the dinner focused on good friends and good food, not waiting around for service or being bothered by rude staff to leave."], "output": "[['food', 'positive'], ['service', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Then we were led downstairs to the main room, and were seated at the huge communal dining room table."], "output": "[['seated', 'neutral'], ['dining room table', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the waiter was unable to identify whether certain cheeses from the cheese course were cow or goat milk."], "output": "[['waiter', 'negative'], ['cheeses', 'neutral'], ['the cheese course', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Some advice: have the prime rib if it is a special, try a price fix lunch or dinner because it is an exceptional value."], "output": "[['prime rib', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had spicy halibut with some sauces I can't remember."], "output": "[['halibut', 'positive'], ['sauces', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We ordered the Tuna a la carte and Wild Salmon and chicken breast on the Prix Fixe."], "output": "[['Tuna a la carte', 'positive'], ['Wild Salmon and chicken breast', 'positive'], ['Prix Fixe', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["great trendy spot for a night out but to be honest the food was not worth the cost."], "output": "[['spot', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food was fine, and the place is pretty cool, but the waitstaff was slow and pretty clueless."], "output": "[['Food', 'positive'], ['place', 'positive'], ['waitstaff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Be prepared to sip the finest wines and dine on such splendid flavors as the Torellini Bottega (hand-made tortellini filled with prosciutto, veal and beef in a porcini-butter sauce -- it is to die for!"], "output": "[['dine', 'neutral'], ['flavors', 'positive'], ['tortellini filled with prosciutto', 'positive'], ['beef in a porcini-butter sauce', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service wasn't good -- dumplings were served after we had almost finished the main courses, drinks had to be asked for three times, etc."], "output": "[['service', 'negative'], ['dumplings', 'neutral'], ['served', 'negative'], ['main courses', 'neutral'], ['drinks', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The staff is cool and friendly, and the place has been around since J."], "output": "[['staff', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service was horrendous, not only did the waiter take an hour to remember we ordered drinks, we were rushed to eat and get out so they could seat the next party."], "output": "[['service', 'negative'], ['waiter', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There's very little on their menu if you're trying to avoid cheese and oil - not many grilled entrees at all."], "output": "[['menu', 'neutral'], ['oil', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was good, but it's not worth the wait--or the lousy service."], "output": "[['food', 'positive'], ['wait', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The problem was that we waited for a long time to get our waitress, we had to ask the bus boy for refills for drinks, and we waited for a long time to pay for our check."], "output": "[['waitress', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter didn't go over the menu choices and at the end of the night we were so fed up we didn't even order dessert."], "output": "[['waiter', 'negative'], ['menu choices', 'neutral'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["And the ambience is very cool, stop by on a Saturday afternoon and you can play some old school games while having a beer."], "output": "[['ambience', 'positive'], ['beer', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["yes as I sat at the table waiting just under 1 HOUR for my food, i was quite tempted to step across the road for a quick snack."], "output": "[['table waiting', 'neutral'], ['snack', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitstaff brought us so many free tapas (chilled mussels, spare ribs, chorizo, sauteed shrimp) along with our house salad and bread that we barely had room for the entrees."], "output": "[['waitstaff', 'positive'], ['tapas', 'positive'], ['ribs', 'neutral'], ['house salad', 'neutral'], ['bread', 'neutral'], ['entrees', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When we arrived there was no free table so we waited at the bar for quite a long time."], "output": "[['table', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waitress (and the chef himself) helped us a bit with the Austrian cuisine where we had questions, and every recommendation was right on."], "output": "[['waitress', 'positive'], ['chef', 'positive'], ['Austrian cuisine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitress came back with the bill and money (with a calculator) and asked for more tips."], "output": "[['waitress', 'negative'], ['money', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Classic seafood offerings include lobster tails, steamed crab legs and wild Alaskan salmon; sides, served a la carte, include baked potato and chipotle mac and cheese."], "output": "[['seafood offerings', 'positive'], ['lobster tails, steamed crab legs', 'neutral'], ['wild Alaskan salmon', 'neutral'], ['sides', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Italian cheesecake, Cassata Al Forno and pastries you never saw in other bakeries are great."], "output": "[['cheesecake', 'neutral'], ['pastries', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Anyway after witnessing the owner abusing some of the staff and scarfing down the college dorm made pasta we left; the momentum of the night gone we were all drained from the bad dining experience and just went home."], "output": "[['owner', 'negative'], ['staff', 'neutral'], ['pasta', 'neutral'], ['dining', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When I tried getting a lunch order delivered, I was told I was out of the delivery range (strange since I am also located in the East Village)."], "output": "[['lunch', 'neutral'], ['delivery range', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["FOOD WAS OK,SERVICE NOT SO OK,WAITED FOR THE CHECK WHILE OUR WAITER WAS GOSSIPPING,WAITED FOR CHANGE,WHILE OUR WAITER WAS GOSSIPPING."], "output": "[['FOOD', 'positive'], ['SERVICE', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["big chunk of meat(beef short rib)."], "output": "[['chunk', 'positive'], ['beef short rib', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have told so many people to come here even my friend from Japan and we all love it, especially when we get the room for all of us to sit in our own little world eating tons of good sushi!"], "output": "[['room', 'neutral'], ['sushi', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was good but we were dissatisfied with waiting too long for a uncomfortable table."], "output": "[['food', 'positive'], ['waiting', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The bartender informed me the place was full, and the wait was 30 minutes."], "output": "[['place', 'negative'], ['wait', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food The pan-Italian menu forgoes the appetizer-entree format in favor of fairly priced small plates, which quickly add up."], "output": "[['Food', 'neutral'], ['pan-Italian menu', 'neutral'], ['priced', 'positive'], ['plates', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Huge selection of farm roasted coffee served with a smile, absolutely no attitude, and accompanied with the best pastries in Manhattan."], "output": "[['farm roasted coffee served', 'positive'], ['attitude', 'negative'], ['pastries', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We tried the Tasting menu', and the manager offered to select the items to be served after taking inputs from us ( Choice of meat, allergies etc."], "output": "[['menu', 'positive'], ['manager', 'positive'], ['served', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The manager also refused to remove the drink from the check, suggesting that if we didnt like it, we could simply remove the corn ourselves."], "output": "[['manager', 'negative'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Well, the manager rudely informed us that this was how the food is supposed to be served (one course every 30 or so minutes) and then claimed that Oliva is NOT a tapas restaurant."], "output": "[['manager', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The lengthy menu includes the likes of mee krob (glass noodles with shrimp, chicken and pork in plum sauce), nur-yang-num-tok (barbecued flank steak served with a spicy sauce), pork with chili and basil leaves and spicy, bean curd coconut milk soup."], "output": "[['lengthy menu', 'neutral'], ['pork in plum sauce', 'neutral'], ['pork with chili and basil leaves', 'neutral'], ['bean curd coconut milk soup', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I haven't tried a lot of their menu however their appitizers are tasty and fairly priced."], "output": "[['menu', 'neutral'], ['appitizers', 'positive'], ['priced', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the waiter never asked if we would like more drinks, we had to flag him down and ask him and then when he brought them he forget two of them."], "output": "[['waiter', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We let the very kind hostess know we were there and had some drinks at the bar."], "output": "[['hostess', 'positive'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A bit noisy at street for the hospital a block away, but relaxing for drinks or appetizers (Ceviche, Croquetas, Empanas, Serrano Pizza, Calamar) and a BIG 10 for the main entrees (Argentinian Steak, Pata Chancho, Salmon)."], "output": "[['drinks', 'negative'], ['appetizers', 'negative'], ['Croquetas', 'neutral'], ['main entrees', 'neutral'], ['Salmon', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We asked the chef if it was possible to have two different tasting menus, to which he was quick and eager to comply."], "output": "[['chef', 'neutral'], ['menus', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The server rolled his eyes when we ordered only an entree per person (with no appetizers), spoke curtly to us, and ignored our requests for more water etc."], "output": "[['server', 'negative'], ['entree', 'neutral'], ['appetizers', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It was topped with pan roasted new onions and it lent the meat a great flavor."], "output": "[['pan roasted new onions', 'positive'], ['meat', 'neutral'], ['flavor', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I was told by the hostess that a specific table would be mine once the customers left and I waited 45 minutes for that to happen."], "output": "[['hostess', 'negative'], ['specific table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After finally choosing banana-macadamia nut pancakes (a Hawaiian favorite of mine) after being unable to decide between 4 or 5 dishes that all sounded spectacular, I sat back and enjoyed the (complementary) tall shot glass of the smoothie of the day."], "output": "[['dishes', 'neutral'], ['glass', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A server came shortly after that with a cheeseburger, which is not what i ordered."], "output": "[['server', 'negative'], ['cheeseburger', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I especially recommend ordering the duck, foie gras, and beef cheeks although it's probably hard to go wrong with anything on the menu."], "output": "[['duck, foie gras', 'positive'], ['beef', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I would not recommend this place until they get a new staff that can complement the food."], "output": "[['new staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["07 menu was a deal to try this hip tribeca restaurant but the wrong dessert was sent to the table."], "output": "[['dessert', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We tried the duck quesadilla (good), a house special maki roll (nothing special), salmon 3 ways (dry+overcooked), and jumbo prawns (super salty)."], "output": "[['duck quesadilla', 'positive'], ['maki roll', 'neutral'], ['salmon', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu contains both Japanese fusion and plain Italian dishes - everyone should be able to find something they like."], "output": "[['menu contains', 'neutral'], ['Japanese fusion', 'neutral'], ['Italian dishes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Rather you are paying rock bottom price for a meal that could cost you triple any where else."], "output": "[['price', 'negative'], ['meal', 'neutral'], ['cost', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu offers a lineup of USDA prime steaks at higher-end prices paired with sides such as crab cakes, fried oysters and onion rings."], "output": "[['menu', 'neutral'], ['prices', 'positive'], ['sides', 'neutral'], ['crab cakes', 'neutral'], ['fried oysters and onion rings', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A blink-and-you-missed, tiny bar lines the lefthand side wall as you enter, which is packed with neighborhood hipsters, but it sadly interferes with the tables filled with dining patrons that are forking out mega bucks for mediocre fare."], "output": "[['bar', 'negative'], ['tables filled with dining patrons', 'neutral'], ['fare', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When I got the bill and saw I was billed separately for each cup of coffee, I asked the waiter if he could do anything since the menu doesn't even list drinks and the manager said no."], "output": "[['cup', 'neutral'], ['coffee', 'neutral'], ['menu', 'neutral'], ['drinks', 'neutral'], ['manager', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Only con was the cost -- our dinner for two was $400!"], "output": "[['cost', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When I went in for dinner this Sunday, after a 2 month absence, I noticed their addition of table cloths, which really add to the ambiance and I noticed that their wine list has been expanded."], "output": "[['dinner', 'neutral'], ['table cloths', 'neutral'], ['wine list', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Paying that high price, I could have dined at other places with better food and service."], "output": "[['price', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["i've ordered a cheese plate there, too- the kitchen makes it for you even though it's not on the menu!"], "output": "[['cheese', 'neutral'], ['kitchen', 'positive'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I politely asked the waitress to explain these charges noting that the menu was misleading and she got frustrated mad and then told her manager."], "output": "[['waitress', 'negative'], ['menu', 'neutral'], ['manager', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene Rows of glass-topped, red-tableclothed tables stretch back to the rear of the brightly lit space, whose white walls hold a few seafaring decorations--a boat painting here, a captain's wheel there."], "output": "[['Scene', 'negative'], ['tables', 'negative'], ['lit space', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the busboys were fantastic -- very attentive when it came to replenishing chips, removing dishes, but I have to say the waitress service was not quite as good."], "output": "[['chips', 'neutral'], ['dishes', 'neutral'], ['waitress service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While waiting we asked the bartender for at glass of red wine which he not only forgot to serve but when we asked him again 10min later he poured us white wine."], "output": "[['bartender', 'negative'], ['glass of red wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["when I came back for brunch a week or so later, I was told that the marscapone version was no longer being served, because there was a new cook."], "output": "[['brunch', 'neutral'], ['marscapone version', 'neutral'], ['served', 'negative'], ['cook', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For breakfast, thick, fluffy brioche French toast, served with maple butter and fresh berries, excels; likewise, a clever sandwich of scrambled eggs and tomato jam in a light, salty buttermilk biscuit."], "output": "[['breakfast', 'neutral'], ['brioche French toast', 'positive'], ['sandwich of scrambled eggs and tomato jam', 'positive'], ['biscuit', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It's got above-average diner and italian fare, and it's right near the subway."], "output": "[['diner', 'positive'], ['fare', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I thought the bar was fair in terms of decor, but how long do you have wait at the bar before a bartender with an attitude (he wasn't rude, but not friendly) makes you an awful drink, but food was delightful and music light and tasty as well."], "output": "[['decor', 'positive'], ['bartender', 'negative'], ['drink', 'negative'], ['music', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food was ok, but not worth the 1 hour wait (we sat down an hour after our reservation time) If you are going to make people wait a LONG time, then at least build a bigger bar."], "output": "[['Food', 'positive'], ['reservation', 'neutral'], ['bar', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Xunta's tapas dishes were great though a little pricey for small plates."], "output": "[['tapas dishes', 'positive'], ['plates', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter, though he was charming,was too busy to truly take care of us properly and the food was over priced."], "output": "[['waiter', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When your overzealous kitchen brings out the food all at once way too quickly how about apologizing and have the manager come over."], "output": "[['overzealous kitchen', 'neutral'], ['manager', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The dinner special is amazing, although I would pick the meat option rather than seafood."], "output": "[['dinner special', 'positive'], ['meat', 'positive'], ['seafood', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food, though good for the most part (very good duck and chicken with rice dish, but awful charred squid salad - tasted bitter going down), was the least memorable part of the meal."], "output": "[['food', 'positive'], ['charred squid salad', 'negative'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The place wasn't packed, but there was a bar scene and a few salsa dancers who strutted their stuff on the dancefloor."], "output": "[['place', 'positive'], ['bar scene', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The host actually came over to my table and told me and my date we had to leave because we already paid our bill."], "output": "[['host', 'negative'], ['table', 'neutral'], ['bill', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We ordered one of the specials our decent waiter mentioned, and one of the chicken dishes off the menu."], "output": "[['specials', 'neutral'], ['waiter', 'positive'], ['chicken dishes', 'neutral'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My husband doesn't like vegetables and made a point to ask the waiter if he could have a side of pasta instead."], "output": "[['vegetables', 'negative'], ['waiter', 'neutral'], ['pasta', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The singing wait staff are great, the food is just awful!!"], "output": "[['singing wait staff', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The wait staff was better the second time around and our water glasses were always full."], "output": "[['wait staff', 'positive'], ['water glasses', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["(The booths remained unoccupied throughout our meal, unless you count the not-very-busy waitstaff."], "output": "[['meal', 'neutral'], ['waitstaff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went for an early dinner the other night and encountered the worst service i have experienced in a long time."], "output": "[['dinner', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter placed the wrong entree in front of us each time."], "output": "[['waiter', 'neutral'], ['entree', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Sometimes people get up and dance, overall a pretty fun spot, although the crowd does tend to be over 30."], "output": "[['spot', 'positive'], ['crowd', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["All dishes are an incredible dining experience."], "output": "[['dishes', 'neutral'], ['experience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had calamari for appetizer which was fried to a golden crisp not overdone , and a veal for main course with a side of pumpkin ravioli which was absolutely to die for."], "output": "[['appetizer', 'neutral'], ['veal for main course', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["An unpretentious sexy atmosphere lends itself to the above average wine-list and a menu that can stand-up to any other restaurant in NewYork City (or Paris)."], "output": "[['atmosphere', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I will say that often times they make their drinks very strong (may tell your bartender / waitress to keep it mild)."], "output": "[['drinks', 'negative'], ['bartender', 'neutral'], ['waitress', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the 2 tables next us had undercooked beans, tough hanger steak, mediocre dessert and same vibe about the chicken."], "output": "[['beans', 'negative'], ['hanger steak', 'negative'], ['dessert', 'negative'], ['vibe', 'negative'], ['chicken', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The bar had a hip DJ and the crowd was ultra chic."], "output": "[['bar', 'neutral'], ['DJ', 'positive'], ['crowd', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I'm not a big dessert fan, but I met a friend for a drink there the other night and we found it cuz it was really cozy looking packed with people."], "output": "[['dessert', 'negative'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Crystal Ballroom was closed for a private party, so we couldn't even enjoy the decor."], "output": "[['Crystal', 'neutral'], ['decor', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["do not take the reservation at 8pm to begin with, if in reality the management knows that it will be impossible to seat at that time."], "output": "[['reservation', 'neutral'], ['management', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The drinks are cute as is concept--unfortunately, the service is not and neither is the wait."], "output": "[['drinks', 'positive'], ['service', 'negative'], ['wait', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There are only 8-10 tables, so you receive a lot of attention from the waiters, which is good."], "output": "[['tables', 'neutral'], ['waiters', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food could be better, the ambience is loud and unwelcoming during lunch, and the service is not only inattentive but also disgusting."], "output": "[['food', 'negative'], ['ambience', 'negative'], ['lunch', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service was nice, although our food took longer than usual to arrive because it had been brought to the wrong table and accidently eaten."], "output": "[['service', 'positive'], ['food', 'negative'], ['table', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene This stylish, golden-hued noodle house spiffs up a dull stretch of Sixth Avenue with a crowd ranging from Japanese visitors to NYU students taking advantage of full-flavored, sustaining soups at bargain prices."], "output": "[['Scene', 'neutral'], ['crowd', 'neutral'], ['soups', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["i ate here with a friend by default-- we were in the meatpacking district on a saturday night, every place in the area was pretty much booked, we were hungry, i only drink sake, and he was treating :)."], "output": "[['area', 'negative'], ['drink sake', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food The best homestyle Italian cooking and service (Menu?"], "output": "[['Food', 'neutral'], ['homestyle Italian cooking', 'positive'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["As for the food, it is way too rich/greasy, whether it was the calamari or grilled chicken."], "output": "[['food', 'negative'], ['grilled chicken', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My party did not love the meats on the menu maybe the pork dumplings but nothing else."], "output": "[['menu', 'neutral'], ['pork dumplings', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service was really bad at several points our waiter would just leave for a cigarette for like 10 minutes while we waited for him to get us another drink or even pay the bill."], "output": "[['service', 'negative'], ['waiter', 'negative'], ['drink', 'neutral'], ['bill', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Tiny slices of pie with a dribble of cream topped off the evening."], "output": "[['slices', 'negative'], ['pie', 'neutral'], ['cream', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Best plan is to order more appetizers and get one sushi platter."], "output": "[['appetizers', 'positive'], ['sushi platter', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food and drinks held up to eatery's rep and the service was just as good if not better."], "output": "[['drinks', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter was a bit weird as well, but the lounge area looked like a nice place to get a drink after work."], "output": "[['waiter', 'negative'], ['lounge area', 'positive'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Yuckity Yuck Yuck  The Burritos were horrible but the Sangria was decent."], "output": "[['Yuckity', 'negative'], ['Sangria', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This is the only place that has great cheesecake in the Tri State area and they are famous for it."], "output": "[['cheesecake', 'positive'], ['area', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The bar area got a little too crowded but the ambiance was great."], "output": "[['bar area', 'negative'], ['ambiance', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Extensive menu plenty of dishes to choose from my dinner was so-so but my BF entree was delicious."], "output": "[['menu', 'positive'], ['dishes', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Had a late-night dinner there on Friday, and while the decor is fabulous, we waited a long time for our check."], "output": "[['late-night dinner', 'neutral'], ['decor', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After being seated the waiter was prompt with coffee and taking my order."], "output": "[['waiter', 'positive'], ['coffee', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Upon reading the $44 prix fixe menu (a fair price for good food), we realized half of the Appetizers and Entrees required an additional supplement ranging from five dollars to $105!"], "output": "[['prix fixe menu', 'neutral'], ['price', 'positive'], ['food', 'positive'], ['Appetizers', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The drinks were really good- albeit a bit weird served out of baby bottles."], "output": "[['drinks', 'positive'], ['served', 'neutral'], ['baby bottles', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you are under 24 this might seem to be a great place in the big city but for the rest of us it's just a liitle too chheesy and the food is under par for the price."], "output": "[['food', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["i had the smallest martini, which the waiter spilled part of."], "output": "[['smallest martini', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food The Korean dishes here are a bit more delicate than the potent fare found 30 blocks north, but the kitchen is hardly pulling its punches."], "output": "[['Food', 'positive'], ['kitchen', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although the food was good, it wasn't quite worth the price tag."], "output": "[['food', 'positive'], ['tag', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Simple Italian fare, with an emphasis on familiar pastas, include My Father's Style Rigatoni, served with thick slices of sausage and veal meatballs."], "output": "[['slices of sausage', 'positive'], ['veal meatballs', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had a reservation for a Staurday night and after a 1 hour and 45 minute wait, we still were not seated!!"], "output": "[['reservation', 'neutral'], ['wait', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Oh, but on a brighter note, when the waiter poured water into my vodka glass by mistake, we got a free drink out of it."], "output": "[['waiter', 'negative'], ['vodka glass', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Don't expect to be filled up by one small dish, you should order a few, or a combination, if you are eating dinner."], "output": "[['dish', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We sat in the garden out back, and the calm atmosphere with the waterfall rock wall on the side completed the setting."], "output": "[['garden', 'neutral'], ['atmosphere', 'positive'], ['setting', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Based on the menu prices, the value of the buffet is made up before you even hit the buffet with the appetizers that are served to the table."], "output": "[['value', 'positive'], ['appetizers', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The small shrimp were dry and rubbery and when I sent the dish back to the kitchen, the waitress returned saying that they use 'frozen shrimp so that is wny they have that texture."], "output": "[['small shrimp', 'negative'], ['dish', 'neutral'], ['kitchen', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitress had zero knowledge about wine, and even knowledge about the dishes they were serving."], "output": "[['waitress', 'negative'], ['wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Every course was delicious, including the multiple chef samples, brought to you from the chef throughout your entire meal."], "output": "[['course', 'positive'], ['multiple chef', 'neutral'], ['meal', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It took a long time for the waiter to bring the check and we had to flag him down."], "output": "[['waiter', 'negative'], ['check', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene The main dining room of this boisterous Carnegie Hall restaurant, dubbed the New York Room, is a cavernous space with high ceilings and sweeping glass windows."], "output": "[['Scene', 'neutral'], ['main dining room', 'neutral'], ['New York Room', 'neutral'], ['space', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While the hostess claimed to have lost my reservation, we were there early enough to only have to wait about 10 minutes to seat our party of seven."], "output": "[['hostess', 'negative'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Be warned - between the pizza and spumoni the place is packed nightly in the summer."], "output": "[['pizza', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They ran out of the drinks my friends ordered, but the staff was eager-to-please and much appreciated."], "output": "[['drinks', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Lastly, after spending a little over an hour and most of that time waiting for our food to arrive the manager barked at us to leave to make room for another party that had been waiting for 25 minutes!"], "output": "[['manager', 'negative'], ['room', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["same atmosphere but food was better before years ago- octopus was like chewing a rubber tire- dumplings tasted artificial."], "output": "[['atmosphere', 'positive'], ['dumplings', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have tolerated the fact that the place is packed on weekends, pricey and not that great drinks, often poor music on Saturdays, and bottle service that is slowly turning into a must."], "output": "[['place', 'neutral'], ['drinks', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The meal was improperly served."], "output": "[['meal', 'neutral'], ['served', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Beer selection is a bit slim, but seats are plentiful and there are several sports monitors placed about the bar."], "output": "[['Beer selection', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although the atmosphere was lacking, I could definitely recommend a trip to Esca for the fish alone!"], "output": "[['atmosphere', 'negative'], ['fish', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter was knowledgable about the menu and spirits, and guided me to all the right items to order given my budget and occasion."], "output": "[['waiter', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["On the night I went to Yakiniku Juju, my plate came first wet, then streaked with grease; the waitress brought the wrong beer, smeared the grill with pork fat despite our having indicated that some in our party were on a kosher diet, and the music was recycled three times."], "output": "[['waitress', 'negative'], ['beer', 'negative'], ['grill with pork', 'neutral'], ['music', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The space is a bit cramped and the waitress seemed to avoid eye contact at all costs, however, I would recommend you go just for the food."], "output": "[['space', 'negative'], ['waitress', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["From the goat cheese and caperberry dish to hangar steak to pancottas, the food was amazing!"], "output": "[['goat cheese', 'neutral'], ['dish', 'positive'], ['steak', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Chances are the garden out back is hopping, with happy Slopers sipping wines that start less than $20 per bottle and munching on more than a dozen kinds of pressed sandwiches."], "output": "[['Slopers sipping wines', 'positive'], ['bottle', 'neutral'], ['sandwiches', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitress only stopped at our table to take our order and pick up the check."], "output": "[['waitress', 'negative'], ['table', 'neutral'], ['check', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Two people having a multi-course dinner in Midtown Manhattan involving excellent food and it all came in under $50!!!"], "output": "[['multi-course dinner', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["At this level, I want my servers to know more than me about the food and I didn't get that sense."], "output": "[['servers', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter comes over and says You changed the salad and made us throw it out!"], "output": "[['waiter', 'positive'], ['salad', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["my table of four was not totaly neglected, but there was a lag in how promptly we were being served."], "output": "[['table', 'negative'], ['served', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Warming clam miso soup and expertly rolled Mexican maki (made with yellowtail, scallions, avocado, and jalapeno mayonnaise) pair well with a stiff glass of shochu, Japanese liquor with a bite as strong as tequila."], "output": "[['clam miso soup', 'positive'], ['scallions', 'neutral'], ['avocado', 'neutral'], ['and jalapeno mayonnaise', 'neutral'], ['glass', 'neutral'], ['shochu', 'neutral'], ['tequila', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu is limited but good with rice paper rolls being a house specialty."], "output": "[['menu', 'negative'], ['rice', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They weren't exagerating when they called it Baku Palace, because the place is huge, having the potential to accomodate weddings, bar mitzvas or any other large parties while still serving other guests who prefer to dine outside the main room."], "output": "[['place', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Other reviews complain about portions, it's a TASTING menu not a Time's Square buffet."], "output": "[['portions', 'negative'], ['buffet', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My dinner partner loved some dishes even when they were too hot for her taste."], "output": "[['dinner', 'neutral'], ['dishes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We actually gave 10% tip (which we have never done despite mediocre food and service), because we felt totally ripped off."], "output": "[['tip', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While the food was good, service tried way too hard."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Every item on the menu tasted like it had been lovingly perfected- from the pulled pork sandwich on white roll to the smokey baked beans, buttery mac-n-cheese, and slightly spicey coleslaw."], "output": "[['menu', 'neutral'], ['smokey baked beans', 'neutral'], ['coleslaw', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I was thinking I am gonna have a nice dinner in that place that a friend of mine recommended to me , but beside the expensive prices that it has was nothing more."], "output": "[['dinner', 'positive'], ['prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had to ask for bread after 45 minutes and even though our waiter was GREAT, he had to ask the stiff manager to comp us a round of drinks for waiting so long."], "output": "[['waiter', 'positive'], ['manager', 'negative'], ['drinks', 'neutral'], ['waiting', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It's got funky, fun furniture and a round bar at the front, which is convenient for those waiting to be seated and be prepared to wait for a while, if you don't have reservations."], "output": "[['furniture', 'positive'], ['reservations', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the new look for hill diner is amaizing and the food is just getting better and better i had a blast of a brunch."], "output": "[['diner', 'positive'], ['food', 'positive'], ['brunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The bartendars are very friendly and at service with you."], "output": "[['bartendars', 'positive'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I do not understand how this place can stay in business with its prices and quality of food."], "output": "[['quality', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My steak looked worse than the grizzle and fat John Candy had to finish in the Great Outdoors and the service, while friendly, was incredibly slow even though we were one of only 4 other tables."], "output": "[['steak', 'negative'], ['grizzle', 'negative'], ['Outdoors', 'positive'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Great place for dinner or late night for a few drinks and something to eat, the kitchen will be open till 3am."], "output": "[['place', 'positive'], ['dinner', 'neutral'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The notable array of refreshing drinks includes raspberry lemonade, an assortment of smoothies and iced teas, and a black cow ice-cream float."], "output": "[['drinks includes raspberry lemonade', 'positive'], ['assortment of smoothies', 'neutral'], ['iced teas', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["yes Shrimp not lobster (those are 6 Lbs) try the exotic Fish not on the menu and a must have is the Flower stuffed with lump crab meat."], "output": "[['Shrimp', 'neutral'], ['lobster', 'neutral'], ['exotic Fish', 'positive'], ['menu', 'neutral'], ['Flower stuffed', 'positive'], ['lump crab meat', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Went back for lunch and had great Chicken Fajitas."], "output": "[['lunch', 'neutral'], ['Chicken Fajitas', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Got club soda, filled with ice, no lime."], "output": "[['club soda, filled with ice', 'neutral'], ['lime', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The seating for dinner is uncomfortable, too close to the bar which gets really crowded since it is so small."], "output": "[['seating for dinner', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The sushi was delicious and fresh and they didn't short you on the pieces of fish either."], "output": "[['sushi', 'positive'], ['fish', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Also the Ka-Choori appetizer (vegetarian goodness) and the Chicken Makhni (Indian for Butter Chicken, American for FATTENING AS HECK) is delish."], "output": "[['Chicken Makhni', 'positive'], ['Indian for Butter Chicken', 'neutral'], ['Ka-Choori appetizer', 'neutral'], ['vegetarian', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Upon explaining, the waiter confronted us as we left and spewed a stream of profanities at us as we walked out the door."], "output": "[['waiter', 'negative'], ['door', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The candle-lit bar is the destination of trendy wine-sippers and snackers, and the rustic-chic dining room, with brick arches that open onto a tight sidewalk terrazza, is booked weeks in advance."], "output": "[['candle-lit bar', 'positive'], ['rustic-chic dining room', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Took my girlfriend here for dinner on a friday night, we were seated promptly and the service continued to be good for the remainder of the evening."], "output": "[['dinner', 'neutral'], ['seated', 'positive'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It took the waiter over a 1/2 hour to come over to tell us the specials."], "output": "[['waiter', 'negative'], ['specials', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our food took so long to be served that we nearly missed our curtain."], "output": "[['food', 'neutral'], ['served', 'negative'], ['curtain', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["You can only sit on the stools with a slice, as the main dining area downstairs is for real food."], "output": "[['main dining area', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food - mostly steak and fish - is decent, but the portions are obscene - filet mignon and salmon were HUGE, but they don't come with any side dishes - you have to order and pay extra for them which is inconvenient and expensive."], "output": "[['Food', 'positive'], ['portions', 'negative'], ['filet mignon', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you can get service, you might enjoy the surroundings- especially the upstairs lounge."], "output": "[['service', 'neutral'], ['lounge', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I would say it's suitable for a romantic date or quiet family meal, as there is no bar so the atmosphere is a little quiet."], "output": "[['family meal', 'positive'], ['bar', 'neutral'], ['atmosphere', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I've ben waiting to try Al Di La for a while, but the menu just never grabbed me."], "output": "[['waiting', 'neutral'], ['menu', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is so good that there tends to be a little bit of a wait."], "output": "[['food', 'positive'], ['wait', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food Though much of the menu draws from border countries with the likes of pasta, cordon bleu and schnitzel, dishes that involve cheese are best."], "output": "[['Food', 'neutral'], ['menu', 'neutral'], ['pasta', 'positive'], ['dishes', 'positive'], ['cheese', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Don't ask for menu,steak is what you will have,along with great creamed spinach."], "output": "[['steak', 'neutral'], ['spinach', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The staff treated me as if I were a celebrity, which I am not and they did not make me feel uncomfortable as a single diner."], "output": "[['staff', 'negative'], ['diner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Salads vary, but dinner specials (standard diner fare) are usually more than adequate."], "output": "[['Salads', 'negative'], ['dinner specials', 'positive'], ['diner fare', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had read good reviews about the value and food quality at this restaurant, so I was not surprised to see a decently priced menu (pasta under $10 and entrees approx $12 to $15)."], "output": "[['value', 'neutral'], ['food quality', 'neutral'], ['priced menu', 'positive'], ['entrees', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere was a little less than inviting as the tables are close together and I could hear the brother/sister couple next to us arguing (although this did provide entertainment for the evening)."], "output": "[['atmosphere', 'negative'], ['tables', 'negative'], ['entertainment', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The sauce was fresh, sweet, and had a bit of a garlic kick."], "output": "[['sauce', 'positive'], ['garlic kick', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Then, when we ordered from a regular menu, and told the waiter, that we are in a hurry to make the show, his response was So what do you want me to do ?"], "output": "[['menu', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We saw the waitress twice - once to tell us the night's specials and once to take our order."], "output": "[['waitress', 'negative'], ['specials', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene Opened in 1993, Nick's may be the only great pizza place in the city of New York that isn't older than most of the people who eat there."], "output": "[['Scene', 'neutral'], ['pizza', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Weekday lunch is less crowded and the staff cheerfully tolerated a 3-year-old."], "output": "[['Weekday lunch', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Being a basil fanitac, the fresh leaves that come on the pizza pie I ordered were a delight."], "output": "[['basil', 'neutral'], ['pizza', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Then I ordered a margarita,rocks w/ salt, the waitress' replied:I don't think we have salt What do you cook your food with?"], "output": "[['waitress', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["But when the bartender messes up the returned drinks something is wrong."], "output": "[['bartender', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were left waiting a while after our food for our waiter to return, and thus we did not have time for dessert."], "output": "[['food', 'neutral'], ['waiter', 'negative'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitress had the gall to ask us to close out our check when she brought our food so she could go home rather than wait for us to finish (hey babe we waited for YOU, you can wait for US)."], "output": "[['waitress', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["So we all did the buffet--one of my companions liked the lamb very much."], "output": "[['buffet', 'neutral'], ['lamb', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["And when a waiter, in answer to a question by a diner, turns to another table and asks excuse me, do you know what this is?"], "output": "[['waiter', 'negative'], ['diner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I am vegetarian - so this review applies only to the veg portion of their menu."], "output": "[['portion', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["She's watching your table, helping the staff candy to your eyes."], "output": "[['table', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I came to celebrate finishing my third year of med school and was greatly disappointed by the way I was treated at the door (rude and terse), the food (mediocre), and the ambiance (very loud, crowded, and uncomfortable close to our neighbors despite the large room)."], "output": "[['food', 'negative'], ['ambiance', 'negative'], ['room', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Each dish is carefully prepared and is a tribute to the ingredients being served."], "output": "[['dish', 'positive'], ['ingredients', 'neutral'], ['served', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This place overall is a bad dining experience, its a tourist trap, save your money and go somewhere that you can actually taste the food."], "output": "[['dining', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["it's a joy to watch the chef work, who refused to take my order but seeing him open my live scallop made me understand why."], "output": "[['chef', 'positive'], ['live scallop', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We ended up having appetizers in the lounge, while listening to a really great DJ."], "output": "[['lounge', 'neutral'], ['DJ', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The server also forgot about our dessert."], "output": "[['server', 'negative'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When asked to explain the hostess told us she would lose money by seating us instead of them."], "output": "[['hostess', 'negative'], ['seating', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I waited 15 minutes for the waiter to take the bill from me and finally I got fed up with him walking past our table I had to start waving the bill in the air and finally some other waitress took our bill."], "output": "[['waiter', 'negative'], ['air', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Cheap pitchers of beer, cheap food that just stopped kicking minutes before going on your plate, lots of burgers, ribs, sandwiches."], "output": "[['beer', 'positive'], ['food', 'positive'], ['burgers', 'neutral'], ['ribs', 'neutral'], ['sandwiches', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the food sounded good enough on paper, with lots of clever names and interesting choices, but once we bit in, the dishes were all pretty bland."], "output": "[['food', 'negative'], ['choices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I could not believe how much food they brought out to the table!"], "output": "[['food', 'positive'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Even though the place was more than half empty he refused to do so because we had already given our order to the waiter and a change of tables would cause too much confusion."], "output": "[['place', 'negative'], ['waiter', 'neutral'], ['change', 'negative'], ['tables', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene Flanked by a diner-style bar on one side and glass cases of sweets on the other, General Store resembles a cozy mom-and-pop rest stop on the way through Pennsylvania Dutch country--minus the cheesy gift shop."], "output": "[['Scene', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The bartender ignored us for 10 minutes before asking what we'd like to drink although we were the only people waiting for a table when we walked in."], "output": "[['bartender', 'negative'], ['drink', 'neutral'], ['waiting', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The lunch specials are reasonably priced, but I avoid this place when I can only order off the regular menu."], "output": "[['lunch specials', 'neutral'], ['priced', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There were about 4 tables filled in the entire restaurant yet the hostess made us sit at the bar for 20 mins--she never would have come for us had we not approached her asked to be seated."], "output": "[['hostess', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["(having asked for bread at this point 3 times and still with out) He dashed off before we even finished the drink order!"], "output": "[['bread', 'negative'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the kimchi and other sides were off, the rice had red bean mixed in, and the waitress gave us a double order of the bulgogi instead of two single orders of different meats."], "output": "[['rice', 'neutral'], ['waitress', 'negative'], ['meats', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There is a nice bar (weve had a drink there a couple of times as a break from SoHo shopping and the cheese sticks are an additional attraction) and the dining area is light and airy with an open kitchen."], "output": "[['bar', 'positive'], ['cheese sticks', 'positive'], ['dining area', 'positive'], ['kitchen', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I've been here several times for Sunday brunch now - (note: it helps if you're a late riser as I find the wait is always reasonable if you show up after 3pm)."], "output": "[['brunch', 'neutral'], ['wait', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I recently went to this restaurant with some co-workers for lunch and had an amazing time."], "output": "[['lunch', 'neutral'], ['time', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They didn't have any salad and the waiter didn't tell us this very smoothly."], "output": "[['salad', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We waited over 30 minutes to get our drinks (which were brought over my the manager) and we could not find anyhting that looked interesting on the menu."], "output": "[['drinks', 'neutral'], ['manager', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It was more than enough food and drink for everyone, and at $20 per person, including tax and tip, the prices cannot be beat!"], "output": "[['tip', 'neutral'], ['prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It was very loud, I felt too crowded, the man chair's next to me made it impossible for the waiters to pass."], "output": "[['man chair', 'neutral'], ['waiters', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere is perfect, whether sitting down for dinner or just having a drink at the bar and engaging the friendly bartenders in converasation."], "output": "[['atmosphere', 'positive'], ['dinner', 'neutral'], ['bartenders', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A narrow corridor leads to a tiny space where there are three tiny white tiled counters, a great deal of mess (stacks of bottles, cans) and a small counter holding 12-14 entrees."], "output": "[['corridor', 'negative'], ['counters', 'negative'], ['entrees', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I discovered recent new management has made major improvements at this location ie the bar, dining areas, party room and bathrooms and keeping the kitchen open after 11PM."], "output": "[['management', 'positive'], ['bar', 'neutral'], ['dining areas', 'neutral'], ['kitchen', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is decent at best, and the ambience, well, it's a matter of opinion, some may consider it to be a sweet thing, I thought it was just annoying."], "output": "[['food', 'positive'], ['ambience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In addition, I've always found the waiters helpful with the wine selection, and there is always a good selection of wines by the glass."], "output": "[['waiters', 'positive'], ['wine selection', 'neutral'], ['wines', 'positive'], ['the glass', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Two Tom's food is excellent, it more than makes up for the lack of decor."], "output": "[[\"Tom's food\", 'positive'], ['decor', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["To avoid the crowds, go during lunch, when the menu is augmented with warm sandwiches, entree-sized salads and country omelettes."], "output": "[['sandwiches', 'positive'], ['salads', 'neutral'], ['omelettes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I don't care for the entrees, but the chicken dumpling soup is delicious!"], "output": "[['entrees', 'neutral'], ['chicken dumpling soup', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Bliss Bowl--a large portion of brown rice, beans, kale, carrots, broccoli, cauliflower, tofu, seaweed and tahini--is the specialty of the house."], "output": "[['portion of brown rice', 'positive'], ['beans', 'neutral'], ['kale', 'neutral'], ['carrots', 'neutral'], ['seaweed', 'neutral'], ['tahini', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While the food isn't out of this world, it offers a decent meal at a decent price."], "output": "[['food', 'negative'], ['meal', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is decent, but WAY TOO SMALL of portions for what you pay for."], "output": "[['food', 'positive'], ['portions', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went to the Hudson bar with my boyfriend and the guy at the front door was extremely rude."], "output": "[['Hudson bar', 'neutral'], ['guy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The MooShu spring rolls were tasty, steamed dumplings alright."], "output": "[['MooShu spring rolls', 'positive'], ['steamed dumplings alright', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Those appetizers only appeared after we complained to the manager."], "output": "[['appetizers', 'neutral'], ['manager', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The place is not fancy, but their food is wonderful."], "output": "[['place', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["we told the waitress and she told us that we ordered the dead fish as opposed to the swimming fish."], "output": "[['waitress', 'negative'], ['dead fish', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We waited for thirty minutes for our table, and after inquiring once about the status, we were rudely confronted by the hostess."], "output": "[['table', 'neutral'], ['hostess', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Without another word when we arrived, they added a chocolate decoration saying Happy Anniversary to our desserts."], "output": "[['chocolate decoration', 'positive'], ['desserts', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The kitchen also offers just a few sushi-free entree options, such as a masterful tempura dinner and chicken or salmon teriyaki."], "output": "[['entree options', 'positive'], ['chicken', 'neutral'], ['salmon teriyaki', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had 3 bottles of champagne waiting on the table, the waitress was very helpful, all 15 guests were very pleased and we couldn't have asked for a better night dining outside in the lovely garden."], "output": "[['champagne', 'neutral'], ['waitress', 'positive'], ['dining', 'positive'], ['garden', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Great place for a first date or dinner with a picky group."], "output": "[['place', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["All-night restaurant with excellent burgers and stella on tap."], "output": "[['burgers', 'positive'], ['tap', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The overpriced ice cream is delicious but the service is atrocious - not only do I have to wait to be admitted into this ice cream joint, but the waiter is a snide, gruff man more suited to be a trucker than an ice cream shop server."], "output": "[['service', 'negative'], ['cream joint', 'neutral'], ['cream shop server', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Not only did it take them 45 minutes to serve a salad, when we complained, the manager was abusive, told us to get out and literally started clearing the table while we were still eating."], "output": "[['salad', 'neutral'], ['manager', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When my group complained to our waiter about a cake cutting fee that involved no cutting, the manager came over to the table and basically told us that it was our fault for not knowing that their policy was just to serve the plates, not to cut."], "output": "[['waiter', 'negative'], ['cake', 'neutral'], ['manager', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The place is hip and the decorations funky, but the food is lacking."], "output": "[['place', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Recently I purchased a dish to go, and found that all of my meal contained just one large piece of ginger root."], "output": "[['dish', 'neutral'], ['ginger root', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When questioning our server about a certain dish, she kindly brought over the Union Sq."], "output": "[['server', 'positive'], ['dish', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food and Service of the same high quality elsewhere in NY would have been twice the cost."], "output": "[['Food', 'positive'], ['cost', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["On my first visit, I asked the waiter to please wrap my leftovers and was refused adamantly (he told he wasn't allowed to package the low-priced food)."], "output": "[['waiter', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They overfill the reservation sheet so that the check is dropped off nearly with your food and they are rushing you out of your booth before you are finished."], "output": "[['reservation', 'neutral'], ['food', 'neutral'], ['booth', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although we arrived at the restaurant 10 min late, the hostess did not have a table for us."], "output": "[['hostess', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter took his time taking our drink orders ('97 Italian red was good)."], "output": "[['waiter', 'positive'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is OK but I have to ask WHY they serve noodles with steak???"], "output": "[['food', 'positive'], ['noodles with steak', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The inattentive waiters never refilled our water glasses, never offered more drinks, our silverware was never replaced, and it took almost half an hour at times for them to clear our table after we finished a course."], "output": "[['waiters', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Aside from the Sea Urchin, the chef recommended an assortment of fish including Fatty Yellow Tail, Boton Shrimp, Blue Fin Torro (Fatty Tuna), Sea Eel, etc."], "output": "[['chef', 'positive'], ['Boton Shrimp', 'neutral'], ['Sea Eel', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Be sure to taste the incredible assortment of vegetable and seafood spring and summer rolls."], "output": "[['assortment of vegetable', 'positive'], ['seafood spring', 'positive'], ['rolls', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Waiters were pretty slow, didnt refill my glass of water until I was about to leave, and I had to ask several times to get the check and the slices of lemon."], "output": "[['Waiters', 'negative'], ['glass of water', 'neutral'], ['check', 'neutral'], ['slices of lemon', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I though the service could have been better, the staff are not experience enough to know how to make the drinks without reading the instructions."], "output": "[['service', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It took about ten minutes to get out drink ordering after sitting down and once we recieved the bottle our waitress never once refilled our glasses!"], "output": "[['bottle', 'neutral'], ['waitress', 'negative'], ['glasses', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our meal was capped of with the waiter rudely saying he needed the table for other customers."], "output": "[['meal', 'neutral'], ['waiter', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When the ice cream cake I ordered didnt hold up in their regular freezers temperature, Giovanny immediately had a server run out and got an identical cake in 15 minutes."], "output": "[['temperature', 'neutral'], ['server', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["not fancy I think they keep their christmas decorations up all year long, but good mexican food!!"], "output": "[['christmas', 'negative'], ['mexican food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was definitely good, but when all was said and done, I just couldn't justify it for the price (including 2 drinks, $100/person)."], "output": "[['price', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I love the complimentary hot salsa and fresh chips that they put on the table !"], "output": "[['hot salsa', 'positive'], ['chips', 'positive'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["With the exception of one late day when I came in for caffe and the waitress nearly rushed us out since dinner was coming around."], "output": "[['waitress', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Needless to say, we weren't suprised when our server told us he never put our appetizer order in."], "output": "[['server', 'negative'], ['appetizer', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I recommend using your bread and sopping up the sauce."], "output": "[['bread', 'positive'], ['sauce', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Noise level is high, and if you are a non smoker ask to be seated away from the bar."], "output": "[['Noise', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is nice, but then its pretty hard to screw up Myers sausages, mashed potatoes and tinned beans isn't it ?"], "output": "[['food', 'positive'], ['tinned beans', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The point of dining here is to get several Tasting plates (two of us shared 5 @ $12/each and were quite full), and try as many of the dishes on the menu as possible."], "output": "[['point', 'neutral'], ['dining', 'neutral'], ['plates', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After making our party wait for about an hour past our reservation time (which we chalked up to it being a busy Friday night), they gave us a wobbly makeshift table that was set up in the path of the staff rushing out of the kitchen."], "output": "[['reservation time', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the staff knows the regulars by name and the sushi chef even yells goodbye from behind the bar."], "output": "[['staff', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Usually you lose food quality the trendier you go, but not at this place."], "output": "[['food quality', 'negative'], ['trendier', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["small price to pay to have dinner on a Saturday night in downtown Manhattan."], "output": "[['price', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Their main chef Louie, makes the oddest specials you will ever see and the portions are quite large."], "output": "[['main chef', 'neutral'], ['portions', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The space is cool, but the food and service were awful."], "output": "[['space', 'positive'], ['food', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the water guy was extremely attentive, thank god he was because we had to ask him for our waitress many times: for ordering our food, more drinks, dessert and check."], "output": "[['water guy', 'positive'], ['waitress', 'neutral'], ['food', 'neutral'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They charge $24 for entrees and ask additional price of $3 for rice or $6 for vegetables as side dish!"], "output": "[['entrees', 'neutral'], ['price', 'negative'], ['vegetables', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had hot buffalo tenders for an appetizer, and the waitress didn't bother to come back to check on how we were doing on drinks."], "output": "[['buffalo', 'neutral'], ['appetizer', 'neutral'], ['waitress', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My one complaint: Even though we arrived at our reservation time, the host asked us to wait at the bar -- then forgot to seat us (I had to ask)."], "output": "[['reservation', 'neutral'], ['host', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After fifteen minutes, when nobody even took our drink order, I looked around to try to get our waitresses attention only to see she and about five others of the waitstaff were having an endless gabfest by the register."], "output": "[['drink', 'neutral'], ['waitresses', 'negative'], ['waitstaff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They seem to put the sauce over the mozzarella which allows the sauce to be the primary taste."], "output": "[['sauce over the mozzarella', 'neutral'], ['taste', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The staff was knowledgeable about the cuisine and answered my dining questions with professionalism and style."], "output": "[['staff', 'positive'], ['cuisine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Seconds after we permitted our half-eaten fattened goose livers to be whisked away, our waitress materialized, bearing two cold drinks and the chef's profound apologies for the dish - a completely unneccessary but vastly appreciated gesture."], "output": "[['waitress', 'negative'], ['drinks', 'neutral'], ['gesture', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Waiter brought white instead of red wine."], "output": "[['Waiter', 'negative'], ['red wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene This storefront eatery is decked with colorful Mexican art and party kitsch, but it gets dim and moody enough in the evenings to suit a date."], "output": "[['Scene', 'neutral'], ['Mexican art', 'positive'], ['dim', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["out of the handrolls, the yuka (salmon, salmon roe, and cucumber) the crispy salmon skin were especially good."], "output": "[['yuka', 'positive'], ['salmon roe, and cucumber', 'neutral'], ['crispy salmon skin', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food at Forest Hills was great, the service more than perfect, but but the ambience was too hot they do not have AC and the employes was sweating a lot , it was a nasty esxperience because I eat in front of the service that was sweating like animals."], "output": "[['food', 'positive'], ['ambience', 'negative'], ['employes', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They were playing top 40 music the day I went which just didn't work with the whole theme, but they had the trippy sci-fi music playing in the bathroom, so it was almost right."], "output": "[['sci-fi music', 'negative'], ['bathroom', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is pretty good, and so is the service, though on my first visit I told the waitress I wanted my tuna black-and-blue and she had no idea what that was."], "output": "[['food', 'positive'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["However, after speaking with the manager on the phone for about 15 minutes, the waitress said they couldn't give us any discount but would gladly give us a free pitcher of sangria."], "output": "[['manager', 'negative'], ['waitress', 'negative'], ['sangria', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The deserts are horrid, but the drinks are always good."], "output": "[['deserts', 'negative'], ['drinks', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Evening service--featuring waiters all in black--is a little slow; plan on a leisurely dinner unless you're headed for the theater."], "output": "[['service', 'neutral'], ['waiters', 'negative'], ['leisurely dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Took the waiter 10 minutes to get to our table, and another 15 minutes until the coffee I ordered arrived."], "output": "[['waiter', 'negative'], ['table', 'neutral'], ['coffee', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter made no effort to remember who had orderd what (just threw it on the table and bailed), or even who ordered (I had to flag him so my wife could order her main dish 15 min after he had taken orders from others)."], "output": "[['waiter', 'negative'], ['dish', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Plus, the food was way over priced (even for Manhattan) and while it was decent in taste, nothing made up for the outlandish prices."], "output": "[['food', 'negative'], ['taste', 'positive'], ['prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["a friend was taking me to dinner for my birthday and said he recalled this place around 96th bway that had great chicken."], "output": "[['dinner', 'neutral'], ['chicken', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["At one point my friend knocked over a glass and broke it to pieces, and the waitstaff was so forgiving of it."], "output": "[['glass', 'neutral'], ['waitstaff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Delicious food, just stay away from the specials of the day!"], "output": "[['food', 'positive'], ['specials', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["And I pretty much had to tell the waiter that when dinner is late, you usually comp your guests something."], "output": "[['waiter', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The spaghetti with ricotta cheese is hands down my favorite thing on the menu and I am big fan of the house wine."], "output": "[['spaghetti with ricotta cheese', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I followed my handsome waiter's suggestions for everything from my cranapple martini, BBQ duck tostada appetizer and rum-glazed pork tenerloin entree to the scandalously good brownie sundae."], "output": "[['waiter', 'positive'], ['martini', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Chicken with Mixed vegetables is an explosion of flavor, many great spicy dishes too."], "output": "[['Mixed vegetables', 'neutral'], ['flavor', 'positive'], ['dishes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It was also very reasonably priced, we had 4 bottles of wine, appetizers, dinner, and coffee and our bill was just over 50 per person."], "output": "[['priced', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Went for dinner last Friday night with 2 friends, and the staff was incredibly nice."], "output": "[['dinner', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The owner and his sister make you feel like you've been invited over to their house for dinner."], "output": "[['owner', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Waiting for a table is par for the course."], "output": "[['Waiting', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you can't tolerate slow service at a pizza place, then spend more money elsewhere."], "output": "[['service', 'negative'], ['pizza', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I finally cancelled our order, the waiter came back in 5 min with our plates."], "output": "[['waiter', 'negative'], ['plates', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["i won't be going back, and i'll tell all my friends not to go--you guys could have the best mussels in the whole world, but that waitress must be keeping a lot of customers away."], "output": "[['mussels', 'positive'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I've never been able to find a lunch place in the midtown with the same quality and service, until now."], "output": "[['lunch', 'neutral'], ['quality', 'positive'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They serve mostly paninis (fancy Italian sandwiches)."], "output": "[['paninis', 'neutral'], ['Italian sandwiches', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There was live music at the bar, which made our wait for a table wonderful (we didn't have reservations)."], "output": "[['music', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["i went on a thurs night and it was a bit loud due to the many businessmen eating their dinner, but the food and service more than outdid the lack of peaceful dining."], "output": "[['dinner', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The mussels and fries at this place were amazing!"], "output": "[['mussels', 'positive'], ['fries', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Ate at the bar and started with an amazing bowl of french onion soup with 3 cheeses (3!)"], "output": "[['bar', 'neutral'], ['bowl of french onion soup with 3 cheeses', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Charming atmosphere that seats probably no moroe than 35."], "output": "[['atmosphere', 'positive'], ['seats', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Once we eventaully got seated (all tables are practically on top of each other), we were hustled through our meal by a waitstaff that clearly knows how quickly they need to turn the table over."], "output": "[['tables', 'neutral'], ['meal', 'neutral'], ['waitstaff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The plum wine at the end of the meal was a nice touch."], "output": "[['plum wine', 'positive'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Once seated the waiter took our drink orders only to return 10 minutes later with the wrong drinks."], "output": "[['waiter', 'negative'], ['drinks', 'negative'], ['drink orders', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The chips and salsa were good, the service was good, but the sangria and margaritas were very weak, the food terrible, and the portions small."], "output": "[['chips and salsa', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I just got back from dinner from this UES hotspot - it is like a home away from home - delicious meals and a salad dressing that sometimes they let me have a tiny container of for my lunch at work salads - the price/ atmosphere/ cocktails (FULL BAR!!!"], "output": "[['meals', 'positive'], ['salad dressing', 'positive'], ['price/ atmosphere/ cocktails', 'positive'], ['BAR', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The pork chops, cubed steak, pho bo and whole fried fish are among my favorites."], "output": "[['pork chops', 'positive'], ['steak', 'neutral'], ['fried fish', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were lucky because chef Gari was there when we visited, and himself prepared the platter for us."], "output": "[['chef', 'positive'], ['platter', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The place was very crowded usually it is a good indication that the food would be worth the delay."], "output": "[['place', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The ombiance may be a bit more like your own loft, but how cool to eat food like home."], "output": "[['ombiance', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The famous cheesecake--for sale in a wide array of flavors and sizes in the front bakery, and for consumption in the sprawling orange-and-wood retro interior--is made fresh daily."], "output": "[['cheesecake', 'positive'], ['array', 'positive'], ['flavors', 'positive'], ['bakery', 'neutral'], ['retro interior', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I order the Jerk Chicken full price off the menu."], "output": "[['price', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I'm no sushi connoisseur, but the food there is so delicious, and such a good value."], "output": "[['sushi', 'negative'], ['food', 'positive'], ['value', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Althought the menu is more expensive than your average Mexican restaurant, it is not more expensive than any other hip, increadibly well designed, bar scene and dining room in Manhattan -could be less in fact."], "output": "[['menu', 'neutral'], ['scene', 'positive'], ['dining room', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Bill for three with 7 plates, glass of sangria each and coffee and one dessert was 45 each with tip - not too bad but a tad overpriced for the serving size of the dishes."], "output": "[['glass of sangria each', 'neutral'], ['coffee', 'neutral'], ['dessert', 'neutral'], ['tip', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter never came by to check on us after the bus boy brought us our food."], "output": "[['waiter', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The pizzas are a MUST TRY, hence the name."], "output": "[['pizzas', 'positive'], ['name', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our experience consistently reflected a lazy attitude by the house towards cooking technique and customer care."], "output": "[['attitude', 'positive'], ['house towards cooking', 'neutral'], ['care', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After hearing all of the specials, you would think they were twice as much as the menu prices (as other places do)."], "output": "[['specials', 'neutral'], ['menu prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service is not very good, but I find that we try Atlantic Grill at least once a year."], "output": "[['service', 'negative'], ['Grill', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["However for one appetizer, three entree's, one shared dessert, and two bottles of white, the bill was a cool $100!"], "output": "[['appetizer', 'neutral'], ['entree', 'neutral'], ['dessert', 'neutral'], ['white', 'neutral'], ['bill', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Faux Models/Waiters hustle around the tight spaced restaurant, while the bar is crowded with waiting patrons and dates enjoying a drink."], "output": "[['bar', 'neutral'], ['waiting patrons', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food and appearance of Alfama is quite nice but the menu is a bit deceptive in that my grilled shrimp (Peri Peri) consisted of an entree plate with three shrimp, no veggies or starch."], "output": "[['food', 'positive'], ['menu', 'negative'], ['entree plate with three shrimp', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["food for fancy prices; menu consisted of one page; antipasto, and pizza; that was pretty much it; the other 3 pages was to my surprize the wine list."], "output": "[['prices', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["nice and cozy place but the soup was cold, the pizza was cold."], "output": "[['place', 'positive'], ['soup', 'negative'], ['pizza', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Music is a nice mix of everything from Aerosmith to James Brown to Metallica to disco to whatever else there is."], "output": "[['Music', 'neutral'], ['mix', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The wait was not very long and the staff was great."], "output": "[['wait', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service was attentive but overdone for the tiny and very ordinary setting and poor food."], "output": "[['service', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["- Seeing the same chef umiliate the waitress (actually the only person in there that really belongs to the restaurant business) in front of the costumers (Man: you are not even man enough to take responsability for your own mistakes and you need a woman to take the fall for you!!!!!!!"], "output": "[['chef', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Fish was clammy, with slight off taste to some(according to my sashimi-eating dinner companion)."], "output": "[['Fish', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["As expected, the beer selection is perfectly in synch with the menu."], "output": "[['beer selection', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I ordered the seafood platter - the shrimp was hard and overdone, as were the mussels."], "output": "[['seafood platter', 'neutral'], ['shrimp', 'negative'], ['mussels', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene  With flickering sconces and rough-hewn brick walls, Crispo may look like an elegantly restored Italian farmhouse, but frenzied servers, tight tables and wait-list hopefuls at the marble bar make it feel like a city-slick hotspot."], "output": "[['Scene', 'neutral'], ['servers', 'negative'], ['tables', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["What does it say about an establishment and its chef when its policy forces the Price Fixed, Chefs Choice Menu on every party six or greater?"], "output": "[['Price', 'negative'], ['Chefs', 'neutral'], ['Menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["), the food portions hearty (I was almost full after my appetizer of warm duck salad), and the quality of food was average to above average."], "output": "[['appetizer', 'neutral'], ['quality of food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This set off our critical eye: ceramic bowls having edges higher than the table votives hid the fact that the food was presented cafeteria-style; a rolling-eyed waiter pushing water; the awkward Italian menue gimmick; and the bill."], "output": "[['table', 'neutral'], ['food', 'negative'], ['waiter', 'negative'], ['bill', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The last two didn't come to the people who ordered them until they already had there food ( in which then we had to remind the staff of)."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["i just wish they wld drop some staff though, sometimes you feel like your being stalked by waiters, waiters helper, waterperson, busperson, food runner, supervisors, managers."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['managers', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had my brand new $15 lip gloss on the table and the waiter threw it away."], "output": "[['table', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter became visibly irritated when we didn't want to order any drinks at the start of the evening."], "output": "[['waiter', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The sausage might as well of been Jimmy Dean or from a Hot Dog stand, the Brisket was on the dry side, the Pulled Pork was decent at best, and the Ribs were a giant boiled chunk of fat."], "output": "[['sausage', 'neutral'], ['Pulled Pork', 'positive'], ['Ribs', 'negative'], ['boiled chunk', 'positive'], ['fat', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Louis), select sides (stay away from the mac and cheese."], "output": "[['sides', 'neutral'], ['mac', 'negative'], ['cheese', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["(They even let us bring our own cake for the event, which many restaurants may not allow you too) They food was good as I only sampled so I can't really comment."], "output": "[['cake', 'neutral'], ['event', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Sam and the staff at Rialto were so accomodating and gave us a dinner event we will always remember."], "output": "[['staff', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The prices were outrageous, but we assumed the quality would be commensurate, so we ordered."], "output": "[['prices', 'negative'], ['quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This was after we told the clueless hostess we only wanted to have drinks, and she seated us at a table."], "output": "[['hostess', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Both of our entrees were cold, and my Lobster and Scallop Ravioli left me wondering where the seafood was."], "output": "[['entrees', 'negative'], ['seafood', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["it's one of the cheapest eats in the city and the food is not bad if you sit at the bar only - they have a decent chicken and/or beef tender tips but they cook with a lot of garlic so beware."], "output": "[['bar', 'neutral'], ['beef tender tips', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu had more selections, price points that fit all our budgets and a new Sushi menu that went over huge with the table."], "output": "[['new Sushi menu', 'positive'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When I was there with a friend the waiter who served us was pretty friendly."], "output": "[['waiter', 'positive'], ['served', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Well, its bar is beginning to attract the high-heeled Forever 21 ladies and hair-gelled men-who-love-them crowd (alas) and yet I must admit-- the food is damn good."], "output": "[['bar', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter did not know the menu, and was very unaccomidating about substutions."], "output": "[['waiter', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food here does a great service to the name (Cantonese that is."], "output": "[['food', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We would have left and gone to another restaurant but the host kept saying that a table was opening up in 5 minutes, people had just paid, etc - except when I went to check the table, they were ordering dessert."], "output": "[['host', 'negative'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My date knew the waiters from years of dining here, so we were treated like royalty."], "output": "[['waiters', 'positive'], ['dining', 'neutral'], ['royalty', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We didn't see the solitary waitress after seating ourself for over 10 minutes."], "output": "[['waitress', 'negative'], ['seating', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I'd recommend going across the street to Recharge for some healthy burgers and fries before hitting the bar."], "output": "[['burgers', 'positive'], ['fries', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["People waiting for tables stand at a drink rail next to large windows which open out over a leafy garden in the summertime."], "output": "[['waiting', 'neutral'], ['drink', 'neutral'], ['windows', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service on our visit was absolutely awful - a waiter and two helpers couldn't get our orders right and ignored several pleas for basics such as water and beverage refills and utensils to eat desserts with."], "output": "[['service', 'negative'], ['waiter', 'negative'], ['water', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When we arrived, our table wasn't ready and we waited 30 minutes in the bar."], "output": "[['table', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had an hour for lunch, and service was impeccable each time."], "output": "[['lunch', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the place was empty and the waiters just hung out at the bar."], "output": "[['place', 'negative'], ['waiters', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After dinner and even a few times during the owner came upto us and asked us how we felt about the place and the food which doesn't happen often in Manhattan."], "output": "[['dinner', 'neutral'], ['owner', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food The charming fireplaces and wooden chairs spell cozy cafe-romantic if you're in love, and comfy if you're not."], "output": "[['Food', 'neutral'], ['fireplaces', 'positive'], ['chairs', 'positive'], ['cafe-romantic', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Besides having Tetley's and Belhaven on tap, the cod and chips are nearly perfect, as are the Fried Mars' bars and Fried Reeses Peanut Butter Cups."], "output": "[['cod and chips', 'positive'], ['Fried Mars', 'neutral'], ['bars', 'positive'], ['Fried Reeses Peanut Butter Cups', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Having dined there over a half-dozen I have tried everything on the menu but depending on what night, time and who is taking your order, be prepared for loud, smokey (it is a bar afterall) and herbed waitstaff."], "output": "[['menu', 'neutral'], ['bar', 'neutral'], ['waitstaff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["i went on a thursday evening and the restaurant was pretty empty the server got our drinks wrong 3 times!"], "output": "[['server', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitress told us the portions were not big, so we each got an entree and shared a side."], "output": "[['waitress', 'neutral'], ['portions', 'negative'], ['entree', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Once just for late night drinks (they have a great drink menu) and then again for dinner."], "output": "[['drink menu', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Fettucine Alfredo was appropriately cheesy and dense but the show stopper was the Linguine with white clam sauce."], "output": "[['Fettucine Alfredo', 'positive'], ['white clam sauce', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["finally, onto dessert, wherebv the waiter told us he would have to scrape the bottom to give us any ice cream."], "output": "[['dessert', 'neutral'], ['waiter', 'negative'], ['cream', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After a short 30 minutes of chatting and enjoying our drinks we were approached by the very pretentious Maitre D' who RUDELY demanded we order as our table was needed."], "output": "[['Maitre', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My husband's steak was prepared incorrectly, and the rest of us were almost done eating by the time they got his meal back out."], "output": "[['steak', 'negative'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The servers are constantly in your face asking if you want another drink (mine was half full)."], "output": "[['servers', 'negative'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The final blow came when the waitress scorned our 16% tip for the meal."], "output": "[['waitress', 'negative'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Seemed like they got something wrong with every drink order Bartenders were def."], "output": "[['drink', 'neutral'], ['Bartenders', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had the salmon dish and while it was fine, for the price paid, I expected it to have some type of flavor."], "output": "[['price', 'neutral'], ['flavor', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The cheese muffins served before the meal and the butter cookies given to us after dinner, were the highlight of our dining experience."], "output": "[['meal', 'neutral'], ['butter cookies', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I've also been amazed at all the new additions in the past few years: A new Jazz Bar, the most fantastic Dining Garden, the Best Thin Crust Pizzas, and now a Lasagna Menu which is to die for (these are not your average lasagnas)!"], "output": "[['new Jazz Bar', 'neutral'], ['Dining Garden', 'positive'], ['Thin Crust Pizzas', 'positive'], ['Lasagna Menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Those less interested in people-watching dine inside the whimsical, wood-trimmed room under a canopy of Italian inscriptions, or at the long, art-lined bar, which hosts a hopping after-work crowd."], "output": "[['room', 'positive'], ['bar', 'neutral'], ['crowd', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I've heard that if you sit at the sushi bar, you can request rolls, but if you're at a table, the rolls are just the fish wrapped in seaweed with rice (which is still good, but I really love creative rolls)."], "output": "[['sushi bar', 'neutral'], ['table', 'neutral'], ['fish', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I haven't had much Argentinian cuisine, but the food there is really good."], "output": "[['Argentinian cuisine', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Crowded waiting area in entrance forced you to sweat out the wait for a table while standing over other diners."], "output": "[['waiting area', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Both appetizers arrived cold/luke-warm, which we had to send back, only to have the waiter tell us that one was supposed to be cold."], "output": "[['appetizers', 'negative'], ['waiter', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I must admit the times my family (6 or more) have had dinner there the service seemed to forget us after serving the main course."], "output": "[['dinner', 'neutral'], ['service', 'negative'], ['serving', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The appetizers are ok, but the service is slow."], "output": "[['appetizers', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The ambience was nice, but service wasn't so great."], "output": "[['ambience', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Having just returned from Bourbon Street, I thought I had experienced the steepest drink prices in the US, but this is worse than N'awlins, where at least the expensive drinks cover wonderful live music."], "output": "[['steepest drink prices', 'neutral'], ['music', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Don't go if you want a serene environment to go with your sushi."], "output": "[['environment', 'positive'], ['sushi', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had the Steamed Mussels and Clams and the sauce was to die for."], "output": "[['Steamed Mussels and Clams and', 'neutral'], ['sauce', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you're looking a spicy vindaloo or a tikka masala head to a curry house instead."], "output": "[['vindaloo', 'positive'], ['tikka masala', 'positive'], ['curry', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["servings are plentiful and evey dish is delicious (except for the lemon potatoes)."], "output": "[['servings', 'positive'], ['dish', 'positive'], ['lemon potatoes', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Plenty of tables avail for no reservation in bar areain case you want to go on an expensive date for not so great food."], "output": "[['tables', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They also have Korean BBQ and very beer-friendly Korean appetizer(like KimChee)."], "output": "[['Korean BBQ', 'neutral'], ['Korean appetizer', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene Every time another loud, bouncy Mexican tune kicks in on the corner jukebox, you'd swear this small diner is on the brink of a full-on fiesta."], "output": "[['Scene', 'negative'], ['jukebox', 'neutral'], ['diner', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When we got there, they refused to seat us because our 4th wasn't there yet-even thought there were only two other people there and we assured them we would order some starters and drinks."], "output": "[['seat', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["drink, share your delicious entree's and then head to the bar to mingle."], "output": "[['drink', 'neutral'], ['entree', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There are few tables; most likely, you'll be seated at the bar or on a stool facing the wall."], "output": "[['tables', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["During the day, the sushi bar can be backed up a bit (thanks to their unbeatable lunch specials) so order early."], "output": "[['sushi bar', 'neutral'], ['lunch specials', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you mind waiting for your pie to be made (the wait canbe over an hour, especially for a square pie), I recommend calling ahead and placing your order for pick-up."], "output": "[['waiting', 'negative'], ['square', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Perhaps I chose the wrong place, not fully appreciating that another reviewer's remark that diners here won't be rushed could translate to my timely-arrived party having to wait 'til 9:50PM to be seated for a 9PM Saturday reservation."], "output": "[['place', 'negative'], ['diners', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["this has become one of my favorite spots to hang out at the bar and drink martinis, not only because the atmosphere is energetic and lively, but also becasue the staff are so friendly."], "output": "[['bar', 'neutral'], ['drink martinis', 'neutral'], ['atmosphere', 'positive'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Just don't take the seat between the bar and the back half of the restaurant, i saw a woman get nudged 40times sitting there."], "output": "[['seat', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It was more than enough food even though the portions are tiny."], "output": "[['food', 'positive'], ['portions', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Today I placed a lunch order and the guy hung up on me while I was saying thank you!"], "output": "[['lunch', 'neutral'], ['guy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu was nothing special (I had to switch my entree choices several times because the server told me that the portion is really REALLY small!)"], "output": "[['menu', 'neutral'], ['server', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["you need to steer clear of--our fish was burned on the outside, raw on the inside and we won't even discuss the fried oysters and clams (we had ONE clam!)"], "output": "[['fish', 'negative'], ['fried oysters and clams', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had a 9:30pm reservation for two which stretched out to an hour wait."], "output": "[['reservation', 'neutral'], ['wait', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The liquid brunch consisting of 3 drinks (bloody marys, mimosas or screwdrivers) and coffee and an entree is quite a bargain."], "output": "[['brunch', 'neutral'], ['drinks', 'neutral'], ['mimosas', 'neutral'], ['entree', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu could be a little bigger but my food as well as my boyfriend's was outstanding (and a lot less expensive than I expected)."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The smell near the bar is unbearable, the food is so so, nothing out of the norm, just very plan."], "output": "[['bar', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After I inquired why the food was taking so long, the waitress told us that the 2 dishes we ordered take a long time."], "output": "[['food', 'neutral'], ['waitress', 'neutral'], ['time', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For the most part I enjoyed my dining experience at Revival (not to be confused with the bar on 15th)."], "output": "[['dining experience', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["But the service, though invariably genial and helpful, can be weirdly haphazard -- waiters disappear mysteriously, only to reemerge just when you've decided their shift must have ended -- possibly an understaffing issue?"], "output": "[['service', 'positive'], ['waiters', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The salads were amazing in themselves - mixed greens andtomato wedges in a delicious balsamic vinagrette with slices of Italian bread with warm goat cheese."], "output": "[['salads', 'positive'], ['mixed greens', 'neutral'], ['balsamic vinagrette', 'positive'], ['slices', 'neutral'], ['Italian bread', 'neutral'], ['goat cheese', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The rude and unaccomodating hostess (who we later learned was the manager) repeatedly promised us the next table but never offered to buy us a drink while we waited."], "output": "[['hostess', 'negative'], ['manager', 'negative'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Though if the restaurant got bigger, the service and quality of the food would probably suffer."], "output": "[['service', 'negative'], ['quality', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I specifically recommend the eggs with potato pancakes for breakfast and the orange beef for dinner."], "output": "[['eggs with potato pancakes', 'positive'], ['breakfast', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Fun atmosphere, good beer selection, but meals were skimpy portions on big plates and the service was weak - never had the same server/waitperson come back twice."], "output": "[['atmosphere', 'positive'], ['portions', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I walk in ask to take a look a the menu and was greeted by the a nasty not so passive aggressive hostess."], "output": "[['menu', 'neutral'], ['hostess', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although we had to wait a few minutes for our table, the manager bought us a round of drinks and proceeded to take care of throughout the entire meal."], "output": "[['table', 'neutral'], ['manager', 'positive'], ['round of drinks', 'neutral'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["straining to read the menu under the low-lighting-tag-sale-chandelier motif, we were able to order a salad, tapas, and entrees from the first of several waiters, none of whom were able to introduce themselves, recommend dishes, present silverware, remove plates, or deliver water when asked."], "output": "[['menu', 'neutral'], ['salad', 'neutral'], ['entrees', 'neutral'], ['waiters', 'negative'], ['dishes', 'neutral'], ['plates', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["As we were wrapping up a very rushed meal--appetizers were barely started when the entrees arrived crowding a table for two at which three were crammed--the hostess charged over and grabbed a half-full wine glass declaring thanks ladies, I'll get your check."], "output": "[['meal', 'negative'], ['appetizers', 'neutral'], ['entrees', 'neutral'], ['table', 'neutral'], ['hostess', 'negative'], ['half-full wine glass declaring', 'neutral'], ['check', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["That bastion of authentic Mexican food in Spanish Harlem that earned raves by white reviewers, leading other gringos to nervously venture to Spanish Harlem and pretend they're trendy to pay too much for food that is only marginally better than the place around the corner."], "output": "[['Mexican food', 'positive'], ['reviewers', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Waited 30 min for a brick they call bread and water, another hour for food (tiiiiiiiny portions)."], "output": "[['bread', 'neutral'], ['water', 'neutral'], ['food', 'neutral'], ['portions', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere is still to die for, but the wine list has so clearly been pared down and marked up (as a result of higher foot traffic brought in by lots of rave reviews in local publications, perhaps?"], "output": "[['atmosphere', 'positive'], ['wine list', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They have little booths if you want a little privacy w/ your date~ and they have large tables for families and groups."], "output": "[['privacy', 'neutral'], ['tables', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["One hour into our dinner, we were told by the hostess that we needed to hurry up and finish so that they could accommodate the next party's reservation."], "output": "[['dinner', 'neutral'], ['hostess', 'negative'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["So when i walked in i was just blown away by the lighting, flowers, wood and iron work, a reservationist, and a full bar."], "output": "[['lighting', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The portions were very big for appetizers (calimari and fried zucchini) but average for the entrees (chicken marsala, spaghetti w/ meatballs) and very expensive of course."], "output": "[['portions', 'positive'], ['appetizers', 'neutral'], ['calimari and fried zucchini', 'neutral'], ['chicken marsala', 'neutral'], ['spaghetti w/ meatballs', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Service was en pointe and I felt like the servers were always aware of our wants, whether it was punctual refill of water, new napkins, etc."], "output": "[['servers', 'positive'], ['water', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While the server offered nothing, the host apologized, and said that he hoped that I would return again, perhaps for brunch."], "output": "[['server', 'negative'], ['host', 'positive'], ['brunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food came out wrong, the waiter was no where to be found and the wine showed up at the end of the meal."], "output": "[['waiter', 'negative'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Jackson Diner was my first intro to true Indian food and its been 10yrs since and I cannot go one month without some of this unbelievable food."], "output": "[['Diner', 'neutral'], ['Indian food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Apparently, the waitress informed us that they change the menu at 5 Ninth every few days, which kind of explains the hit or miss situation."], "output": "[['waitress', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They were more than happy to seat us even though we were early for our reservation."], "output": "[['seat', 'positive'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The wait staff was attentive without being overbearing, and our waiter gave thoughtful advice on dishes that would be suitable for the children."], "output": "[['wait staff', 'positive'], ['dishes', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I would only recommend this restaurant to a friend if waiting at least 40 minutes for your RESERVATION is acceptable, and you don't mind paying for relatively standard fare."], "output": "[['RESERVATION', 'neutral'], ['fare', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["He did do the service part well enough -- brought the food, etc."], "output": "[['service', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Needing a sugar fix, my husband and I walked in here to find a wall to wall adornment of delightful confections."], "output": "[['sugar', 'neutral'], ['confections', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["me , i hated it, the center of the pork one was frozen,  salad was ok, wine was a little corcked."], "output": "[['pork', 'negative'], ['wine', 'negative'], ['salad', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The bar was a disaster because there were no tables for anyone, and drinks took 20 minutes to receive."], "output": "[['bar', 'negative'], ['tables', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["since it looks like everyone's already familiar with the rude hostess and long wait for a table (even with a reservation), i'll skip that part."], "output": "[['hostess', 'negative'], ['wait', 'negative'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I usually run the other way when I hear of an Italian restaurant with huge portions, because it's usually a lot of mediocre food."], "output": "[['portions', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I've only been here once for dinner but I think the lunch specials are definitely a better deal."], "output": "[['dinner', 'neutral'], ['lunch specials', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although we had to wait a long while and the hostess was very busy behind the bar, she was very apologetic and sincere which made it feel ok to have to wait."], "output": "[['hostess', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It's just a diner, but three decent hearty lunches for 12 bucks?"], "output": "[['diner', 'neutral'], ['hearty lunches', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although we were seated 35 minutes after our reservation the service from then on was outstanding."], "output": "[['reservation', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Since the service was so poor, we asked if they could offer any concessions - complimentary drinks?"], "output": "[['service', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waitress asked us if we wanted anything else, we said only the check - she quickly scooped up our not-yet finished food."], "output": "[['waitress', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Waiter dropped check on table while I was in the middle of handing my wife her anniversary present."], "output": "[['Waiter', 'negative'], ['check', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I'd like to try their brunch - the menu looks good."], "output": "[['brunch', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The sangria was served quickly and often."], "output": "[['sangria', 'neutral'], ['served', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Bountiful sushi platters, which focus on familiar basics like salmon and tuna, are best followed by green-tea ice cream for dessert."], "output": "[['sushi platters', 'positive'], ['salmon and tuna', 'neutral'], ['cream', 'positive'], ['dessert', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Each dish had its own distinct character and pleasant flavor surprises."], "output": "[['dish', 'neutral'], ['flavor surprises', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Nonetheless, we are looking forward to the next time for more pizza and the great service."], "output": "[['pizza', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When his to sons joined the mix they took Dads quest for the best food another step adding slowly to the menu a host of items that reflect the demigraphic of this still growing nabe."], "output": "[['mix', 'neutral'], ['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Once we had our menus we were nearly assaulted by wait staff asking if we were ready to order."], "output": "[['menus', 'neutral'], ['wait staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["On each of my several visits, the crowd is local, professional, family and those who are not familiar with the cuisines of India are deftly walked through the menu by management."], "output": "[['crowd', 'positive'], ['cuisines', 'neutral'], ['menu', 'neutral'], ['management', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The place was small and simple, but I never cared about service or decor."], "output": "[['place', 'negative'], ['decor', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There are a few things I can forgive at any popular place: somewhat long waits even with reservations, service staff that mistakenly believes they're there to act haughty rather than serve, and a way over-the-top interior."], "output": "[['reservations', 'neutral'], ['service staff', 'negative'], ['interior', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We got there early so there wasn't much of a wait -- otherwise, I usually sit at the bar and have a cocktail."], "output": "[['wait', 'positive'], ['bar', 'neutral'], ['cocktail', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While the decor is a bit bland--a white room with a few fake palm trees and thatched roof--the service is fast and friendly."], "output": "[['white room', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Raz Mojito is excellent (stay away from the champagne)."], "output": "[['Raz Mojito', 'positive'], ['champagne', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was horrible, we had the Peking duck salad, tuna, vegetable fried rice, and the spinach."], "output": "[['food', 'negative'], ['Peking duck salad', 'neutral'], ['tuna, vegetable fried rice', 'neutral'], ['spinach', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I'll give it to Sea; the decor is pretty cool and the food was good, but the service was beyond terrible!"], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went here all 4 years that I lived in the area, and being a not-so-loaded student, it was a great place to go for some good sushi and a very pleasant comforting atmosphere."], "output": "[['area', 'neutral'], ['sushi', 'positive'], ['atmosphere', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We started with the guacamole and this is by far the best I've ever had bar none."], "output": "[['guacamole', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["and to get an extra side vegtable was close to $20 for overdone asparagus that had no taste."], "output": "[['vegtable', 'neutral'], ['asparagus', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Eggs benedict with smoked salmon was equally fine and the portion was adequate for lunch."], "output": "[['Eggs benedict with smoked salmon', 'positive'], ['portion', 'positive'], ['lunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the wait for our drinks, appetizers and food was very long, the food was mediocre, and it was a bit pricey."], "output": "[['wait', 'negative'], ['drinks', 'neutral'], ['appetizers', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Hillarious lighting and ecclectic side dishes make you want to love the place, but the meal on the whole was abyssmal."], "output": "[['place', 'positive'], ['meal', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The mariachi band that walked around during dinner was fun and like I stated before the food is delish!"], "output": "[['dinner', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Went to Gallaghers for the first time on a Saturday night, had no problem getting reservations, great staff-great service."], "output": "[['reservations', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The chef even came out with a sample some new appetizers he's working on (the tuna tartare is a keeper!"], "output": "[['chef', 'positive'], ['new appetizers', 'neutral'], ['tuna tartare', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Even better was the food, had shrimp wrapped in prosciutto, followed by lamb chops, and of course a double macchiato to finish it all off."], "output": "[['shrimp wrapped in prosciutto', 'positive'], ['lamb chops', 'positive'], ['course', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I love the food and as a person that does not drink often or regularly, I am practically addicted to their sangria."], "output": "[['food', 'positive'], ['drink', 'neutral'], ['sangria', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The amble sweetbreads and goat cheese/caviar ravioli appetizers were memorable, but the highlight of our dinner was the scallops in a cream reduction entree - truly heavenly."], "output": "[['amble sweetbreads', 'positive'], ['goat cheese/caviar ravioli appetizers', 'positive'], ['dinner', 'neutral'], ['scallops in a cream reduction entree', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The whole time we were waiting the hostess kept talking to us, telling us we wouldn't lose our reservation, and even gave us free blue margarita shots!"], "output": "[['hostess', 'positive'], ['reservation', 'neutral'], ['blue margarita', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Also the waiter anever asked if the steaks were cooked to out liking or if we wanted anything else."], "output": "[['waiter', 'negative'], ['steaks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Don't know if the bar is really that bad, BUT the food would more than compensate!"], "output": "[['bar', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The managers aren't snobby for wanting reservations -- it's a new restaurant and they're trying to manage the flow of diners."], "output": "[['managers', 'negative'], ['reservations', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went there recently with my boyfriend and not only did it take the waitress 20 minutes to acknowledge we were even there, 20 minutes to get us water and coffee and even MORE time to place our order and get food!"], "output": "[['waitress', 'negative'], ['water', 'neutral'], ['coffee', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A good restaurant would have at least comped desert or sent over a round of drinks for such a long wait -- we didn't even get an apology from a manager."], "output": "[['round of drinks', 'neutral'], ['manager', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The sweetness of succulent barbecued pork and thick salsa cruda counterpoint a salty and garlicky fresh guacamole."], "output": "[['succulent barbecued pork', 'positive'], ['thick salsa cruda', 'neutral'], ['guacamole', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We complained to our waiter serveral times about this and the stares continued and to top it all off as the manager walked around to each table asking if they enjoyed their dinner, he conveniently did not ask us!"], "output": "[['waiter', 'neutral'], ['table', 'neutral'], ['dinner', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food In a health-conscious century, it's as likely to be the pub grub as it is the booze that does you in."], "output": "[['Food', 'positive'], ['pub', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although we were seated right away and the waiter brought menus promptly as well as drink, he was almost never at our table despite being at the other tables right next to ours."], "output": "[['waiter', 'positive'], ['menus', 'neutral'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Went there a few months ago, and while the food was really good, and I was ready for it to be pricey, the one thing that bothered me was the waiter was standing in a corner watching us eat."], "output": "[['food', 'positive'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The average price of a meal (app, entree, 1 drink and tip) is probably around $28."], "output": "[['price', 'neutral'], ['meal', 'neutral'], ['app', 'neutral'], ['entree', 'neutral'], ['drink', 'neutral'], ['tip', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although the food what adequate, the service was preposterous."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were also seated promptly at the time of our reservation and the service was very quick and professional."], "output": "[['reservation', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": [") I also noticed the table next to ours didn't enjoy her dish and they went above and beyond to try to make up for it."], "output": "[['table', 'neutral'], ['dish', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waitress was merely inattentive at first but became just plain hostile after we had the nerve to ask about the wine we had ordered to go with dinner (we were halfway through our entrees and still no wine)."], "output": "[['waitress', 'negative'], ['dinner', 'neutral'], ['entrees', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We did enjoy the recommended, yet simple $40 sangiovese, atmosphere and loosey-goosey service, but we were disappointed overall."], "output": "[['atmosphere', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went to Mocca with my boyfriend for a few drinks and food, and I was really impressed by the service."], "output": "[['drinks', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["oh, and if you're there for drinks at 3:30 on a weekday afternoon, when the place is empty - and ask for a bread basket - they'll charge you $6."], "output": "[['drinks', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have been back for several dinners and lunchs and especially like the terrace when weather permits."], "output": "[['dinners', 'neutral'], ['terrace', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food Chef Nao Sugiyama serves in the traditional kaiseki style--a kind of tasting menu consisting of between six and 12 small courses."], "output": "[['Food Chef', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["4 of had dinner here last Saturday and we were all very disappointed with the food and the service."], "output": "[['dinner', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Go in, take a deep breath and expect great food, fairly priced with just about the worst service in North Jersey!"], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The crust was a crispy tan dream come true with those little blackened air bubbles and chewy center."], "output": "[['crust', 'positive'], ['blackened air', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We told the waitress a few more were coming and ordered drinks."], "output": "[['waitress', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu alternates between typical American fare (salads, potato skins, Angus burgers and grilled chicken) and modestly international cuisine like fajitas, wraps and pot stickers."], "output": "[['menu', 'neutral'], ['American fare', 'positive'], ['salads', 'neutral'], ['potato skins', 'neutral'], ['burgers and grilled chicken', 'neutral'], ['international cuisine', 'positive'], ['wraps', 'neutral'], ['pot stickers', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It's unfortunate because the food is generally pretty good, although the waitstaff did try to convince us once that the flan they gave us was really creme brulee."], "output": "[['food', 'positive'], ['waitstaff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our salads and appetizers were brought at the same time and we barely had time to enjoy them before a team of waiters whisked them (and our bread!)"], "output": "[['appetizers', 'neutral'], ['waiters', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Her attitude put a damper on the evening, as did the stares from some servers when we took a peek into the cheese cellar."], "output": "[['servers', 'negative'], ['cheese cellar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When I went back to the hostess (yes it was past the time we had for our original reservation) - she said that it was fine to get seated but we needed to leave in an hour."], "output": "[['hostess', 'negative'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Generous portions of rice porridge and noodles really hit the spot after fighting the crowds on a busy weekend in Chinatown."], "output": "[['portions of rice porridge', 'positive'], ['noodles', 'positive'], ['crowds', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I loved the food and service here, the only downside was the decor was dissappointing and the prices are a bit high (about $30 for an entree."], "output": "[['food', 'positive'], ['service', 'positive'], ['decor', 'negative'], ['prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["one waiter couldn't remember what we had to drink and we were the only people in the place."], "output": "[['waiter', 'negative'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The wait here is long for dim sum, but if you don't like sharing tables or if the typical raucous dim sum atmosphere is not your gig, this is a sleek (for Chinatown) alternative."], "output": "[['wait', 'negative'], ['dim sum atmosphere', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went with a party of 7, we all had drinks, tomato and onion salad, slabs of bacon, all the extras and magnificent steaks."], "output": "[['drinks', 'neutral'], ['tomato and onion salad', 'neutral'], ['slabs of bacon', 'neutral'], ['steaks', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitstaff can be hard to track down and uninformed about the menu."], "output": "[['waitstaff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Decent value for decent chinese food for the area - obviously you can get cheaper down in chinatown."], "output": "[['value', 'positive'], ['chinese food', 'positive'], ['area', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The oysters were warm as was the sushi that was served over dry rice."], "output": "[['oysters', 'positive'], ['rice', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Try the salmon - I was a bit concerned about the fennel - but this dish's combination of textures and flavors left me wanting more."], "output": "[['salmon', 'positive'], ['dish', 'neutral'], ['flavors', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I think I'm going to start taking the food and coffee to go b/c everytime I go there (which is quite often) I get more frustrated with the service."], "output": "[['food', 'neutral'], ['coffee', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["PDiddy need a new staff you would have thought it was a bunch of old people cooking the food and waiting on us."], "output": "[['new staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We waited to be seated for about 15-20 minutes for brunch, while it was quite obvious that there were plenty of empty tables right in front of us."], "output": "[['brunch', 'neutral'], ['tables', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["From the enormous menu, we opted for the 3-course dinner specials - chicken soup or clam chowder, although small portions, came with loads of rolls, crackers etc."], "output": "[['menu', 'positive'], ['portions', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I don't drink coffee so I can't judge that but if you want a friendly place to take a time out- read - people watch and enjoy a bagle, pastry or sandwitch this is a great place with liberal politics and nop pretensions."], "output": "[['coffee', 'neutral'], ['bagle', 'positive'], ['pastry', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Whatever the twist they supposedly have added is nothing new in Chinese cuisine (maybe except foie gras)."], "output": "[['Chinese cuisine', 'negative'], ['foie gras', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Dinner was recently a lamb special - large gristly hunks of lamb slopped on plate, swimming in a pool of watery sauce with chopped asparagus thrown all over plate."], "output": "[['Dinner', 'neutral'], ['sauce with chopped asparagus', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A great place to eat or just hang out at the bar."], "output": "[['place', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have dined at JG many times for dinner and lunch over the past two years and both the food and the service is by far the best compared to others in NYC or else where."], "output": "[['lunch', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Waitress was nice but didnt know some specials and was alittle off, think she was new."], "output": "[['Waitress', 'positive'], ['specials', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The top layer of my adobo salad was nice enough, but just below the surface it began to swim in a cloyingly sweet dressing, so that it became like some weird melted jello concoction."], "output": "[['adobo salad', 'positive'], ['concoction', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Increedible value, 3 courses $20 price fixe(menu changes everyday), organic seldom seen wines all around $20."], "output": "[['value', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Perfect place to bring a date before the theater, a mother/ grandmother/ or aunt for their birthday, or friend for lunch."], "output": "[['place', 'positive'], ['lunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food quality is good, but the prices are not worth it!"], "output": "[['food quality', 'positive'], ['prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My friend and I had brunch the coffee was cold, too much worcestershire sauce in the bloody mary."], "output": "[['brunch', 'neutral'], ['sauce', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene Superfine is an easygoing, instantly appreciable neighborhood hangout that boasts a kitchen staff armed with serious cooking chops."], "output": "[['Scene', 'positive'], ['kitchen staff', 'neutral'], ['cooking chops', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The burger was just a big klump of dry meat with 1 slice of cheese."], "output": "[['burger', 'neutral'], ['meat', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu consists of a tasting selection, Austrian, traditional American, and the chef's recommended menu."], "output": "[['selection', 'positive'], ['Austrian', 'positive'], ['American', 'positive'], ['chef', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Check out the little room with the red seats and candles and get a green dragon saketini - it's worth the NYC cocktail price ($14)."], "output": "[['red seats', 'neutral'], ['candles', 'neutral'], ['cocktail price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was awful and took forever to arrive - which considering the limited menu, few diners and the fact that we ordered chili, mac cheese and a grill cheese was annoying."], "output": "[['menu', 'negative'], ['diners', 'negative'], ['chili', 'neutral'], ['mac cheese', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["50, I got the Paella Marinera which was beyond filling in itself, but before it even came, the waitstaff provided more than ample appetizers for my group that by the time that the meal came to us, we were so stuffed, we could barely finish up the meal."], "output": "[['waitstaff', 'positive'], ['ample appetizers', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Keep in mind, no one else was even in the restaurant and we were asking the waitress questions about entree options."], "output": "[['waitress', 'negative'], ['entree options', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitress was unbelievably rude to my friend and myself when she realized that we were ordering appetizers as our entrees."], "output": "[['waitress', 'negative'], ['appetizers', 'neutral'], ['entrees', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter was pushing us all night to take our plates, and swiped my dessert before I was finised with it."], "output": "[['waiter', 'negative'], ['plates', 'neutral'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The word chicken was barely out of my mouth when the waiter rushed away from my table without asking me about side orders or a drink."], "output": "[['word chicken', 'neutral'], ['waiter', 'negative'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Unlike some of the other reviews here, the reservation was upheld, the waiter took the time to explain each dish and frequently asked if we wanted more of anything (which we did, several times)."], "output": "[['reservation', 'positive'], ['waiter', 'positive'], ['dish', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Main dishes encompass the usuals--like chocolatey chicken mole and grilled flank steak-- well as seasonal specials, like soft-shell crabs with orange tequila sauce."], "output": "[['grilled flank steak', 'neutral'], ['specials', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["their filet mignon was prepared very well but lacked the flavor and savvy I generally require food at that price to have."], "output": "[['filet mignon', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Upon entering, I was impressed by the room while the food on other peoples' tables seemed enticing."], "output": "[['food', 'neutral'], ['tables', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The place was extremely busy, and with food like this why not."], "output": "[['place', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Some other appetizers fell short of expectations though (ie, good, but not worth the price), like the tempura and veggies."], "output": "[['appetizers', 'negative'], ['veggies', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The highlight of the night was the mayonaisse for my side of fries I received from one of the food runners, which is not good considering the bill was nearly $100."], "output": "[['mayonaisse', 'positive'], ['fries', 'neutral'], ['food runners', 'neutral'], ['bill', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After taking unusually long to bring the wine, the waiter could not open the bottle and had to get a different one."], "output": "[['waiter', 'negative'], ['bottle', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["UNREAL LUNCH can't go wrong with pastas or sandwiches, thin crust pizza is good, would steer away from the deep dish."], "output": "[['LUNCH', 'neutral'], ['pastas', 'neutral'], ['sandwiches', 'neutral'], ['crust pizza', 'positive'], ['dish', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Waiters and busboys were taking our water glasses and the tip tray off the table before we had counted the change."], "output": "[['Waiters', 'negative'], ['water glasses', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["At the end of the meal the manager stopped by and said dessert was on her."], "output": "[['meal', 'neutral'], ['manager', 'positive'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Went to Public last Saturday, couldn't get a table so the lovely host suggested that my partner and I dine at the bar."], "output": "[['table', 'neutral'], ['host', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A basic sandwich/burger menu is also served for pre-ice cream nourishment--just always remember to leave room for dessert!!"], "output": "[['menu', 'neutral'], ['pre-ice cream nourishment', 'neutral'], ['dessert', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food at Parish was tasy and well-prepared, but the portions were absurdly miniscule, especially in proportion to the prices."], "output": "[['food', 'positive'], ['portions', 'negative'], ['prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Diners at the bar watch busy chefs scoop lobster salad onto warm brioche rolls."], "output": "[['bar', 'neutral'], ['lobster salad', 'neutral'], ['brioche rolls', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was below average , I'm not a great cook and I could have cooked a better meal."], "output": "[['food', 'negative'], ['meal', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I dined at Belleville and my meal was distrupted by the manager yelling at the wait staff in the middle of the dining room."], "output": "[['meal', 'neutral'], ['manager', 'negative'], ['wait staff', 'negative'], ['room', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Even if you have to wait a bit for a reservation, the hostess will come over to apologize, update you on the wait and make sure you are comfortable."], "output": "[['reservation', 'neutral'], ['hostess', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["i ordered non-sushi rolls and enjoyed my meal."], "output": "[['non-sushi rolls', 'neutral'], ['meal', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There are no vegetarian items on the menu, but when I requested that the chef make something meat-free for me, he came through with a dish just as delicious and pretty as those my friends were eating."], "output": "[['menu', 'neutral'], ['chef', 'positive'], ['dish', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My friend and I were the ONLY 2 people in the entire place seated for dinner and after sitting there for 15 minutes, I had to walk over to our surly waiter and ask for menus."], "output": "[['seated', 'neutral'], ['dinner', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The veal was nice and tender, but the flavors weren't exciting."], "output": "[['veal', 'positive'], ['flavors', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The handwritten menu makes me think the choices change frequently -- we started with pumpkin fritters and then had bunny rabbit and sea bass cakes."], "output": "[['handwritten menu', 'neutral'], ['rabbit', 'positive'], ['sea bass cakes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["it is too bad because the food, ambiance, and drinks were great but they need serious help on the service."], "output": "[['food', 'positive'], ['ambiance', 'positive'], ['drinks', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After sitting without any beverages for about fifteen minutes, the manager got up and poured a glass of water for his smacking companion."], "output": "[['beverages', 'neutral'], ['manager', 'negative'], ['glass of water', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It was super busy, but our waiter still had time to chat, and knew the menu very well."], "output": "[['waiter', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When I asked for a particular drink, the waitress gave me dirty look and annoyed b/c they didn't know what it was."], "output": "[['drink', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["huuge portions, which made it much easier paying the $350 bill."], "output": "[['portions', 'positive'], ['bill', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["BTW, the prices are very affordable, which make the mediocer service tolerable."], "output": "[['prices', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["and don't be ashamed to ask for more during the hour long wait for your entrees."], "output": "[['wait', 'negative'], ['entrees', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["What we were treated to, instead, was snooty attitude by the waiter and the maitre d' and a dinner I couldn't eat."], "output": "[['maitre', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Still my favorite part of the restaurant and bar adjacent are the drinks."], "output": "[['bar', 'neutral'], ['drinks', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A cold reception got even colder when we didn't have a reservation for a Tuesday night (the place was half empty)."], "output": "[['reservation', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I don't know why the place was almost empty until 8PM, but the food and service were perfect for the price."], "output": "[['place', 'negative'], ['food', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Ignoring the merits of the cuisine (which was par at best), I see no reason why one would pay Da Umberto prices for an okay meal and below average ambience."], "output": "[['prices', 'neutral'], ['meal', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We tried their new menu that just started last Wednesday a combination of 4 different kind of ceviches and 4 kinds of Tiradito, of course you can't go wrong with spicy Tuna Rolls and The Peruvian Corn mmmm!"], "output": "[['menu', 'positive'], ['Tuna Rolls', 'positive'], ['Peruvian Corn', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Even with reservations, we had to wait 20 minutes until our server came to take our order, then waited an HOUR 10 minutes for our food!"], "output": "[['reservations', 'neutral'], ['server', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It takes forever for them to serve you just drinks, and some of the waiters seem to not comprehend what you order."], "output": "[['drinks', 'neutral'], ['waiters', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The next thing we know, the bartender comes over and says (and I quote verbatim), I already gave you two beers (which he hadn't)."], "output": "[['bartender', 'negative'], ['beers', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I did not try the caviar but I tried their salmon and crab salad (they are all good)  It is definitely a good spot for snacks and chat."], "output": "[['caviar', 'negative'], ['salmon and crab salad', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["i would not go after the early bird b/c its not worth it, find better food for full prices."], "output": "[['food', 'positive'], ['prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Granted we were just the girls, but this would also be a great date spot b/c the ambiance is chic and bustling yet you can also hear the conversation at your own table rather than a loud din or worse, someone else's conversation."], "output": "[['spot', 'positive'], ['ambiance', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The noise here is so bad that people entered and left without ordering and they lowered the lights during the dinner."], "output": "[['noise', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Tapas, served four at a time in small white porcelain trays, are a highlight--salt cod fritter stuffed with parsley-garlic sauce melts in the mouth, while pan-fried duck liver sits in a rich mix of sherry vinegar, honey and black pepper."], "output": "[['Tapas', 'positive'], ['white porcelain trays', 'neutral'], ['salt cod fritter stuffed with parsley-garlic sauce', 'positive'], ['duck', 'positive'], ['mix of sherry vinegar', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The complementary cognac at the end of dinner will leave you with a smile on your face :)."], "output": "[['cognac', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["To complain about waiting for a table, etc."], "output": "[['waiting', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We got there a bit early and the staff wasn't ready for us but we didn't mind b/c we got to wait by the beautiful bar."], "output": "[['staff', 'negative'], ['bar', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Seemed to be many problems just getting our appetizers out (guacamole, which was delicious when it finally came) and we were there an hour before entrees arrived."], "output": "[['appetizers', 'neutral'], ['guacamole', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We figured we never had Argentinian Pizza before so we grabbed our lunch there, sharing a large Pelligrino, a pizza of two of their specials, one was goat cheese the other blue cheese, and both were excellent."], "output": "[['Argentinian Pizza', 'neutral'], ['lunch', 'neutral'], ['Pelligrino', 'positive'], ['goat cheese', 'positive'], ['blue cheese', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There are several specials that change daily, which the servers recite from memory."], "output": "[['specials', 'positive'], ['servers', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Bringing a large group on a busy Saturday night ,I was afraid quality of food and service might not be up to par, but we were seated promptly and the service by our waitress was fantastic considering how busy it was."], "output": "[['quality of food', 'negative'], ['seated', 'positive'], ['waitress', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While the place looks rather small and undecorated, I will definitely go back just for the food."], "output": "[['place', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I used to live in Japan, and have had some pretty good raw fish, but I was blown away by the Chef's tasting plate, which includes 6 appetizers including a stunning octopus portion and some incredible sashimi."], "output": "[['fish', 'positive'], ['Chef', 'neutral'], ['plate', 'positive'], ['appetizers', 'neutral'], ['stunning octopus portion', 'neutral'], ['sashimi', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["All this Asian fusion craze leaves one feeling like they should've went to an authentic Thai or Indian restaurant for probably 1/3 of the price of Spice Market."], "output": "[['Thai', 'positive'], ['price', 'neutral'], ['Spice', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Park your trench coat at the coat check and be prepared for fine dining, expert / attentive table service and a delectable cuisine."], "output": "[['coat check', 'neutral'], ['dining', 'positive'], ['table service', 'positive'], ['cuisine', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The fruit that came with the fondu was perfectly ripe, no bruises at all."], "output": "[['fruit', 'positive'], ['fondu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Instead of doing so, the manager came to our table and told us he'd be happy to take our orders off if we didn't like the way he ran his restaurant."], "output": "[['manager', 'positive'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My friends and I had a great time - the atmosphere was exciting but didn't encroach on us while we had our meal and drinks (which is better, the kiwitini or the watermelon martini?)"], "output": "[['atmosphere', 'positive'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere was nice (tables were a bit too close together) and trendy, but waiters seemed rushed."], "output": "[['atmosphere', 'positive'], ['tables', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Recommend eating at the bar for an intimate, relaxed dinner."], "output": "[['bar', 'neutral'], ['dinner', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Went with a large group of 7 ladies before a show, and the staff was extremely obliging, even when one person was late and we had to wrap up her dinner to take to her."], "output": "[['staff', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Jalepeno slices and a little bit of cheese, yes again them hamburgers make me weak in my knees."], "output": "[['Jalepeno slices', 'neutral'], ['cheese', 'neutral'], ['hamburgers', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I love the food, and have gone back several times, but each time the waitress is a little nastier."], "output": "[['food', 'positive'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Desserts were visually inventive but lacking in flavor."], "output": "[['Desserts', 'positive'], ['flavor', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["And price is over value for two persons dinner $ 90."], "output": "[['price', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We also had an extra appetizer-some sort of fish roll, which was dipped in spicy sauce."], "output": "[['sort of fish roll', 'neutral'], ['sauce', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["went here w/ great expectations and was greatly disappointed; the food was good, not great and vastly overpriced- one salad, two pasta dishes, two demi-carafes of red wine- $100 (tax and tip); rediculous; orechiette came w/ so little brocoli rape that it did not have its characteristic flavor; and it is very very loud."], "output": "[['food', 'positive'], ['flavor', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We went there just for dinner, and the place was so good we didn't leave."], "output": "[['dinner', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The ambience is cool, and the cocktails might be worth coming by, but head somewhere else for dinner."], "output": "[['ambience', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When her boyfriend told the host that she would like to keep her seat as it was, he grabbed a chair and slammed it down very hard on the floor."], "output": "[['host', 'negative'], ['seat', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["my boyfriend's fish was overwhelmed by the sauce."], "output": "[['fish', 'negative'], ['sauce', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Bollos appetizer, this deliciouss black bean, roasted corn fritter w/ a tsty dipping sauce and the Mahi Mahi was grilled just right."], "output": "[['Bollos appetizer', 'neutral'], ['roasted corn fritter w/ a tsty dipping sauce', 'positive'], ['Mahi Mahi', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waitress seemed less than happy about the prix fixe dinner choices and at one point said, Do you really need to hear the specials?"], "output": "[['waitress', 'negative'], ['specials', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Setting aside the interminable wait for food, the cheese omelet opened up on the way from the kitchen to the table so that when it arrived, it looked like a large yellow pancake with a slab of uncooked cheese sitting in the middle."], "output": "[['wait', 'negative'], ['food', 'neutral'], ['cheese omelet', 'neutral'], ['table', 'neutral'], ['yellow pancake', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The staff is nice, but they have the awful job of having to sell bland food as amazing treats."], "output": "[['staff', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This is the perfect place to come with a group from work, people from out of town, or just to have a drink at the bar and enjoy the atmosphere."], "output": "[['drink', 'neutral'], ['bar', 'neutral'], ['atmosphere', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There is a litte bit of a wait on the food, but it is well worth it!"], "output": "[['wait', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["but above all, they do have fresh fish, especially salmon and yellowtail."], "output": "[['fish', 'positive'], ['salmon', 'neutral'], ['yellowtail', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The calamari, the penne and vodka sauce, the friendly service the parking and the open area kitchen to see all the action in the making!"], "output": "[['calamari', 'neutral'], ['penne and vodka sauce', 'neutral'], ['service', 'positive'], ['open area kitchen', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["One server came and gave us food that turned out to be someone else's."], "output": "[['server', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Perhaps it's early and they will improve but service is VERY slow - took a good 25min for waiter to take our order on both visits and the second time I was one of three tables at a 5:30pm reservation so not like it was busy."], "output": "[['service', 'negative'], ['waiter', 'negative'], ['tables', 'neutral'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Even with our large appetites we could not finish all the food or wine, which has never happened with a tasting menu before."], "output": "[['food', 'neutral'], ['wine', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The chef/owner is always walking around making sure everyone is having a good time."], "output": "[['chef/owner', 'neutral'], ['time', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A shrimp dish that was boiled and in a sauce that tasted like unflavored jello."], "output": "[['shrimp dish', 'neutral'], ['sauce', 'neutral'], ['jello', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After losing our reservation the staff at March called 24 hours later to apologize and ask if we would still like to dine there."], "output": "[['reservation', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Enough space between tables that you don't feel crowded or that it's too loud."], "output": "[['space', 'positive'], ['tables', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This is a wonderful mix of food from Turkey and the Caucasus."], "output": "[['mix', 'positive'], ['food', 'positive'], ['Turkey', 'neutral'], ['Caucasus', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter messed up my order and we had to hunt down the wait staff to get a second drink."], "output": "[['waiter', 'negative'], ['wait staff', 'negative'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Unfortunately for them, we would have ordered twice as many drinks if we didn't have to wait half an hour for the waitress between every drink."], "output": "[['drinks', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For such an expensive place, you can find much, much better in Manhattan; heck, you can find much better food for a lot cheaper!"], "output": "[['place', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Appetizers: those that we tried were good, though skip the soup, cuz you can eat that at home since it tasted like Campbells."], "output": "[['Appetizers', 'positive'], ['soup', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Asking for the menu is out of line and unusual where the staff is actually insulted if you choose not to rely on their expertise on average Chinese food selections."], "output": "[['menu', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For lunch, walk in slightly after 1pm to avoid long lines."], "output": "[['lunch', 'neutral'], ['lines', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Like the previous reviewer said, the appetizers were by far the best part (chipotle chicken wings)."], "output": "[['appetizers', 'positive'], ['chicken', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The complimentary salmon with horseradish sauce was delicious and I don't even like eating fish."], "output": "[['salmon with horseradish sauce', 'positive'], ['fish', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The plain slice is a bit pricey for what you get sometimes, but the pre-made multi-topping slices are a bargain at $3 a pop."], "output": "[['plain slice', 'negative'], ['pre-made multi-topping slices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I tried both and definitley thought the duck was amazing, I'm not generally not a big fan of lamb shank but thought they did a good job here."], "output": "[['duck', 'positive'], ['lamb', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I don't expect an enormous, heaping plate of food, but c'mon."], "output": "[['plate', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The ubiquitous nasty plastic cheese bread that passes for pizza in too many NYC establishments these days."], "output": "[['plastic cheese bread', 'negative'], ['pizza', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Once we had ordered etc, the wait for our meal was not long and the food was fabulous."], "output": "[['wait', 'positive'], ['food', 'positive'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Much to my satisfaction, I was seated promptly without a reservation and soon after being seated was greeted by my server."], "output": "[['reservation', 'neutral'], ['server', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Out waitress never came back to our table after taking our food orders."], "output": "[['waitress', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Diners choose between deep banquettes or seats at the bar, which offer a front-row view of the small preparation area and a chance to watch the two chefs as they whip together the elegantly constructed desserts."], "output": "[['Diners', 'positive'], ['seats', 'neutral'], ['bar', 'neutral'], ['area', 'neutral'], ['chefs', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter kept pestering us for our order even though we were among the last diners."], "output": "[['waiter', 'negative'], ['diners', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitress lost some points for not refilling our champagne glasses."], "output": "[['waitress', 'negative'], ['champagne glasses', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Tried again for Brunch and really bad server with HUGE attitude."], "output": "[['Brunch', 'positive'], ['server', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Also, try to get a seat at the main bar, because I sat at the smaller bar by the entrance and it was getting so crowded with people waiting that it became a bit unpleasant towards to end of the meal."], "output": "[['seat', 'neutral'], ['main bar', 'neutral'], ['waiting', 'negative'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitress was slow and forgot drinks and food we ordered."], "output": "[['waitress', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Fajitas, a house specialty, are available with nearly a dozen different fillings, from mesquite-grilled chicken to portobello mushrooms and asparagus."], "output": "[['fillings', 'positive'], ['chicken to portobello mushrooms', 'neutral'], ['asparagus', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had to remind the waiter to pour our wine (white) and then he didn't show us the label."], "output": "[['waiter', 'negative'], ['wine', 'neutral'], ['white', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Those of you who are sick of the standard Italian fare will be blown away by the food at Arezzo."], "output": "[['Italian fare', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The value for this place was great-- we had 2 drinks, 2 appetizers, 2 entrees, and 1 chocolate cake (yummy!!)"], "output": "[['value', 'positive'], ['drinks', 'neutral'], ['appetizers', 'neutral'], ['entrees', 'neutral'], ['chocolate cake', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Perhaps it was because the 20% tip was already added to the bill, but the waiter brought us plain gazpacho without any of the other ingredients described on the menu; later, when we complained, he brought us saucers of garnish instead of new bowls of the soup properly prepared."], "output": "[['tip', 'neutral'], ['bill', 'neutral'], ['waiter', 'negative'], ['soup', 'neutral'], ['prepared', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Even when the place has been packed with tables (I saw a party of 12 in there last time), the waiters and bartenders are still nice."], "output": "[['tables', 'neutral'], ['waiters', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the fillet minion was a little too salty and the chicken was average but the side dishes with each meat was amazing."], "output": "[['fillet minion', 'negative'], ['chicken', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When the other half of my party arrived, the waited helped us with the menu, and i was happy to know you can mix and match items in their lunch box I got the mekong box and i could not believe how great the pork sandwich was, I also enjoyed the asian salad and brownie tremendously."], "output": "[['menu', 'neutral'], ['lunch', 'neutral'], ['mekong box', 'neutral'], ['pork sandwich', 'positive'], ['asian salad', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Those who choose an omakase (chef's choice) menu will be happily surprised with accents of jalapeno or swaths of homemade sauce cleverly accenting rolls and sushi alike."], "output": "[['omakase', 'positive'], ['chef', 'neutral'], ['menu', 'positive'], ['sushi alike', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Enjoy dishes like a Maine lobster and rock shrimp BLT in a sundried-tomato tortilla wrap (Lobster Man From Mars) and a roasted pork chop with vanilla-rum mashed yams and apple chutney (Promethean Pork Chop)."], "output": "[['dishes', 'positive'], ['Maine lobster and rock shrimp', 'positive'], ['wrap', 'positive'], ['Lobster Man', 'positive'], ['apple chutney', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If only they'd get a better wine list - the reds are all so mediocre - this would be the perfect meal."], "output": "[['reds', 'negative'], ['meal', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Despite a slightly snotty server (our waitress was great) I cant wait to hop back on the L train and cruz on over."], "output": "[['server', 'negative'], ['waitress', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["$45 a head with tip for bad gnocchi, mediocre wine (as recommended by a condescending waiter, who thought himself oh-so-nice) and the feeling that our companions (at our shared table) were listening in on all our chatter."], "output": "[['wine', 'negative'], ['shared table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The decor maybe great for young kids but as an adult this place was an horrible experiance, it didn't bring the kid in me."], "output": "[['decor', 'positive'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Large portions of food to share."], "output": "[['portions', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The steak is brought to the table soaked in grease."], "output": "[['steak', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Best value is the sushi/sashimi lunch combo - get the large for double pieces on sushi!"], "output": "[['value', 'positive'], ['sushi/sashimi lunch combo', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My grandmother-in-law had a problem with her meal, and the manager AND chef came over and offered to replace it and/or take it off the check."], "output": "[['meal', 'neutral'], ['manager', 'positive'], ['chef', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although the sushi was fresh, I was disappointed with the size of the portions for the price."], "output": "[['sushi', 'positive'], ['portions', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["AVOID - there are WAY better pre-theater places, like Orso, Hell's Kitchen, etc for the same price."], "output": "[['places', 'positive'], ['Kitchen', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["You can't fault them for serving up some pretty good food, even if it's a bit overpriced."], "output": "[['serving', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This place is cheap and so much better for spending your football Sunday than the nightmarishly crowded Times Square ESPN Zone or a more trendy sports bar."], "output": "[['place', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My favorites: warm veal with goat cheese (just melts in your mouth), the gnocchi with crab meat, and for dessert - the beignets are unbelievable."], "output": "[['veal with goat cheese', 'positive'], ['gnocchi with crab meat', 'positive'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Two of us could eat a full meal with two desserts and a salad for $40."], "output": "[['meal', 'positive'], ['desserts', 'neutral'], ['salad', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Spend your time sitting on one of their couches enjoying a cocktail from the bar."], "output": "[['cocktail', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was delicious, and the menu provided ample choices which suited all of the eaters in our party from the most daring to the most conservative."], "output": "[['food', 'positive'], ['menu', 'neutral'], ['choices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["nicely decorated with cool rock and roll photos and after dinner the nightlife tends to pick up."], "output": "[['rock', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My husband had the mesclun, salmon, and ice cream and he enjoyed all 3 courses."], "output": "[['mesclun', 'neutral'], ['salmon', 'neutral'], ['ice cream', 'neutral'], ['courses', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Brunch is what Friend of a Farmer is known for, however dinner is equally impressive."], "output": "[['Brunch', 'positive'], ['dinner', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In addition to Italian staples like pasta, chicken and veal parmigiana, house specials like chicken Giovanni (chicken breast with sausage, sauteed in white wine) and linguini Giovanni (shrimp and clams in red sauce) keep the menu interesting."], "output": "[['veal parmigiana', 'neutral'], ['white wine', 'neutral'], ['linguini Giovanni', 'neutral'], ['menu interesting', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Even more impressive, when my vegetarian girlfriend started asking whether certain dishes were made with meat, the waiter offered to have a vegetable plate created for her -- and it was quite well done too."], "output": "[['dishes', 'neutral'], ['waiter', 'neutral'], ['vegetable plate', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Not ony did our waiter impose on the dessert we were trying to enjoy to take the money -- he didn't even ask us if we wanted change -- nor did he bring us back any!!!"], "output": "[['waiter', 'negative'], ['dessert', 'neutral'], ['money', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After my friend and I were seated, we were greeted by a gorgeous waitress, who helped us make our way through the large selection of choices on the menu."], "output": "[['waitress', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were not rushed at all, and the manager comped drinks at the bar so that we would vacate our table for a birthday girl who had to wait."], "output": "[['manager', 'positive'], ['drinks', 'neutral'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I expected there to be more options for tapas the food was mediocre but the service was pretty good."], "output": "[['tapas', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were able to get a table right away on Friday night, but we only saw our server twice and he failed to give us the specials, we overheard him tell the table right next to us after we had ordered and were already into our salads."], "output": "[['server', 'negative'], ['specials', 'neutral'], ['salads', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The oil is changed frequently, and the food never tastes TOO HEAVY."], "output": "[['oil', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were hassled about seating by our waiter who seemed at the end of his pony-tail, so we opted for the bar, quaintly decorated with giant fly strips."], "output": "[['waiter', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Pizza is supposed to have an extremely thin crust, and a sauce which is actually made of crushed tomatoes instead of tomato paste."], "output": "[['crust', 'positive'], ['tomato paste', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["One thing that is great is there is a pitcher of water at each table, great for people who can't handle the spices."], "output": "[['water', 'positive'], ['spices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The filet was NOT on the menu, but my friend had the bouillabaisse, which he found delicious."], "output": "[['menu', 'neutral'], ['bouillabaisse', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I agree that the wait staff wasn't very friendly, but the service was adequate and our food arrived without too much of a wait."], "output": "[['wait staff', 'negative'], ['service', 'positive'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I highly suggest you make reservations, as wait times can be extremely long."], "output": "[['reservations', 'neutral'], ['wait', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our server was just fantastic, she recommended that we order a lot of different dishes, so we did, we tried almost everything on the menu, we were a party of six and the whole group enjoyed everything."], "output": "[['dishes', 'positive'], ['menu', 'neutral'], ['server', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Management had always been rude, but without the great staff as a buffer, Jesse's is just another pubby place with poor decor and average food."], "output": "[['Management', 'negative'], ['decor', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Theme and actors are kinda cool but you are charged some entertainment fee on top of the expensive food and drinks."], "output": "[['actors', 'positive'], ['food', 'negative'], ['drinks', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the specials were excellent, everything was delicious down to the olive oil they serve when you sit down."], "output": "[['specials', 'positive'], ['olive oil', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The white tablecloths covering closely-packed, old wood tables; waitresses with accents and up-turned noses; warm firelight ambience; boisterous crowds drinking wine -- it's all here."], "output": "[['waitresses', 'neutral'], ['crowds drinking wine', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After leaving the traditional 15% tip, the waiter ran after us for half a block to confront."], "output": "[['tip', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Dominic will give you the ambience of the old times when they were all immigrants and good food was equivalent of good friends and unforgettable times."], "output": "[['ambience', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiters, all wearing black suits, are serious, courteous, and knowledgeable; the dining rooms are ornate and convivial, with large parties celebrating various things interspersed with dressed-up couples on dates."], "output": "[['waiters', 'negative'], ['suits', 'neutral'], ['parties', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["true I had to wait longer for my table, but the ambience and the food definitely made up for it."], "output": "[['table', 'neutral'], ['ambience', 'positive'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["from the legendary Big Mac to new and exciting menu items like Chicken Parm and the Big Extra Mickey D's is always expanding their menu!"], "output": "[['legendary Big Mac', 'neutral'], ['menu items', 'positive'], ['Chicken Parm', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Their version of chicken tikka masala tastes nothing like what it should- it's basically chunks of chicken with stewed tomatoes, and of course, half of the dish is cilantro."], "output": "[['chicken tikka masala', 'negative'], ['chicken with stewed tomatoes', 'neutral'], ['dish', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Well I can't tell you how the food was because the moment we walked in, the single waiter was extremely rude and told us to wait outside while he cleared a table (in the middle of winter) because he was busy."], "output": "[['food', 'neutral'], ['single waiter', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["(And the mixed steamed seafood appetizer took *forever* to arrive -- apparently the oysters here are shucked by machine, and they only have one shucker, so if more than one table orders anything off of that section of the menu, you'll be waiting a while."], "output": "[['mixed steamed seafood appetizer', 'negative'], ['oysters', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We got the tasting menu($100 for two), which was a selection of the signature dishes."], "output": "[['menu', 'positive'], ['dishes', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went there for brunch, I hated this place : Incompetent service, cold food (even if I dont think it could have been better warm), flat soda."], "output": "[['brunch', 'neutral'], ['service', 'negative'], ['cold food', 'negative'], ['soda', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After being sat for dinner, we enjoyed the fresh bread and butter before the salad and main course."], "output": "[['dinner', 'neutral'], ['bread', 'positive'], ['butter', 'positive'], ['salad', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["But the waiter was very accomodating; he brought extra garlic bread at no charge, was attentive, and apologized profusely for not allowing us to order from the 12-and-under kids' menu."], "output": "[['waiter', 'positive'], ['garlic bread', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitress had an ongoing diatribe with a waiter the whole time she served us-it was ALL BAD!!"], "output": "[['waitress', 'neutral'], ['waiter', 'neutral'], ['served', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food The owners' visits to farmers' markets in Brooklyn drive the ingredient-centric New American menu, which changes about once a month."], "output": "[['owners', 'neutral'], ['New American menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Standouts among appetizers include hypnotically aromatic laska, a Southeast Asian soup; a trio of smoky seared scallops atop a mix of chili sauce and creme fraiche; and seared rare kangaroo served with a bright green, sweet-hot pepper relish."], "output": "[['appetizers', 'neutral'], ['seared scallops atop', 'positive'], ['mix of chili sauce and creme fraiche', 'positive'], ['green', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The staff knows all about the food and the Chef is very visible visiting tables and overseeing the dining room."], "output": "[['staff', 'positive'], ['food', 'neutral'], ['Chef', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["when the wine is the best thing at dinner, its not a good thing."], "output": "[['wine', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My friend was looking forward to her favorite dish on the menu had made reservations for the 14 of us a few weeks beforehand."], "output": "[['dish', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I organized a dinner for 20 and was extremely satisfied with the results."], "output": "[['dinner', 'neutral'], ['results', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A friend and I went for dinner, the host was rude to us as we walked in, we stayed because the decor is charming and we wanted french food."], "output": "[['dinner', 'neutral'], ['decor', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Whole roasted branzino, a well-charred rib eye steak and roast suckling pig are typical dinner entrees."], "output": "[['roasted branzino', 'neutral'], ['well-charred rib', 'neutral'], ['roast suckling pig', 'neutral'], ['dinner entrees', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We went to the Sunday brunch, and were pleasantly surprised to find a jazz combo there."], "output": "[['Sunday brunch', 'neutral'], ['jazz', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had some sorta of kobe sashimi salad with coconut shavings which was phenomenol and a lobster ravioli."], "output": "[['kobe sashimi salad with coconut shavings', 'positive'], ['lobster ravioli', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Come here to drink, but don't come here for a meal."], "output": "[['drink', 'negative'], ['meal', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The place was busy and had a bohemian feel."], "output": "[['place', 'negative'], ['feel', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The high prices and small portions reflect the hype of a new Battali restaurant as well as the cache that comes with having to make a reservation a week in advance only to wait to be seated."], "output": "[['prices', 'negative'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Their Billy-Cheese steak sandwich is very good, too, but last I was there it wasn't on the menu, at least not for dinner anyway."], "output": "[['Billy-Cheese steak sandwich', 'negative'], ['menu', 'neutral'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere is certainly unlike any other restaurant in all of Manhattan, but it is a pity that the food does not live up to the decor."], "output": "[['atmosphere', 'positive'], ['food', 'negative'], ['decor', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The place is small, but loaded with plenty of goodies that range from Italian inspired treats to Greek pastries all well prepared."], "output": "[['place', 'negative'], ['Greek pastries', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went with a friend from out the town - the best thing on the menu was the Veal."], "output": "[['menu', 'neutral'], ['Veal', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had lunch with 3 friends of mine, all ordered different pasta dishes and we all loved each of ours!"], "output": "[['lunch', 'neutral'], ['pasta dishes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the COOKED STUFF were OVERCOOKED, the lobster tail was DRY, and CRAB melted in your mouth like mashed potatoes, the salads and dessert looked like they were lunchtime leftovers."], "output": "[['lobster tail', 'negative'], ['CRAB', 'negative'], ['mashed potatoes', 'neutral'], ['salads', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Portions are small, they try to pass themselves off as family style by encouraging sharing and putting dishes in the center of the table, but it is glorified a la carte."], "output": "[['Portions', 'negative'], ['table', 'neutral'], ['carte', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our wine was not brought out until AFTER our entree was served."], "output": "[['wine', 'negative'], ['entree', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter was conspicuously eyeing our table the entire meal and there was a lot of scurrying by the wait staff in general."], "output": "[['waiter', 'negative'], ['table', 'neutral'], ['meal', 'neutral'], ['wait staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I sometimes go here when in the area and though the food is always great, the Basil Chicken and Shrimp Tempura roll in particular, the service has much to be desired."], "output": "[['food', 'positive'], ['Basil Chicken and Shrimp Tempura roll', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter's recommendation for the entree (seabass in a lime and mango chutney) exceeded our expectations and we ate the chutney to the last drop."], "output": "[['waiter', 'positive'], ['lime and mango chutney', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The fondue was good, but not worth the very expensive price tag."], "output": "[['fondue', 'positive'], ['price tag', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Not 5 minutes passed before the server actually tapped us on the shoulder and, I swear to god, ASKED US TO LEAVE because they had a reservation."], "output": "[['server', 'negative'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For appetizer I order the Pasteis filled with Goat cheese Toasted Pinenuts."], "output": "[['appetizer', 'neutral'], ['Pasteis filled with Goat cheese Toasted Pinenuts', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Everything I have had just tasted like salt-not garlic,not cheese,salt-only thing i can figure is that since they churn it out in such quantity the quality's gotta suffer, wouldnt go back unless dragged or for a drink."], "output": "[['salt-not garlic', 'neutral'], ['cheese', 'negative'], ['quality', 'negative'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A few times at the bar I felt as though the Sushi chef an older gentleman was laughing at me and my girlfriend."], "output": "[['bar', 'neutral'], ['gentleman', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The decor was pleasant, but the tables were way too much crowded for a restaurant of this presumptive caliber."], "output": "[['decor', 'positive'], ['tables', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Everything that could go wrong did starting with the set menu that I was not informed of at the time of the reservation, to trying to seat us 45 minutes late at a table that was not made up."], "output": "[['menu', 'neutral'], ['reservation', 'neutral'], ['table', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I like pad thai shrimp and shrimp tempura roll ,for dessert just try banana rum."], "output": "[['pad thai shrimp and shrimp tempura roll', 'positive'], ['dessert', 'neutral'], ['rum', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["However, the drinks are very good and this place is alright for brunch, if you don't mind sitting in a very cramped spot and/or waiting on line."], "output": "[['drinks', 'positive'], ['brunch', 'positive'], ['spot', 'negative'], ['waiting', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our appetizers came out the same time as our entree and our waitress disappeared quite frequently."], "output": "[['appetizers', 'neutral'], ['entree', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["this place was ok I guess since they have karaoke goin' on with a free shot if you sing."], "output": "[['place', 'negative'], ['goin', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Desserts include a sweet masala chai and keer, and cardamom- and saffron-flavored rice pudding."], "output": "[['Desserts', 'neutral'], ['sweet masala chai', 'neutral'], ['rice pudding', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the steak and chicken fajitahs were good, a bit too much sauce on the meat for my taste."], "output": "[['chicken fajitahs', 'positive'], ['sauce', 'negative'], ['meat', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Evidently, our waiter went to the Mediterrean for our humus pita because it took about 25 minutes."], "output": "[['waiter', 'negative'], ['humus pita', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I took my boyfriend there for his birthday, he got the biggest single serve steak available, we each had an appetizer, i had a glass of wine and the meal cost about $110, which is good for a great NYC resturant."], "output": "[['single serve steak', 'positive'], ['appetizer', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Let me count the problems: music so loud it hurt, sticky unclean tables, the waitress took a long time to take our order, and then didn't bring a glass for the beer."], "output": "[['music', 'negative'], ['tables', 'negative'], ['waitress', 'negative'], ['glass', 'neutral'], ['beer', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We ended our great experience by having Gulab Jamun (dessert) recommended by the waiter."], "output": "[['Gulab Jamun (dessert)', 'positive'], ['waiter', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My mother and I had our chairs bumped over a dozen times by hasty waiters."], "output": "[['chairs', 'neutral'], ['waiters', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The appetizers are really pricey particularly once you see the size (or lack thereof)."], "output": "[['appetizers', 'negative'], ['size', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Clever decor with lower false ceiling to distinguish the bar area."], "output": "[['ceiling', 'positive'], ['bar area', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My group and I cancelled whatever drinks we ordered (no food order since there was NO wait staff) and left."], "output": "[['drinks', 'neutral'], ['wait staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Guacamole+shrimp appetizer was really great, we both had the filet, very good, didn't much like the frites that came with, but the filet was so good, neither of us cared."], "output": "[['Guacamole+shrimp appetizer', 'positive'], ['frites', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Finally, the manager had the audacity to lock the doors, presumably to prevent us from skipping out on the bill, while one of our friends went to an ATM to get cash."], "output": "[['manager', 'negative'], ['doors', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["THe ribs are good and I havent had anything on the menu that did taste great."], "output": "[['ribs', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My tuna tatare was laden with salt and soy sauce - tasted like cheap chinese instead of great fish."], "output": "[['tuna tatare', 'neutral'], ['salt', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The pad thai has a nutty, mild flavor and can be ordered with chicken, shrimp, crab, lobster or tofu, or combinations thereof."], "output": "[['pad thai', 'positive'], ['chicken', 'neutral'], ['lobster or tofu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were on a table of 6, and loved the food,the Portugues salmon and the sirloin steak with cream sauce were loved by everyone, the apetizers were a bit too small for he price they charge."], "output": "[['food', 'positive'], ['Portugues salmon', 'positive'], ['apetizers', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When we confronted the hostess, she told us that there were 3 of them and only 2 of us, and that the 3 women had a reservation at 8:30pm."], "output": "[['hostess', 'negative'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I love to go there on weekends and have the delicious french toast (made from baguette slices) or the granola with fresh fruit, sometimes I am so torn that I end up getting both!"], "output": "[['french toast', 'positive'], ['slices', 'neutral'], ['granola', 'neutral'], ['fruit', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["At one point, the waiter told us that he couldn't find our wine!"], "output": "[['waiter', 'negative'], ['wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["(We did make reservations, since we had a group of 8, but had a short wait when arriving a little early."], "output": "[['reservations', 'neutral'], ['wait', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu was small, but the food delicious."], "output": "[['menu', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For appetizers try vegetable samosas and chicken wings."], "output": "[['appetizers', 'neutral'], ['vegetable samosas', 'positive'], ['chicken wings', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We tried to get the manager who flatly refused to come to our table and discuss the problem with us."], "output": "[['manager', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The owner has taken over three dining tables for her computer, adding machine, phone and assorted and untidy papers."], "output": "[['dining tables', 'neutral'], ['papers', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Though the wait may be long because they only have 16 tables it is worth it, and it seems to go by fast after a drink or two at the bar."], "output": "[['wait', 'negative'], ['tables', 'neutral'], ['drink', 'neutral'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The drinks are just as expensive as the chain coffee houses."], "output": "[['drinks', 'negative'], ['coffee houses', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A waiter looked me in the eye and said we did not order wine, as if to infer we were making this up."], "output": "[['waiter', 'negative'], ['wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were charged for the missing appetizer and when I complained to the manager, who never thought to apologize, he blamed the kitchen."], "output": "[['missing appetizer', 'neutral'], ['manager', 'negative'], ['kitchen', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["However, the service has SIGNIFICANTLY declined since they expanded into the back room."], "output": "[['service', 'negative'], ['room', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The pancakes I ordered were nothing like the menu's description."], "output": "[['pancakes', 'negative'], ['menu', 'neutral'], ['description', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The place was a bit busy when I got there so we ate at the bar."], "output": "[['place', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The best dish out of our 3 mains: quail with figs (also had the rabbit chicken), I suggest ordering a few plates to share as one would normally do with tapas."], "output": "[['rabbit chicken', 'neutral'], ['tapas', 'neutral'], ['dish', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Both times I sat in the lounge area which is very appealing, but right in front of the bar, which explains my frustration for being ignored while dropping a lot of money for decent food and wine."], "output": "[['lounge area', 'positive'], ['bar', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After ordering drinks, we both decided on the Paella Vallenciana, brought out on hot plates."], "output": "[['Paella Vallenciana', 'neutral'], ['plates', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Very pleasant looking bar area and a lounge area with free pool."], "output": "[['bar area', 'positive'], ['lounge area', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The bar gets out of control busy due to it's proximity to Fordham University--but the Fordham kids are cool, so it's alright!"], "output": "[['bar', 'neutral'], ['Fordham kids', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After reading all the reviews here and many glowing recommendations on food blogs, I thought I MUST try this pizza!"], "output": "[['food', 'neutral'], ['pizza', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Among us, we ordered a large sampling of the menu, and everyone thoroughly enjoyed their meal."], "output": "[['menu', 'neutral'], ['meal', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My group got charged an outrageuos $63/person for a family-style dinner, including a 23% tip added for the horrible service."], "output": "[['family-style dinner', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were told by the front door hostess since we didn't have a reservation, it would be about 45mins for a table, but we could wait at the lounge and they would get us when our table was ready."], "output": "[['front door hostess', 'negative'], ['reservation', 'neutral'], ['lounge', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Apart from the rare to medium rare mistake on my steak, the food was ok and and not worth the money."], "output": "[['steak', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The prixe fix menu was a deal to boost downtown restaurants, atleast we didn't pay the full price."], "output": "[['menu', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["And the service is unbearable - I waited for ages to get my drink, got the wrong sushi order, and had my appetizer whisked away prematurely."], "output": "[['service', 'negative'], ['drink', 'neutral'], ['appetizer', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There is a huge line, usually a 45 minute wait; they take no reservations and no tables of more than five people."], "output": "[['wait', 'neutral'], ['reservations', 'negative'], ['tables', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiters do not pay any attention to the customers, instead sit at the bar and watch TV."], "output": "[['waiters', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the pre dinner drink at the bar was very pleasant, good start, although we waited up to about an hour before our table was ready."], "output": "[['pre dinner drink', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu is pricey and the food was not tasty - except for the tostones with garlic and oil."], "output": "[['menu', 'negative'], ['tostones', 'positive'], ['garlic', 'neutral'], ['oil', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My boyfriend took me to dinner for an early Valentine's Day, we showed up early for our reservation to meet an incredibly rude host who told us the bar was full, to just wait behind a rope."], "output": "[['reservation', 'neutral'], ['bar', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["for dessert , you can't go wrong with the buttermilk panacotta with rhubarb compote, or the righteous cheesecake."], "output": "[['dessert', 'neutral'], ['cheesecake', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Ok, it's not greasy steak and juicy burger good, but it's a light healthy fare, if you are into that kind of stuff."], "output": "[['fare', 'positive'], ['stuff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When there are ten open tables in a room, the hostess insisted on seating peopl on top of each other."], "output": "[['hostess', 'negative'], ['seating', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For the prices, the food is decidedly lackluster, and the service, unless you are a regular, can be quite rude."], "output": "[['prices', 'neutral'], ['food', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We happen to walk by, read the menu posted outside they offered a nice selection ranging from citrus salmon, pan seared trout, chicken pot pie, sirlion steak, the fried calamari is out of this world they use a secret ingredient to their dipping sauce."], "output": "[['menu', 'neutral'], ['selection', 'positive'], ['salmon', 'neutral'], ['pan', 'neutral'], ['chicken pot pie', 'neutral'], ['steak', 'neutral'], ['fried calamari', 'positive'], ['dipping sauce', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The store has a great atmosphere amd amazing staff who are always there to help if its a cup of coffee or a nice chat."], "output": "[['atmosphere', 'positive'], ['staff', 'positive'], ['cup of coffee', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They did a great job on the decor but it seems that the food has gotten a bit less in the quality department, as well as in the portion size!"], "output": "[['decor', 'positive'], ['food', 'negative'], ['portion size', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had dinner with my friend, and regardless of our $100 check, I overheard the waiter say that we had been there too long."], "output": "[['dinner', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The prices have gone up and some of good old standby entrees have disappeared from the menu."], "output": "[['entrees', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food Crispy flatbreads and excellent olive oil start the meal, but save room--chef-owner Rocco Sacramone's abbondanza means you'll be going home with doggie bags."], "output": "[['Food', 'positive'], ['olive oil', 'positive'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We asked the waitress very nicely to please change the playlist to something more appropriate for dinner, she chuckled to herself and said sure but never changed it."], "output": "[['waitress', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We went for lunch on Saturday, wait wasn't bad considering that it had only opened recently."], "output": "[['lunch', 'neutral'], ['wait', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The complimentary desssert with the Greek coffee knocked my socks off!"], "output": "[['desssert', 'positive'], ['Greek coffee', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I stopped in here for a pre-theater dinner, and I must say I was very happy with my meal."], "output": "[['pre-theater dinner', 'neutral'], ['meal', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["People were leaving because they had been waiting for hours, however we decided to stay and have a complimentary drink at the bar which was absoloutely beautiful along with the view, the only plus."], "output": "[['waiting', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["As the waitress cleaned the table in a rush she knocked over a party bag containing a glass bottle with bath oil."], "output": "[['waitress', 'negative'], ['table', 'neutral'], ['glass bottle', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Between the 6 of us we tried almost everything on the menu and we were all very pleased with our meals."], "output": "[['menu', 'neutral'], ['meals', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Since the menu is not organized in the way to describe the size of each dish, and there is no omakase nor a course, waiter's recommendation may be crucial to decide what to order, but he just recommended what he likes without considering appropriate amount for one person, and even served shellfish to whom who had mentioned she is allergic to shellfish!"], "output": "[['menu', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Even though it wasn't totally full, the waitress had to RUN around the restaurant, and the drinks and the food took a LONG time to arrive."], "output": "[['waitress', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Showed up last Sunday night with girlfriends and no reservation, host was very helpful finding us a seats at bar after short wait."], "output": "[['host', 'positive'], ['bar', 'neutral'], ['wait', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["As to the fact that everyone else's sushi looked better: the waitresses are not responsible for offering you what is CLEARLY written on the menu as Omakase - Chef's Choice."], "output": "[['sushi', 'positive'], ['waitresses', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The only bad thing was that the third alien was so friendly and took a lot of time at the other tables, so she didn't come see us."], "output": "[['alien', 'positive'], ['tables', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We received our food and coffee at the same time, and couldn't get the attention of any waiter to refill our cups."], "output": "[['food', 'neutral'], ['coffee', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["i love this pizza, its not greasy or filled with mounds of cheese, its just fresh tomatoes basil and buffalo mozz."], "output": "[['pizza', 'positive'], ['mounds', 'neutral'], ['tomatoes basil', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We tried explaining nicely to them that we were just finishing up a drink, and after a brief, unprofessional discussion with the two waiters, they told us never to come back again."], "output": "[['drink', 'neutral'], ['waiters', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["my date's non veg thali was really expensive and had like one or two pieces of meat in each sauce."], "output": "[['thali', 'negative'], ['meat', 'neutral'], ['sauce', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We fully relied on our very capable waiter for choices of the menu and we were not disappointed."], "output": "[['waiter', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There were many helpful people, not only one waiter - kept refilling the water, the wine, asking if everything was okay."], "output": "[['waiter', 'positive'], ['wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Also lovely was the atmosphere; the high ceilings and spacious room make it a nice contrast from the other brunch mills on the upper west side."], "output": "[['atmosphere', 'positive'], ['brunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was so-so and you would think it was a french resturant, the portions were so tiny."], "output": "[['food', 'neutral'], ['portions', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For lunch I had the Carnitas de Puercos (pork tacos), which was a bit bland and the portions are kind of small dont expect to chow down."], "output": "[['lunch', 'neutral'], ['Carnitas de Puercos (pork tacos)', 'negative'], ['portions', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["), we were not given bread though the couple next to us was, we asked twice for our check and when it came, they forced us to pay the tip in cash so they could get out of paying taxes!"], "output": "[['bread', 'negative'], ['tip', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["At one point I noticed the grime on the mustard bottle and asked the waitress for a clean one."], "output": "[['bottle', 'negative'], ['waitress', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["if you don't mind slow service and limited selections on the menu occasionally, then you might consider dining there."], "output": "[['service', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the regular prices looked pretty expensive (~$15 per appetizer, ~$35 per entre) so the restaurant week menu (at $35pp) seemed like a sweet deal."], "output": "[['prices', 'negative'], ['appetizer', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Best Baked Ziti in the area, great classic NY pizza."], "output": "[['Baked Ziti', 'positive'], ['area', 'neutral'], ['NY pizza', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service may be a little slow (what can you expect in this laid back atmosphere), but a Sunday brunch is a rewarding experience."], "output": "[['service', 'negative'], ['brunch', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Husband and Wife owners are always pleasent and accomidating, food is top notch quality made with care, and now, recently renovated to accomidate more tables and a young fresh feel."], "output": "[['owners', 'positive'], ['food', 'positive'], ['tables', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Even with reservations, checking in, and a generally quiet night, the hostess forgot that we were there and gave our table to her friends."], "output": "[['reservations', 'neutral'], ['hostess', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After having the table cleared and recieving fresh warm plates, we shared the Chicken Tikka Masala and the Chicken and Lentils."], "output": "[['table', 'neutral'], ['plates', 'positive'], ['Chicken Tikka Masala', 'neutral'], ['Lentils', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The tasting menu experience lasted close to three hours and included six or seven food courses and three desert courses."], "output": "[['menu', 'positive'], ['food courses', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Stumbled unto this little gem early one saturday afternoon and was thoroughly pleased with the wonderful little backyard."], "output": "[['afternoon', 'neutral'], ['backyard', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["South American additions to the menu, like perfectly fried green plantains and garlicky pork, are uniformly successful."], "output": "[['menu', 'neutral'], ['fried green plantains', 'positive'], ['pork', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food The fare is mostly traditional, with a few contemporary specials offered nightly."], "output": "[['Food', 'positive'], ['fare', 'positive'], ['specials', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A typical old New York steak-house atmosphere - no ambience, comfort or class, but some of the best steak you will ever have."], "output": "[['atmosphere', 'positive'], ['ambience', 'negative'], ['comfort', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Great romantic place for a date (try to get the corner booth table for a little privacy and to sit close!"], "output": "[['place', 'positive'], ['corner booth table', 'positive'], ['privacy', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were served by two very rude waitresses who slammed every glass and dish they brought onto the table, and then got so caught up by hanging out at the bar that I eventually had to hunt them down to pay my bill."], "output": "[['waitresses', 'negative'], ['dish', 'neutral'], ['table', 'neutral'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A freind invited me for lunch at Home because he said they have the best hamburgers."], "output": "[['lunch', 'neutral'], ['hamburgers', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It is not a very stylish place, but we had some of the best Chinese food we ever had."], "output": "[['place', 'negative'], ['Chinese food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The ingredients are fabulously fresh and the pizza's well-prepared -- but the crust doesn't match up to John's."], "output": "[['ingredients', 'positive'], ['pizza', 'positive'], ['crust', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In the front bar, boisterous neighbors and friends share bottles of wine; the large dining room, with its lovely painted ceiling and oversized portrait of a portly chef, is the destination for serious eating."], "output": "[['bar', 'neutral'], ['wine', 'neutral'], ['painted ceiling', 'positive'], ['chef', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After each of them had had one drink, one of the managers came up to our table and told us that he no longer felt comfortable serving us any more margaritas."], "output": "[['drink', 'neutral'], ['managers', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food There's something for fish fans of every stripe on the lengthy menu."], "output": "[['Food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Ask for the cocktail menu it has a plenty selection of drinks."], "output": "[['cocktail menu', 'neutral'], ['drinks', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service was very good, although the food was mediocre."], "output": "[['service', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Had dinner here this past Friday night with some friends and Salmon River definitely did not disappointment."], "output": "[['dinner', 'neutral'], ['Salmon', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["People at the next table were complaining how horrible their house wine was."], "output": "[['table', 'neutral'], ['wine', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Even though the food was prepared nicely, it was definitely lacking flavor."], "output": "[['food', 'positive'], ['flavor', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["However, we were never served bread with our meals and the restaurant is too crowded."], "output": "[['served bread', 'negative'], ['meals', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Yes, hard not to look at the waitresses (and they're really good servers), but as I'm reminded by everyone who knows Hooters, they don't rank anywhere near the girls at the Hooters locations South of the ol' Mason-Dixon."], "output": "[['servers', 'positive'], ['Mason-Dixon', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Cute decor, but rather small so the dining room can get very smoky if the bar is crowded."], "output": "[['decor', 'positive'], ['dining room', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Customers choose flavors like sweet cream, cake batter or banana, add mix-ins--ranging from candy bar chunks and Gummi bears to hot fudge and peanut butter--then servers mash it all together on a frozen slab of granite."], "output": "[['sweet cream', 'neutral'], ['cake batter', 'neutral'], ['banana', 'neutral'], ['servers', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Knock off 15-20% of the prices and you have a decent night out."], "output": "[['prices', 'neutral'], ['out', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["(must try the fois gras appetizer and chocolate milkshake for dessert."], "output": "[['fois gras appetizer', 'positive'], ['chocolate milkshake', 'positive'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I am an extremely low maintenance diner and the staff at this restaurant managed to insult my dinner party and refuse kitchen service minutes after seating us and informing us that the kitchen was open."], "output": "[['diner', 'negative'], ['dinner', 'neutral'], ['seating', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Overall, I good place to take a date or have a small group of friends for dinner."], "output": "[['place', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were seated promptly there were a few people waiting in the bar, but had ordered quickly been at the table less than 45 mins."], "output": "[['seated', 'positive'], ['waiting', 'neutral'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["' When I reasoned with them that my dining partner already received her hot entree and was halfway done eating, and all I ordered was two rolls, the wait staff finally got the idea that maybe they should be trying to get me my order."], "output": "[['dining', 'neutral'], ['entree', 'neutral'], ['wait staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The salad looked as though they have a premixed trash bag full of it, and they just dump a heap of it on a plate."], "output": "[['salad', 'neutral'], ['premixed', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The red Borsht provides a hearty meal for $1."], "output": "[['red Borsht', 'neutral'], ['meal', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The margaritas took me on an instant vacation, and although there was a bit of a wait for a table, the food was well worth it."], "output": "[['margaritas', 'neutral'], ['wait', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Don't forget to get quacamole made at your table (it's $10 extra) I told the waitress it was my cousin's birthday and they brought out a cake and the mariachi band played at our table."], "output": "[['waitress', 'positive'], ['band', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The other dish was arroz con pollo, the chicken was delicions and the rice was a greasy but good."], "output": "[['dish', 'neutral'], ['chicken', 'positive'], ['rice', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I met five of my friends for dinner at Blockheads last Friday night and had a good time."], "output": "[['dinner', 'neutral'], ['time', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Dylan Prime is one of an increasingly small number of restaurants in NYC that take reservations for large groups."], "output": "[['Dylan', 'positive'], ['reservations', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["on the food-front while adding just enough of a civilized atmosphere where you won't worry about either your neighbor or the wait staff biting off one of your fingers."], "output": "[['atmosphere', 'positive'], ['wait staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They need to expand the menu some, and offer additional toppings for the pizza."], "output": "[['menu', 'neutral'], ['toppings', 'positive'], ['pizza', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Get the pepperoni - YUM - and a family style salad."], "output": "[['pepperoni', 'positive'], ['family style salad', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had a very nice and entertaining waitress who was very much on top of our table."], "output": "[['waitress', 'positive'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Lousy, hard as a rock home made potato chips that could slice a tomato as well as a soda can."], "output": "[['rock', 'negative'], ['soda can', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["), the BBQ salmon was good if not a bit too salty from the heavy miso."], "output": "[['BBQ salmon', 'positive'], ['miso', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Along with the regular items on the menus, they also offer some wonderful specials--and if an item is not on a menu, they always do their best to accommodate."], "output": "[['regular items', 'neutral'], ['specials', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Two curiosities: on my last two visits, the salad's lettuce had clearly seen better days, and on my last visit, I was told that I couldn't have coffee at the end of the meal (we were asked to go next door!)"], "output": "[[\"salad's lettuce\", 'positive'], ['coffee', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They might be all business at the counter when you give your order, but their food says I love you."], "output": "[['counter', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["was yelling at the rest of the waitstaff audibly enough that I was able to follow his entire tirade from where I sat in the secondary dining room."], "output": "[['waitstaff', 'negative'], ['dining room', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Went here for a casual Sunday night dinner at 7:45pm; dinner was served at 10:15pm!"], "output": "[['Sunday', 'neutral'], ['served', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I ordered a thin-crust individual meat pizza which was big enough for two and my companion ordered pasta with pesto."], "output": "[['thin-crust individual meat pizza', 'positive'], ['pasta with pesto', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For fun on the run, sip a mojito at the bar while a portrait of the Virgin Mary bizarrely watches over you."], "output": "[['mojito', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The red sauce had no flavor, the cheese lacked that fresh quality cheese taste you expect from a well-known pizzaria, and the slice overall was really dry."], "output": "[['red sauce', 'neutral'], ['flavor', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although the food was in small portions, it was good."], "output": "[['food', 'positive'], ['portions', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They need to change the overall decor if they want to get a serious dinner crowd though."], "output": "[['decor', 'neutral'], ['dinner', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["On the menu board posted outside - they got Passion Fruit Creme Brule."], "output": "[['menu', 'neutral'], ['Fruit Creme Brule', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you live downtown, definitely grab one of their menus, make a phone call and relax in front of the tv while they pound the pavement to get to you (although they do take about 45 minutes on average to get to you)-- the in restaurant service is likewise very very good."], "output": "[['menus', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Service was slow and spotty; had to flag the waiter down many a time to get drink and food orders in."], "output": "[['Service', 'negative'], ['waiter', 'negative'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you want a quiet dinner don't show up late, cuz the atmosphere gets louder and more loungy as the nite goes on."], "output": "[['dinner', 'positive'], ['atmosphere', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had the lobster ravioli--good size portion with a delicious vodka cream sauce."], "output": "[['lobster ravioli', 'neutral'], ['vodka cream sauce', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the waitress never asked us how the food was or if we needed anything."], "output": "[['waitress', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food, however, is completely uninteresting - my special of the day pasta was decent, but definitely not worth the money, the wine wasn't particularly spectacular, and the bread."], "output": "[['food', 'negative'], ['day pasta', 'positive'], ['wine', 'negative'], ['bread', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was OK at best, and if you don't LOVE cheese don't even consider going here."], "output": "[['food', 'neutral'], ['cheese', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Sit at the bar (no reservations necessary), eat, talk to the bartender, and enjoy, b/c come dinnertime you will pay quadruple the price (but it's still worth it)."], "output": "[['reservations', 'neutral'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I've had Gnocchi from the Bronx to Coney Island and this place is, hands down, the best."], "output": "[['Gnocchi', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Did not get to dessert as it took a while to get the server's attention and we had a show to get to."], "output": "[['dessert', 'neutral'], ['server', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["To the amusement of our server, I wrote everything down, lest I forget a single morsel (about 21 different dishes)."], "output": "[['server', 'positive'], ['dishes', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Man, that chicken (in some kind of spicy soup) was yummy!"], "output": "[['chicken', 'positive'], ['spicy soup', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Besides ordering single dishes you can also order family style."], "output": "[['single dishes', 'neutral'], ['style', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The owners couldn't have been more accomodating -- we had the entire restaurant to ourselves on a Saturday (before it opens to the public for dinner)."], "output": "[['owners', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service was autrocious in fact my order came out wrong and our wine was never repoured throughout the entire dinner, which lasted 3 hours."], "output": "[['service', 'negative'], ['wine', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Place was okay, the food was definitely not worth the money, however the appetizers were good, we had the jumbo shrimp and oysters."], "output": "[['Place', 'positive'], ['food', 'negative'], ['appetizers', 'positive'], ['shrimp', 'neutral'], ['oysters', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service was a bit inadequate-and be warned they bring your food as it is ready- so be sure to order apps then after being served order entrees."], "output": "[['service', 'negative'], ['food', 'neutral'], ['entrees', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Ten minutes later: no burgers and no sign of our waiter."], "output": "[['burgers', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For the high price you would pay (dinner for the two could run $80), you sure do get alot."], "output": "[['price', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While I liked the place, I'd never come back in a weekend night again, and with reservations."], "output": "[['place', 'positive'], ['reservations', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Then the food came- TINY portions and plates came out in 15 min intervals."], "output": "[['food', 'neutral'], ['portions', 'negative'], ['plates', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We both had habtchi, a bottle of plum wine, and 3 appetizer, the food was great, and I really didnt find the wait to be that long like some the other review said."], "output": "[['bottle of plum wine', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the pasta I had for lunch was $12, but my dessert, which was a small slice of apple pie, was $10!"], "output": "[['pasta', 'neutral'], ['lunch', 'neutral'], ['apple pie', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The jukebox is always playing good tunes, and the patrons are never shy about getting up and dancing in the aisles, or even on the bar."], "output": "[['jukebox', 'positive'], ['patrons', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["(So long that it prevented me from increasing their sales by getting more possible drinks) If i just saw my one waiter the whole night I would have known who to talk too."], "output": "[['sales', 'neutral'], ['drinks', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I liked the beer selection!"], "output": "[['beer selection', 'positive'], ['beer s', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Your drink is at your fingertips and you don't have to wait for the waitress to come back with your cocktail."], "output": "[['drink', 'neutral'], ['waitress', 'negative'], ['cocktail', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were seated promptly for a Saturday lunch, but service was incredibly slow."], "output": "[['Saturday lunch', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They don't load their pizza down with tons of cheese nor is it dripping with sauce."], "output": "[['cheese', 'positive'], ['sauce', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had to stare out waitress down to get our check and also we were charge."], "output": "[['waitress', 'negative'], ['check', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The hostess did offer free drinks to my party due to the wait, but we were more interested in eating after said long wait."], "output": "[['hostess', 'positive'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Sure, the hostess can be rude, but when in the mood for authentic Mexican food, there is no better place in NYC, yet."], "output": "[['hostess', 'negative'], ['Mexican food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Servers are layed back, but food arrives rapidly."], "output": "[['Servers', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had a few toro and white tuna sashimi as well as a couple roll like the park avenue (which was not listed on the menu but recommended by the waiter) and the paris match roll."], "output": "[['menu', 'neutral'], ['waiter', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food The daily-changing menu, scrawled on large dry-erase boards, offers a blend of haute cuisine and Texas roadhouse fare."], "output": "[['Food', 'neutral'], ['daily-changing menu', 'neutral'], ['cuisine', 'positive'], ['fare', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Nice family place, nice atmosphere, but don't go there for pizza."], "output": "[['family place', 'positive'], ['atmosphere', 'positive'], ['pizza', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food and the value had been ok on our meal, and then after only a little more than an hour, the check was slipped onto the table for our large party, and a few minutes later, waiters began yelling at us to leave."], "output": "[['food', 'positive'], ['meal', 'neutral'], ['table', 'neutral'], ['waiters', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["No table space and one of the angry neighbors decided to take matters into his own hands by throwing a bucket of water out his window and onto the patrons waiting for their tables."], "output": "[['table space', 'negative'], ['water', 'neutral'], ['patrons waiting', 'neutral'], ['table s', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["But other comfort foods are also superb: Scallion pancakes are delectably crispy yet chewy, and chow fun with shredded pork and preserved cabbage (it's not on the menu) offers a tangy rice-noodles retake on the usual lo mein."], "output": "[['foods', 'positive'], ['Scallion pancakes', 'positive'], ['menu', 'neutral'], ['lo mein', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Worth the trip and the wait (and the higher than average price)?"], "output": "[['wait', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu: HOT DOGS, that's it, nothing else."], "output": "[['menu', 'negative'], ['HOT DOGS', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Heartland is the best place in mid-town to grab a beer after work and meet the cuties that work in the building."], "output": "[['beer', 'positive'], ['cuties', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My date and I had entrees, soup, and appetizers (fresh spinach pierogies) for $33 - ($40 with the tip)."], "output": "[['entrees', 'neutral'], ['soup', 'neutral'], ['and appetizers', 'positive'], ['fresh spinach pierogies', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The pizza is baked in a wood burning oven and the flavor is fantastic."], "output": "[['pizza', 'neutral'], ['flavor', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Noodle bowls are mixed with tempura vegetables, mountain yam, mushrooms, or spiced with curry or cold citrus dipping sauces."], "output": "[['mushrooms', 'neutral'], ['citrus dipping sauces', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Upon walking in and noticing the exposed red brick wall and the white tableclothes and and huge rack of various wines behind the bar, I felt like I was in a truly authentic Italian restaurant."], "output": "[['white tableclothes', 'neutral'], ['rack', 'positive'], ['wines', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They serve food with an entire loaf of freshly-baked bread, crusty on the outside and unbelievably warm and gooey in the center."], "output": "[['food', 'neutral'], ['bread', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I love the steak and eggs with a bloody mary that costs around $7 bucks."], "output": "[['steak', 'neutral'], ['eggs', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I found my dinner to be a bit on the heavy side and blamed the large portions."], "output": "[['dinner', 'neutral'], ['portions', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The entree -- a decent filet mignon, soupy mashed potatoes, and, believe it or not, frozen mixed veggies!"], "output": "[['entree', 'neutral'], ['filet mignon', 'positive'], ['mixed veggies', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["i thought the food was great but kind of expensive for that atmosphere, the tables were too close and it was too noisy."], "output": "[['food', 'positive'], ['atmosphere', 'positive'], ['tables', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Two dogs and an adequately sized drink for two dollars."], "output": "[['dogs', 'neutral'], ['drink', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The snooty manager asked us to leave and gave us our check in the middle of our meal."], "output": "[['manager', 'negative'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu options were not appealing, we had to beg the waiter to ask the chef if we could have just a plain dinner salad to start as their salad choices were not appetizing."], "output": "[['menu options', 'negative'], ['waiter', 'neutral'], ['chef', 'neutral'], ['plain dinner salad', 'neutral'], ['salad choices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu was much too narrow - 4 pastas and 6 meat dishes or so."], "output": "[['menu', 'positive'], ['meat dishes', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I still go often, but the prices went up a little and the service is even slower now that they're always full during dinner hours."], "output": "[['prices', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The music is a mix of house radio as well as live band at the same time."], "output": "[['music', 'neutral'], ['band', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Great when the band is playing, not so great when there's a large party at the bar."], "output": "[['band', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were seated promptly and brought rolls and water but then were made to wait much too long before our beverage order was taken and then much much too long before our waiter came back for a food order."], "output": "[['water', 'neutral'], ['waiter', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While service is still ok, the food has been not up to par on my last few visits."], "output": "[['service', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Suddenly the manager, came to our table yelling absolutely no way we can have a drink after dinner becuase he has tables waiting Just to be clear we spent over $70 and had 1 drink each, we used the table for about 1hour and 15 minutes."], "output": "[['manager', 'negative'], ['drink after dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We ate at the bar to avoid waiting for a table."], "output": "[['waiting', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the food at pongal is average, the rava masala dosa is much better at madras mahal (a few doors down) and certainly the service at pongal is the worst among the indian restaurants along that block."], "output": "[['food', 'neutral'], ['rava masala dosa', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I am hoping the stale service was a one shot deal because it was deplorable for what we paid for dinner!"], "output": "[['service', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The mussels and frits were great, but the host had an attitude and my friends and I waited about 1 1/2 hours to be seated on a random Tues."], "output": "[['mussels', 'positive'], ['host', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My hubby's a very picky eater, (plain, no condiments, no cheese, just salt pepper, and onions) and as busy as they were, they got it RIGHT THE FIRST TIME!!"], "output": "[['condiments', 'negative'], ['onions', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter nearly yelled at me when I asked for more water."], "output": "[['waiter', 'negative'], ['water', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Room is impressive, but service is slow and taste was almost like fast food."], "output": "[['Room', 'positive'], ['service', 'negative'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Appetizers and drinks came on time, but we waited 40/45 minutes for entrees."], "output": "[['Appetizers', 'positive'], ['drinks', 'positive'], ['entrees', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The sauce has a lemony olivey taste and the crust has the right mix of chewey and crunchy textures."], "output": "[['sauce', 'positive'], ['crust', 'positive'], ['mix', 'neutral'], ['textures', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They were out of cherry, so we got a few slices of apple and one key lime."], "output": "[['slices', 'negative'], ['apple', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu, which combines pan-Asian influences, offers a wide range of stir-fries and noodle dishes, with several varieties of momo (Tibetan dumplings) as highlights."], "output": "[['range', 'positive'], ['stir-fries', 'positive'], ['noodle dishes', 'positive'], ['Tibetan dumplings', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The smell was heavenly, and the appearance was great, but the cheese was a little too salty and heavy."], "output": "[['appearance', 'positive'], ['cheese', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["But the service was absolutely terrible, and we watied 45 minutes for food."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When we finally had to see the manager because I had lemon juice spilled on me from the waiter- she even took over 10 minutes to come to the table."], "output": "[['manager', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our apetizers took quite a while to be served, in fact, while all the other tables that sat way after us were being served I asked the waiter what happened to our appetizers, the calamari was tough; The entrees were tasteless and really!, one have to be really bad to mess a simple pasta dish."], "output": "[['apetizers', 'neutral'], ['tables', 'neutral'], ['waiter', 'negative'], ['appetizers', 'neutral'], ['calamari', 'negative'], ['pasta dish', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["a drink or two went by, but as we slowly realized our wait had become an hour from the promised 20 min, the server noted upon our inquiry that they recognized and remembered us and would seat us soon- rolling eye look- matched by a tone protesting the uncouth annoyance."], "output": "[['drink', 'neutral'], ['wait', 'neutral'], ['server', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Seated by a moody hostess and presented a menu that included live food-samples."], "output": "[['hostess', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["But the wait staff's attitude will make me rethink about returning."], "output": "[['wait staff', 'negative'], ['attitude', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We ordered 1/2 bottle of Gruner, 2 appetizers - foie gras and oysters, 2 entrees - steak and diver scallops, and 1 dessert, the pastry chef's favorite a mixture of crushed avocado, salt glazed caramel and lime sorbet (which really tasted like margarita infused guacamole, to try only if you're feeling wd-50 adventurous) for around $100."], "output": "[['appetizers', 'neutral'], ['foie gras and oysters', 'neutral'], ['entrees', 'neutral'], ['scallops', 'neutral'], ['dessert', 'neutral'], ['pastry chef', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["On our second trip, our waiter had an attitude, was slow to bring/refill drinks, and we had to flag him down for EVERYTHING."], "output": "[['waiter', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had to request water and chips (tostades) and salsa three times (the third time my date had to go and track down the waitress) before finally being served (by the busser) and the place wasn't even a quarter full."], "output": "[['water and chips (tostades)', 'neutral'], ['waitress', 'negative'], ['served', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service is ok since it is new and the staff didn't know the food items too well."], "output": "[['service', 'positive'], ['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["sirloin was spectacular -- tender, succulent and savory -- and even the salad and dessert (items where you might be willing to cut a steakhouse some slack) were superb."], "output": "[['salad', 'positive'], ['dessert', 'positive'], ['items', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The ambience is horrible but the food is incredible."], "output": "[['ambience', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They have even just expanded to include lunch hours at very reasonable prices."], "output": "[['lunch', 'neutral'], ['prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although the pricing is on the more expensive side, this is a must try restaurant for its food."], "output": "[['pricing', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["!While you are there, try the stuffed chicken wings, the salmon and take a stroll into the restroom."], "output": "[['stuffed chicken wings', 'positive'], ['salmon', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Hot foods selection every weekday for lunch."], "output": "[['foods', 'positive'], ['lunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although the prices is a bit on the high, you do get big portions for it."], "output": "[['prices', 'negative'], ['portions', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Expect to stand around for a while before one of the waiters desides that they can be bothered to actually get you to a seat."], "output": "[['waiters', 'negative'], ['seat', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["and you have to order through a pane of bulletproof glass, but the fact of the matter is, after a night of hard drinkin', college style, nothing hits the spot like a big box of inexpensive chicken and fries."], "output": "[['bulletproof glass', 'neutral'], ['style', 'neutral'], ['fries', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If it's just a quick martini at the bar (which I recommend Jeffery's) or a mind blowing Roast Chicken, go to Village!"], "output": "[['martini', 'positive'], ['bar', 'neutral'], ['Roast Chicken', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["40 minutes later, the waitress finally looked at our table and we asked about our dishes."], "output": "[['waitress', 'negative'], ['dishes', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Went for lunch but wanted to order a la carte, which was so highly discouraged by the waiter (pushing the 10."], "output": "[['lunch', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This restaurant was a great value, even though I know nothing about the prix fixe menu."], "output": "[['value', 'positive'], ['prix fixe menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Though the service leaves a lot to be desired, and the waitstaff runs around like chickens without heads, the beer is cold, the sake is hot, and the sushi is out of this world!"], "output": "[['service', 'negative'], ['waitstaff', 'negative'], ['chickens', 'negative'], ['beer', 'positive'], ['sake', 'positive'], ['sushi', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I will have to say the food was good and the chance to sample wines not often found in other restaurants was a positive but the abyssmal service left a bad taste."], "output": "[['food', 'positive'], ['wines', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere is fun -- dark, pulsing, basement room; a place where you feel like you can relax."], "output": "[['atmosphere', 'positive'], ['room', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["i also like their cocktail menu and dessert menu (try the black tea rose ice cream and the coconout waffles)."], "output": "[['cocktail menu', 'positive'], ['dessert menu', 'positive'], ['black tea rose ice cream', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Order the jalapeno cheddar potatoes- My meal tasted like mom's homemade cooking!"], "output": "[['jalapeno cheddar', 'neutral'], ['meal', 'positive'], ['cooking', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Sadly, many people feel the need to berate their server for a stronger drink."], "output": "[['server', 'negative'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Martinis from the bar are mixed at the size of 1 1/2 drinks, and the wait staff leaves the whole glass there, returning to pour you your remaining drink as your glass empties."], "output": "[['Martinis', 'neutral'], ['bar', 'neutral'], ['drinks', 'neutral'], ['wait staff', 'negative'], ['glass empties', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They moved us upstairs to an area where they were setting up for a private party -- we had no server, and had to flag down people setting up for the party to get us drinks, silverware, water, etc."], "output": "[['server', 'negative'], ['drinks', 'neutral'], ['water', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Shaved tuna and small tapioca balls--a playful substitute for roe--float in an addictive, tart-smooth pool of coconut water and kaffir lime juice."], "output": "[['tuna', 'neutral'], ['tapioca balls', 'neutral'], ['roe', 'neutral'], ['coconut water', 'positive'], ['kaffir lime juice', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had over 100 beers to choose from and the food and service was excellent."], "output": "[['beers', 'neutral'], ['food', 'positive'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For 2 patrons paying over $100 for dinner, you'd think that the waiter would check to see if everything was okay with the dining experience, and he certainly did not."], "output": "[['dinner', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Yes you have to wait to be seated and because its small there is no waiting area and the seat at the bar was all taken."], "output": "[['waiting area', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Appetizers, entrees and desserts suffered from a lack of variety in taste--all were nicely presented but none rose much above the level of something the average person could either cook for onesself or get at a well-run diner."], "output": "[['Appetizers', 'neutral'], ['entrees', 'neutral'], ['desserts', 'neutral'], ['taste', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food and cocktails at SushiSamba were very good; however the seating is so tight and uncomfortable and the service so rushed that I will probably never go back."], "output": "[['cocktails', 'positive'], ['seating', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The slices are pricey for the neighborhood (and always has been), but the fact that it is always packed attests to the value."], "output": "[['slices', 'positive'], ['neighborhood', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Came here for a b-day and ended up waiting so long even for a reservation."], "output": "[['waiting', 'negative'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I saw a waitress yell at 2 customers for moving a table out a little bit in order to have more seating space."], "output": "[['waitress', 'negative'], ['space', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had to wait 1hr since I got there around 8pm but you could have a few drinks by the bar since the ambiance is very loungy/ club like."], "output": "[['drinks', 'neutral'], ['bar', 'neutral'], ['ambiance', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The server (blond guy with blue eyes, we don't even know his name because he came to the table only twice) is rude and incapable and he didn't want to help for anything at all."], "output": "[['server', 'negative'], ['guy', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After the appetizers, which were the only saving grace (BBQ chips, spinach, fried bread), the servers descending and without asking started taking our plates away."], "output": "[['appetizers', 'neutral'], ['servers', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I visited the Park Slope location on Fifth Avenue, and was impressed with the menu, and that they offered chicken fried steak."], "output": "[['menu', 'positive'], ['chicken fried steak', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For dessert, try this pudding, translated Nipple of Venus."], "output": "[['dessert', 'neutral'], ['pudding', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Sushi is consistently fresh, service pleasant Sushi rice is a bit hard."], "output": "[['service', 'positive'], ['Sushi rice', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We recently went for dinner with two kids and the staff were very accomodating even without reservations."], "output": "[['dinner', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our dinner party of four all found the food better than average and of sizeable portions."], "output": "[['dinner', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I ordered a medium Cub burger and it came out well done, not that my server would have noticed since we didn't see her again until she brought the check."], "output": "[['server', 'negative'], ['check', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter knew his menu and what to recommend."], "output": "[['waiter', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We didn't see him the rest of the night, the other courses come out sporadically, and no one ever asked if we wanted more wine (which we did) or refilled our water -- even after we flagged down another waiter, nothing happened."], "output": "[['wine', 'neutral'], ['water', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We wouldn't bother quibbling over the price of a few drinks anyway but I wonder why they would offer if they weren't intending to back it up."], "output": "[['price', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitstaff is charming and knowledgeable about the menu."], "output": "[['waitstaff', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the atmosphere is that of a diner, but if you get a booth that is the best!"], "output": "[['atmosphere', 'positive'], ['diner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had 2 servers helping our party of 12, screwed up 3 orders had to re-do (frightful you never know what chef's mood is when they make mistakes)."], "output": "[['servers', 'positive'], ['chef', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although we didn't have a reservation, my husband and I enjoyed the food and drinks at the kitchen side seating."], "output": "[['reservation', 'neutral'], ['food', 'positive'], ['seating', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["No dress codes, no attitudes, plenty of comfort companionship, a great place to relax in an always busy Midtown."], "output": "[['dress codes', 'negative'], ['attitudes', 'negative'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It's the nicest place to nurse a cup of coffee (and the coffee is good), especially out in the little back garden."], "output": "[['place', 'positive'], ['cup of coffee', 'positive'], ['garden', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My friend and I enjoyed choosing from a very diverse menu of appetizers and entrees."], "output": "[['menu', 'positive'], ['appetizers', 'neutral'], ['entrees', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For an appetizer, I had soba in pho-like broth with dumplings, and I already liked the restaurant."], "output": "[['appetizer', 'neutral'], ['pho-like broth with dumplings', 'neutral'], ['restaurant', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Across the menu, and even within a single dish, there is a stunning variety of scintillating, distinct flavors."], "output": "[['menu', 'neutral'], ['dish', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["* Rude waiter - he kept pushing us to get appetizer (after been told twice that we would like to start ordering entree) and after dinner, told us to check out the shelf ourselves on our way to the restroom for dessert menu."], "output": "[['waiter', 'negative'], ['appetizer', 'neutral'], ['entree', 'neutral'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our reservation was for 9, didn't get seated until 9:20 with no acknowledgment by the staff of the delay."], "output": "[['reservation', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Everyting I ate there was incredible from the Tseukune (chicken dumplings) to the black bass special, right down to the velety chocolate pudding I had for dessert."], "output": "[['Tseukune (chicken dumplings)', 'positive'], ['black bass special', 'positive'], ['chocolate pudding', 'positive'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I would get the raisin bagels and occasionally a plain with lox and cream cheese, but now I go straight for the lox since I don't get there often."], "output": "[['raisin bagels', 'positive'], ['lox and cream cheese', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["At dinner on a Saturday night, I was enthused by the bustling, unpretentious crowd and the lusciously warm lighting."], "output": "[['dinner', 'neutral'], ['lighting', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our agreed favorite is the orrechiete with sausage and chicken (usually the waiters are kind enough to split the dish in half so you get to sample both meats)."], "output": "[['orrechiete with sausage and chicken', 'positive'], ['dish', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Instead of being smart business people and treating us as paying customers, we were told they do not serve drinks, only food (only food?"], "output": "[['business', 'positive'], ['drinks', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Instead of going to a fun lounge after dinner, as planned, everyone had paid so much, that we went to a dive bar for the rest of the night for cheap drinks."], "output": "[['lounge after dinner', 'positive'], ['bar', 'neutral'], ['drinks', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["One time the waitress left in the middle of our dinner."], "output": "[['waitress', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When I told the staff that I was displeased and wanted to write a letter to the owner, I was told the owner had no name and that I should just give the letter with no formal greeting (Dear Pick a Bagel Owner) to the cashier and that she would pass it along."], "output": "[['staff', 'negative'], ['Bagel Owner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["beside i have to wait long time with my food, waiter service ok but unfriendly."], "output": "[['food', 'neutral'], ['waiter service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["only drawback is that space is a bit tight at some tables, but all in all a great place to eat that we will be back to many more times!"], "output": "[['space', 'negative'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Yet, the place was emptyIts too bad because the food is authentic and price is very reasonable considering the location and the quality (eg."], "output": "[['food', 'positive'], ['quality', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Once we'd finished eating, it was another 15 minutes before we saw someone who would bring us the check - and after running my credit card, the waitress had the audacity to write cash only in the tip portion of the receipt!"], "output": "[['check', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Though it might be a wait and the service might leave a little to be desired, anyone that has ever eaten there agrees that the food is worth it."], "output": "[['wait', 'neutral'], ['service', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We ask the waiter where's the chocolate?"], "output": "[['waiter', 'negative'], ['chocolate', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I'd like to think that my brunch was an isolated incident, but just in case it is not, DON'T GET THE STEAK AND EGGS."], "output": "[['brunch', 'neutral'], ['STEAK', 'negative'], ['EGGS', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Again in a group 6 months ago, the service was even worse this time, practically begging for water and other drinks while we waited an age just to get our orders taken."], "output": "[['service', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitress took forever to take our order, we waited almost an hour for our appetizers, and then she asked us whether she even put the order in -- as if we would even know."], "output": "[['waitress', 'negative'], ['appetizers', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My french toast was two slices of bread cut in half- the perfect breakfast for a 4 year old."], "output": "[['french toast', 'neutral'], ['bread', 'neutral'], ['breakfast', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the food at this humble bastion of venezuelan home cooking is delicious-AND-authentic (how does this place rate only a 19 in zagat's?"], "output": "[['food', 'positive'], ['home cooking', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["i went there for dinner on friday night, the waiter had a terrible attitude."], "output": "[['dinner', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food turned out to be descent, but the waitress disappeared from the moment we placed the order untill she came back with the check."], "output": "[['Food', 'positive'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["But my lunch was very light with a wrap, not tortilla, but something thinner, a rice paper sort of crepe, that had lettuce and spicy cabbage and thin sliced beef."], "output": "[['lunch', 'negative'], ['wrap', 'neutral'], ['lettuce', 'neutral'], ['sliced beef', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The all-you-can-eat buffet (available for lunch or dinner from Tuesday through Sunday) features many of the takeout choices plus dishes like stewed beef, supremely tender barbecue ribs and a perfect potato salad."], "output": "[['dinner', 'neutral'], ['takeout choices plus dishes', 'positive'], ['stewed beef', 'neutral'], ['potato salad', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I think that argentine cuisine can be match more interesting better that the insipid expirience that I had in this overpriced place."], "output": "[['argentine cuisine', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had a plate of smoked meats, some stinky cheeses (that's how they were described on the menu), delicious marinated anchovies, and crostini with various vegetable toppings."], "output": "[['plate of smoked meats', 'neutral'], ['menu', 'neutral'], ['vegetable toppings', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We also had the egg platter, vanilla-coconut pancakes, and the Good signature breakfast (little bit of everything)."], "output": "[['egg platter', 'neutral'], ['signature breakfast', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In addition to the two rounds of drinks, the bartender and owner were a hoot."], "output": "[['drinks', 'neutral'], ['owner', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["i always scour citysearch for recommended dishes so here are mine: start with pork and pear appetizer (of asian pear and pork), have eel and cream cheese on top of multigrain rice (but do share it's big portion) and you must try beef with gingseng in stone pot."], "output": "[['dishes', 'positive'], ['pear appetizer', 'neutral'], ['asian pear', 'neutral'], ['multigrain rice', 'neutral'], ['beef', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["At least the entertainment was free, as we were able to witness one customer wooing a waitress, and another being drenched in milk."], "output": "[['entertainment', 'positive'], ['waitress', 'negative'], ['milk', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We weren't even offered a dinner menu and the waitress didn't even notice that we wanted drinks until after I ordered them from the bar myself."], "output": "[['dinner menu', 'neutral'], ['waitress', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This place is even good for just drinks after work (nice bar) I am going back there as soon as I get a chance."], "output": "[['drinks', 'positive'], ['bar', 'positive'], ['chance', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Tuesdays are Wine Lovers nights, where everything on their wine list is half off - it's a great deal."], "output": "[['Tuesdays', 'neutral'], ['wine list', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My water was filled like eight times, good, fast service."], "output": "[['water', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Meanwhile, our server was dancing and posing by the bar."], "output": "[['server', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Waited for a table, got disgusting martinis at the bar, and sat down."], "output": "[['table', 'neutral'], ['martinis', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["During dinner, we sat drinkless once again, as the server and owner never checked on us."], "output": "[['dinner', 'neutral'], ['owner', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We sat at one of the 2 large tables with benches inside the door instead of at the bar - the only options available at 7:15 when we arrived."], "output": "[['tables', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If it was outstanding I could see it as a nice change for lunch, but the peanut butter wasn't any better than one you could buy at any grocery store and the chocolate peanut butter brownie was horrible."], "output": "[['change', 'positive'], ['lunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["As I was paying the bill, the waiter would look over my shoulder to see how much tip I would be giving as where I could almost feel him breathing on my ear."], "output": "[['bill', 'neutral'], ['waiter', 'negative'], ['tip', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I'll second the recommedation for the Purity--which has much faster, better service at half the price and a whole lot more selection."], "output": "[['Purity', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Del Frisco's is pricey and I was seated in a leper locker room area, but the food was totally fantastic."], "output": "[['locker room area', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We waited 30 minutes to be seated, 40 minutes for water, bread, menus, 30 more for wine and soft drinks and when the food finally arrived an hour later, it was inedible, burned on top from sitting under a heat lamp."], "output": "[['water', 'neutral'], ['bread', 'neutral'], ['menus', 'neutral'], ['wine', 'neutral'], ['drinks', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The tea wasn't much good, the menu and the food was pretty much the same as the $5 curry row fare and the waiter need constant prodding."], "output": "[['tea', 'negative'], ['food', 'negative'], ['curry row fare', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This is one of my first dining experiences in NYC when I first moved here 10 years ago, and although Hudson Corner is consistently good, it has gone downhill over the years in both food quality and service!"], "output": "[['dining experiences', 'neutral'], ['food quality', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The wait staff are friendly, but they disappear after they take initial drink and food order."], "output": "[['wait staff', 'positive'], ['drink', 'neutral'], ['food order', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitress came back to our table several times to ensure we were well catered for."], "output": "[['waitress', 'positive'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The decor there is nothing special, though somehow the service manages to deal with the large crowds in an efficient, friendly manner."], "output": "[['decor', 'negative'], ['service', 'positive'], ['manner', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The mussels, garlic shrimp and jamon serrano are killer, while the creamy queixo cabrales--a regional Spanish blue cheese--makes a fine topper for the dense homemade bread."], "output": "[['mussels, garlic shrimp', 'positive'], ['jamon serrano', 'positive'], ['Spanish blue cheese', 'positive'], ['homemade bread', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Hunan Delight has one page in their menu full of Vegetarian dishes."], "output": "[['menu', 'neutral'], ['Vegetarian dishes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["But the karaoke downstairs is the real draw: You and your friends can sing yourself silly in absolute privacy, for nothing more than the cost of dinner and drinks."], "output": "[['karaoke downstairs', 'positive'], ['cost', 'neutral'], ['dinner', 'neutral'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Surf-and-turf encompasses the menu's star entrees: deliciously charred sesame-crusted tuna with ginger ponzu gently juxtaposes espresso-rubbed filet mignon."], "output": "[['menu', 'neutral'], ['entrees', 'neutral'], ['sesame-crusted tuna with ginger ponzu gently juxtaposes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The place was packed, but it didn't effect our service or getting our food/drinks promptly."], "output": "[['place', 'negative'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The kitchen would do well to offer more desserts--the one option of Eight Treasure Sticky Rice connotes a Chinese fruit cake--but the drinks downstairs encourage one to linger."], "output": "[['kitchen', 'positive'], ['desserts', 'positive'], ['Rice connotes', 'positive'], ['Chinese fruit cake', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We started at the bar with a round of mojitos, which were amazing, and went to our reserved table."], "output": "[['bar', 'neutral'], ['round of mojitos', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had a horrible night here stemming from intolerable service, no appologies after our food never came out after waiting longer than an hour and a half, and a plate of crusty bread thrown at us when we asked for their signature corn bread."], "output": "[['service', 'negative'], ['food', 'negative'], ['waiting', 'negative'], ['plate', 'neutral'], ['corn bread', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["SQC is great in the evening, the light is excellent and it's perfect to sit at the bar, eat oysters on the half shell and have a glass of wine."], "output": "[['light', 'positive'], ['bar', 'neutral'], ['oysters', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["And the room is VERY noisy, but I suppose that's because everyone is having a good time."], "output": "[['room', 'negative'], ['time', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["seated promptly; while waitstaff seemed confused as to what they should be doing (one actually looked at my partner's mojito and asked if she had 'put her dinner in the glass'), our waiter appeared experienced."], "output": "[['waitstaff', 'negative'], ['mojito', 'neutral'], ['dinner', 'neutral'], ['glass', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Noodle soup quantities are huge - so don't go for the rest of the menu - the rest are at par with the rest of Chinatown."], "output": "[['Noodle soup quantities', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Once we got our appetizers, it was ANOTHER 40 minutes before we got our entrees, which weren't hot and which were soggy and tasteless."], "output": "[['appetizers', 'neutral'], ['entrees', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The grilled calimari is *scrumptious*, and the must have is a cheese plate ordered with assorted meats, and for dessert, make sure someone has the roasted fruits and someone else has the expresso with ice cream."], "output": "[['grilled calimari', 'positive'], ['cheese plate', 'positive'], ['dessert', 'neutral'], ['roasted fruits', 'positive'], ['expresso with ice cream', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The strong suit of this place is the decor, alas we was seated and served by some guy who looked like he was out of a seedy 70's porn movie and everything went downhill after."], "output": "[['decor', 'positive'], ['served', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had an hour wait past our reservation time, so dealing with the bar scene was not helping things."], "output": "[['reservation', 'neutral'], ['bar scene', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When we mentioned it to the waiter, he shrugged and asked what we expected from a glass wine."], "output": "[['waiter', 'negative'], ['glass wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had the waiters bring back so much meat that that asked me if I wanted Flank steak for dessert."], "output": "[['waiters', 'negative'], ['meat', 'positive'], ['steak', 'neutral'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This is the kind of place that is suppose to have pushy waiters and a loud atmosphere."], "output": "[['place', 'neutral'], ['waiters', 'negative'], ['atmosphere', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The owner roasts his own meats and makes fabulous and interesting sandwiches--the house-roasted ham with celery-root salad and tomatoes on a baguette deserves a prize."], "output": "[['owner', 'neutral'], ['meats', 'neutral'], ['sandwiches', 'positive'], ['house-roasted ham with celery-root salad', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitress made a mental note about it and brought out a special dessert without being asked."], "output": "[['waitress', 'positive'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["some sweaty so frazzled, when we returned both an app and entree, the manager didn't even come to speak to us."], "output": "[['app', 'neutral'], ['manager', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Green bean salad was tasty but could have used a bit more of a kick  Baby backs - Wow!"], "output": "[['Green bean salad', 'positive'], ['Baby backs', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We arrived at Crema at 7:50 and the hostess advised she had no record of my reservation."], "output": "[['hostess', 'negative'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I can't resist the soul chicken whether I am at VP2 or Red Bamboo, but I've been a good girl and at least tried some other menu items and everything, and I mean EVERYTHING I tried has proved amazing."], "output": "[['soul chicken', 'positive'], ['menu items', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The scene is a bit much some time, but the food is worth it."], "output": "[['scene', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Informal servers sashay past plastic chairs and patterned booths, ducking enormous lampshades with cheerful insouciance."], "output": "[['servers', 'negative'], ['plastic chairs', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although the dining area is a bit small you'll feel at home as the owner is very friendly and talkative."], "output": "[['dining area', 'negative'], ['owner', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is always great, and if you're there for brunch, be sure to try their bloody mary!"], "output": "[['food', 'positive'], ['brunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When I walked back to the counter, the two staff people immediately retreated to the back room, glanced back at me attempting to get their attention and immediately returned to wasting time."], "output": "[['counter', 'neutral'], ['staff', 'negative'], ['back room', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For appetizer, I like Potli Samosa, but sometimes it is improperly cooked, which ruins the taste."], "output": "[['appetizer', 'neutral'], ['taste', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service isn't fantastic and the seating is a bit tight but if you aren't looking Four Seasons type quality, then this is the perfect spot to meet some friends for dinner or lunch."], "output": "[['service', 'negative'], ['seating', 'negative'], ['quality', 'neutral'], ['dinner', 'neutral'], ['lunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter and busboy apologized for the host who claims to have done this many times in his 13 years in the biz."], "output": "[['waiter', 'positive'], ['host', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The new server we had was surprisingly well-versed on the menu and gave really solid service."], "output": "[['new server', 'positive'], ['menu', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were promptly seated - the waitress was very attentive, got us drinks and menus."], "output": "[['waitress', 'positive'], ['drinks', 'neutral'], ['menus', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We only saw 2 - 3 boring appitizers on the menu and not a lot of choices of meat to select from."], "output": "[['appitizers', 'negative'], ['menu', 'neutral'], ['meat', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It's called OYSTER BAR, and yet no oyster selection at all!"], "output": "[['OYSTER BAR', 'neutral'], ['oyster selection', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It's so good, we send gophers from Wall St to pick up pies for lunch."], "output": "[['pies', 'positive'], ['lunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Went to dinner with some girlfriends on Wednesday at Calico Jacks and had a fun time."], "output": "[['dinner', 'neutral'], ['time', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Meat wasn't fall-off-the bone (a sign of over-cooking) but was tender and had deep flavor."], "output": "[['Meat', 'negative'], ['flavor', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They draw you in with a fancy looking decore which obviously cost a mint, ply you with overpriced wines (one bottle I knew was a 6$and they had the nerve to charge 40) This place sufferes from the same problem Areos does, it rests on its reputation."], "output": "[['decore', 'positive'], ['wines', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Waited 8 minutes for them to set up the table, another 10 to take our orders and 1 hr plus later for the waitress to say the food is coming in 2 minutes."], "output": "[['waitress', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The chef who is a bundle of personality came to tell us all about the special menu for the wine room."], "output": "[['menu', 'positive'], ['wine room', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While there are now a few appetizers, the traditional thali (sampling platter) is often your best bet; fixed nightly menu changes daily."], "output": "[['appetizers', 'neutral'], ['traditional thali (sampling platter)', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I ordered the eggs benedict, my wife a burger (one o the best i had in a long time) and the kids ordered french toast and belgium waffles."], "output": "[['burger', 'positive'], ['french toast', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Top it off with one of many Polish bottled beer and youre in food heaven."], "output": "[['beer', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went with my sister and neither of us had wine so the final bill was a bit shocking."], "output": "[['wine', 'neutral'], ['final bill', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While the people here were nice and the service was very good, the food was not very good - it was extremely greasy, the place did not offer alternatives such as egg whites and PAM spray instead of oil, coffee was average Crystal Rock Office Flavored Coffee - not the good coffee."], "output": "[['service', 'positive'], ['food', 'negative'], ['egg whites', 'neutral'], ['PAM', 'neutral'], ['oil', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were seated promptly, and after an inordinate wait, somebody took our drink order and disappeared for half an hour."], "output": "[['wait', 'negative'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Zero decor, this is not a date place--just a great place to get a quick, tasty and cheap meal."], "output": "[['decor', 'negative'], ['meal', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Be prepared to hear bad 70s rock and 80s pop thumping downstairs while you eat, but the food is shockingly good."], "output": "[['pop', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["GREAT APPETIZER BEFORE THE BURGER!"], "output": "[['APPETIZER', 'positive'], ['BURGER', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter rushed us through the last half of our dinner because they were turning the room into a dance floor."], "output": "[['waiter', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["18 has a cozy romantic atmosphere that's very comfortable to enjoy myself in; whether I want to have a drink at the bar or get together with a group of friends for dinner, suitable accomodations are available."], "output": "[['atmosphere', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We arrived on Tuesday (party of 2) at 6:55 sharp and the place was empty, with just a few people sitting at the bar."], "output": "[['place', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The hummus was not flavorful and when we ran out of bread and asked for more, it never came."], "output": "[['hummus', 'negative'], ['bread', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The space was unique (even though looking out the skylight windows on a tenament was a bit odd) and the service, happily, was fine."], "output": "[['space', 'positive'], ['skylight windows', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My favorite foods include the vegetable spring rolls, Goong Gar Bog (shrimp appetizer) and Pad Kimow Gai or Goong."], "output": "[['foods', 'positive'], ['vegetable spring rolls', 'neutral'], ['Pad Kimow', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The advertised unlimited mimosas and bloody marys is too good to be true until you realize that they keep down your drink count because the service is so slow."], "output": "[['mimosas', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After taking our orders, another person came to the table to announce the special dishes which the waiter forgot prompting 2 in our party to cancel the original orders in favor of the specials."], "output": "[['special dishes', 'neutral'], ['waiter', 'negative'], ['specials', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were a party of four, and after a long wait, were seated in a freezing corner."], "output": "[['wait', 'neutral'], ['corner', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They brought us one teacup sized bowl of chips for the 4 of us, which disappeared within minutes, and didn't replenish our chips until an hour later--after we finally got our food and after we asked them for some more chips 2 TIMES!"], "output": "[['bowl of chips', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Horrible service, below average cuisine, asked to leave the table before finishing our wine, and forced to have our port at the bar."], "output": "[['service', 'negative'], ['wine', 'neutral'], ['port', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They're just as fanatical about tlacoyos--homemade half-moon corncakes stuffed with smoky pulled chicken tinga--and hot-pressed sandwiches, like the Aztec Hoggie with shredded guajillo-spiced pork."], "output": "[['pulled chicken tinga', 'positive'], ['sandwiches', 'positive'], ['Aztec', 'neutral'], ['pork', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I've been there for lunch many times and the service is always cheerful and efficient."], "output": "[['lunch', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We asked for a side of dressing but the waiter told us that all the salads just had oil and vinegar so we should just use the oil and vinegar that was on the table."], "output": "[['side of dressing', 'neutral'], ['waiter', 'negative'], ['salads', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you like deep dish, you may be disappointed, as Grimaldi's only does thin crust, but if you want the best New York pizza, come here."], "output": "[['dish', 'neutral'], ['crust', 'positive'], ['New York pizza', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["To elaborate; the menu is written in French but the dishes themselves are something that your - enthusiastic yet talentless boyfriend - might muster up for you, leaving you looking concerned for his love for you."], "output": "[['menu', 'neutral'], ['dishes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": [") I'm sticking with Cafe Mozart--which has the same desserts, bigger slices, and lower prices!"], "output": "[['Cafe', 'neutral'], ['desserts', 'neutral'], ['prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I was shocked to have gotten no apology from the management, and to top it off were charged for the drinks we had while patiently waiting for food that never arrived."], "output": "[['management', 'negative'], ['drinks', 'neutral'], ['waiting', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The portions were so big that after a cocktail drink we had no room left for desert."], "output": "[['portions', 'positive'], ['cocktail drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Try the Bangkok fruit punch, or floating market drinks."], "output": "[['Bangkok fruit punch', 'positive'], ['market drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had the 6 course tasting menu - the salad and first course pasta was good; the gnocchi was watery with a tasteless sauce; then came out the entree, a burnt cod."], "output": "[['salad', 'positive'], ['course pasta', 'positive'], ['gnocchi', 'negative'], ['sauce', 'negative'], ['entree', 'neutral'], ['cod', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The cool thing about the 3 course price fix is that there is no special or limited menu, you can order ANY app, ANY entree and ANY Dessert."], "output": "[['course price', 'neutral'], ['menu', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter was just throwing our dishes on the table without even clearing the appetizer plates and then they started clearing the food when we weren't even finished yet."], "output": "[['waiter', 'negative'], ['dishes', 'neutral'], ['table', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It's interesting but after eating dinner here once the only thing I remember is that the bar was nice, drinks expensive and food was only average."], "output": "[['bar', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The wine cellar was perfect for our group of 10 for dinner last week."], "output": "[['wine cellar', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We asked for the manager who told us that it was their first time serving brunch, to be patient and that our bill would be discounted."], "output": "[['manager', 'positive'], ['serving brunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Nevertheless, after waiting for an eternity to be seated, we finally sit down and wait for our menus, wait for our food, and to our surprise the food was minimal relative to the price."], "output": "[['waiting', 'neutral'], ['menus', 'neutral'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My dinner started with a fish soup marseille, which was devine."], "output": "[['dinner', 'neutral'], ['fish soup marseille', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["(Note: Price variations were listed nowhere--and I had asked for a to-go drink, deciding--after paying--to sit at a no-service counter until my drink cooled off."], "output": "[['Price', 'negative'], ['to-go drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While the design of the space and the atmosphere is quite enjoyable (with a great view of Union Square), the food has once again proved to be less than favorable and the service mediocre."], "output": "[['space', 'positive'], ['atmosphere', 'positive'], ['food', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I came in for lunch with some co-workers, and we had an amazing meal for a bargain because they've extended the $20."], "output": "[['lunch', 'neutral'], ['meal', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I was their for Saturday lunch, adn I think that there's a different dinner menu, but everything was great."], "output": "[['Saturday lunch', 'neutral'], ['dinner menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you go, you have to order the beef ribs for appetizer, coconut char for entree and green donuts for dessert."], "output": "[['beef ribs', 'positive'], ['appetizer', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The entertainment is awesome - and believe it or not, I was so impressed with one of their musicians/singers (named Alessandro) that I even had him play during my cocktail hour."], "output": "[['entertainment', 'positive'], ['cocktail hour', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Waiter spilled a decent amount of water on my friend's plate -and then walked away - didn't remove the plate!"], "output": "[['Waiter', 'negative'], ['water', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food was good but we were forgotten after we finished our entrees."], "output": "[['Food', 'positive'], ['entrees', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The first time around, we had the $80 tasting menu, which included some sushi items, which I found to be pretty average, especially for the price."], "output": "[['menu', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I can only speak as a non-Indian, since we both come from an originally American palate, but Indian cuisine, both Northern and Southern, is my favorite non-Western cuisine, and I'm always on the prowl for something delicious and worth the price."], "output": "[['Indian cuisine', 'positive'], ['Southern', 'neutral'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitress was not very responsive to requests and was slow to return with drinks."], "output": "[['waitress', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["On another occasion, this same gentleman brought bottled water for our entire party [4] on the house again, when we missed our cab and asked to wait inside."], "output": "[['gentleman', 'negative'], ['water', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The head-on shrimps with anchovy butter had me licking the plate."], "output": "[['head-on shrimps with anchovy butter', 'positive'], ['plate', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had a side dish of pasta and that was definitely the tastiest of the entrees we ordered."], "output": "[['pasta', 'neutral'], ['entrees', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Despite a lovely atmosphere, this was perhaps the worst dining experience I've had in New York."], "output": "[['atmosphere', 'positive'], ['dining', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although the restaurant was far from crowded (maybe three tables), service was abysmally slow, to the point that we wondered if the server was trying to avoid us."], "output": "[['tables', 'neutral'], ['service', 'negative'], ['server', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We objected at the ill flavor of the drinks and the manager was not understanding at all."], "output": "[['flavor', 'negative'], ['drinks', 'neutral'], ['manager', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["One person's dinner was cold, another was charged for a larger portion than ordered, and my shrimp pasta was inedible."], "output": "[['dinner', 'negative'], ['portion', 'positive'], ['shrimp pasta', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The mole sauce is not too sweet and adds a nice flavor to the otherwise bland chicken."], "output": "[['flavor', 'positive'], ['chicken', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Again, since I go out to dinner several times a week in NY, I am used to paying high prices and do not mind at all."], "output": "[['dinner', 'neutral'], ['prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went back (with my cold soups) They said they would have to make me another dish since they couldn't scrape off the unwanted ingredients."], "output": "[['soups', 'neutral'], ['ingredients', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["But Bobby Flay really steps up at Bar Americain--his passion and heart shine through the food."], "output": "[['Bar', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["You have to wait in line most of the time, but the burgers are worth it and the beer is cheap."], "output": "[['wait', 'negative'], ['burgers', 'positive'], ['beer', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Like the other reviewer said, have a Mojito and enjoy the sugarcane."], "output": "[['Mojito', 'neutral'], ['sugarcane', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Only reason to go is Eben, the most solicitious bartender in NYC (now) with drink knowledge and ability to spare."], "output": "[['bartender', 'positive'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Don't ask for a menu- take the trip with your waiter who eloquently (and vividly) describes dishes until he sees your eyes light up."], "output": "[['waiter', 'negative'], ['dishes', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A terrific place to eat breakfast, lunch or dinner."], "output": "[['place', 'positive'], ['lunch', 'neutral'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food The secret to Nick's pizza is the sublime crust, which arrives caked in soot."], "output": "[['Food', 'neutral'], ['pizza', 'neutral'], ['crust', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Kids love the tabletop crayons and coloring books, but the real crowd-pleaser is raw pizza dough--lumps are available at the open kitchen window."], "output": "[['pizza dough', 'positive'], ['kitchen', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I thought I'd give the new place a try since it had an expanded menu and a more legit look."], "output": "[['new place', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food is fine but unremarkable, atmosphere is very noisy, especially for a date, and our waiter looked like he had never seen us before when we reminded him that we had ordered a second round of drinks 20 minutes earlier."], "output": "[['atmosphere', 'negative'], ['waiter', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The host was aloof; my waitress, though sweet, didn't seem to know the food or the menu very well; and the waiter we flagged over to order our wine seemed as if he had never looked at the wine list before."], "output": "[['host', 'negative'], ['waitress', 'positive'], ['menu', 'neutral'], ['waiter', 'negative'], ['wine list', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["really bad service took half an hour just to get a drink."], "output": "[['service', 'negative'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went there for lunch and brunch and both times had a very good meal."], "output": "[['lunch', 'neutral'], ['brunch', 'neutral'], ['meal', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For a restaurant with such limited menu and wine list, each dish should better be darn good."], "output": "[['menu', 'negative'], ['wine list', 'negative'], ['dish', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Babbo and Lupa are significantly better, and this place should redo the menu, or empty seats could become the norm."], "output": "[['menu', 'neutral'], ['seats', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I especially love the korean dish's they add into there menu consider its 2 for 1 its hard not to resist with asian cuisine being so expensive in all in New York."], "output": "[['korean dish', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["although the food was good, the wait was so long; extremely snobby about seating you, we waited 45 min + for our reservation."], "output": "[['food', 'positive'], ['seating', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I sat at the bar to receive faster service, and boy was i wrong!"], "output": "[['bar', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the variety of fish wasnt bad and all the usual suspects (salmon, tuna, yellowtail, squid, octopus, etc) were present."], "output": "[['variety of fish', 'positive'], ['yellowtail', 'neutral'], ['squid', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["$25 prix fixe sounds like a good deal, but dinner was still $100 for two, the portions were small, and the ($35) wine, clearly where the money is made, mediocre."], "output": "[['prix fixe', 'neutral'], ['portions', 'negative'], ['wine', 'negative'], ['money', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Reasonable prices for Cuban food in the city."], "output": "[['prices', 'positive'], ['Cuban food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Having heard that the steakhouse had a tendency to overcook the steaks, I asked the waitress that she ask the chef to prepare it closer to rare than medium."], "output": "[['steaks', 'negative'], ['waitress', 'neutral'], ['chef', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food here is consistently good - the service is not - but it seems that they're getting busier than they can handle, good for them, bad for guests."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The table next to us had hummus which looked delicious, so we really should have stuck to appetizers and wine."], "output": "[['hummus', 'positive'], ['appetizers', 'neutral'], ['wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I drop by to Cascina most often for lunch with co-workers for great pizza."], "output": "[['lunch', 'neutral'], ['pizza', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After dinner I walked over to the cheese counter -after having been greeted by a rude server, I was shocked to see how dissapointing their cheese selection was: it is miniscule, many of the fresh chevre cheese were more than ready to be tossed, etc."], "output": "[['dinner', 'neutral'], ['cheese counter', 'neutral'], ['server', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were so irritated about how horrible the food was, we didn't stick around to hangout at the bar."], "output": "[['food', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It would have been nice to find that out on the website but it took us an hour of waiting for Godot before calling and being told the news that no lunch was prepared for us."], "output": "[['waiting', 'neutral'], ['lunch', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Though the menu is brief, entrees range from a deeply satisfying, wintry seared calf's liver with oven-dried tomatoes to a much lighter striped bass drizzled with textbook perfect beurre blanc."], "output": "[['menu', 'neutral'], ['entrees', 'positive'], ['striped bass', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our meal was interrupted several times by the arguments between our waiter and the maitre 'd."], "output": "[['meal', 'neutral'], ['waiter', 'negative'], ['maitre', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter forgot about us for long periods of time and never even offered us a dessert menu."], "output": "[['waiter', 'negative'], ['dessert menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food was good, but for the price of a plate of pasta here, four raviolis doesn't cut it as an entre for a big guy."], "output": "[['Food', 'positive'], ['plate', 'neutral'], ['pasta', 'neutral'], ['guy', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I particularly like the side dishes -- the eggplant dip, for example -- and the appetizers."], "output": "[['side dishes', 'positive'], ['eggplant dip', 'positive'], ['appetizers', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene The consistent lines at this bustling Japanese tapas hot spot don't lie: Yokocho's fresh, reasonably priced comfort food and social atmosphere draw a youthful clientele of cultural natives and gaijin alike."], "output": "[['Scene', 'neutral'], ['priced comfort food', 'positive'], ['atmosphere', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For dessert we split the combination platter, which had rather small portions but they were good."], "output": "[['dessert', 'neutral'], ['platter', 'neutral'], ['portions', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I used to love the Dog but now its become a metling pot of really undesirable people."], "output": "[['Dog', 'positive'], ['pot', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Since we had to wait, we decided to get a drink but the bartender ignored us even when we made it known that we would like to order a drinks."], "output": "[['bartender', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We asked the server for two glasses with a splash of Southern Comfort and Grand Marnier."], "output": "[['server', 'neutral'], ['Southern Comfort', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Get there before 7:30 for dinner or get ready for a really long wait - this place doesn't take reservations."], "output": "[['dinner', 'neutral'], ['wait', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitress was kind and helpfull with the menu."], "output": "[['waitress', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For instance, the Spicy Potatoes were merly home fries with Red Hot sauce on them."], "output": "[['Spicy Potatoes', 'positive'], ['fries with Red Hot sauce', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The best aspect of Dylan Prime is that it's a perfect spot for a first date, a business dinner, a casual night-on-the-town or even just a quite bite at lunch."], "output": "[['spot', 'positive'], ['business dinner', 'neutral'], ['lunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["AND, the waitstaff likes to lick its fingers when cutting cakes/pies and serves hot and cold drinks by holding the glass or cup around the brim/top."], "output": "[['waitstaff', 'negative'], ['drinks', 'neutral'], ['glass', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["-the bread served was cold  -the choices for restaurant week was very slim (no meat dish except pork) -there were no chef's treats or delights -the food was ok but not up to the quality expected There are more exciting, romantic restaurants in the city to visit."], "output": "[['bread served', 'negative'], ['meat dish', 'neutral'], ['chef', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The manager, typical machissimo italian businessman, sat outside with his chef scowling and smoking -- an uncomfortable dining experience."], "output": "[['manager', 'negative'], ['chef', 'neutral'], ['dining experience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Great hamburgers, but the Corner Bistro has the worst service of any food establishment I've ever been to."], "output": "[['Corner Bistro', 'neutral'], ['service', 'negative'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Diver scallops were divine along with chilled beets or high volocety pasta."], "output": "[['scallops', 'neutral'], ['chilled beets', 'neutral'], ['volocety pasta', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I waited 10 minutes to get change for a drink I ordered at the bar, my friend had one of her drinks dumped all over the floor by the same waitress above who took too long to get me my change, and it took forever for that much to happen."], "output": "[['bar', 'neutral'], ['drinks', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is ok, typical for the chain, a good place to stop for a lunch."], "output": "[['food', 'positive'], ['lunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The hostess SLOWLY walked by our table scribbing something on paper."], "output": "[['hostess', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The tables are too close together and it's awkward to get up and down without disturbing the folks next to you, but the food is still the best around."], "output": "[['tables', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have never been treated more rudely than I was by the hostess and the manager of Public for brunch last Sunday; the hostess was arrogant, despicable, and mean to our party (reminder: she is a hostess in the service industry)."], "output": "[['manager', 'negative'], ['brunch', 'neutral'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They have a lot of beautiful clientele, gay and straight, plus you#146;ll spot random famous actors on occasion."], "output": "[['clientele', 'positive'], ['spot', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food The menu ably pulls off Bistro 101: The generous cheese plate makes a big enough starter for at least three people to share, and French onion soup is rich and decadent."], "output": "[['Food', 'neutral'], ['menu', 'neutral'], ['cheese plate', 'positive'], ['starter', 'positive'], ['French onion soup', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Upon entering we were promptly seated and ordered a few minutes after ordering the waiter came out and said they are completely out of crab, crab legs, crab claws everything."], "output": "[['waiter', 'negative'], ['crab legs', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food was blend and overcooked and the waitress kept on coming over every 10 minutes to ask whether if things were ok, do we want to refill drinks (when my drink was half full!!"], "output": "[['Food', 'negative'], ['waitress', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Yes the wait is dreafully long, the place feels a bit uncomfortable to talk in with your dining partner, but the food is excellent none the less."], "output": "[['wait', 'negative'], ['dining', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Server was nonexistent; when we flagged her down, she told us that the food was 'being plated' when clearly they were just starting to prepare it."], "output": "[['Server', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For $13 you receive 2 entrees, soup, rice, salad, maki roll, and small dessert."], "output": "[['entrees', 'neutral'], ['soup', 'neutral'], ['salad', 'neutral'], ['roll', 'neutral'], ['dessert', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When a seemly accommodating Le Souk manager assured you that he had no problem serving a group of twenty on a Saturday evening, I expected him to keep his words or shall I say our table."], "output": "[['manager', 'positive'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We both orderd drinks that we never recived, but were charged for, and when we said something to the waiter he rolled his eyes and asked if we wanted them anyway (after we were done eating and more than ready to go."], "output": "[['drinks', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This place is pricey, and yes, the food is worth it; but the service makes you feel like you should be paying a quater of the price."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service was good, but not excellent; however, the waiter was initially huffy with me when my guest was only 5 minutes late, threatening to make me move!"], "output": "[['service', 'positive'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Mixed drinks were bad, had to switch to beer."], "output": "[['Mixed drinks', 'negative'], ['beer', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The choices for vegetarians are extremely limited, unless one is content with side dishes."], "output": "[['choices', 'negative'], ['dishes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["food arrived quickly and was hot and v good, just don't be on a diet if you are going to eat here as no real options for slimmers!!"], "output": "[['food', 'positive'], ['options', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["no dish on brunch menu over $11 - definitely worth the price."], "output": "[['brunch menu', 'neutral'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Would go back when I was ordering off the regular menu and give the steak a try."], "output": "[['menu', 'neutral'], ['steak', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["and salads( try mixed green with mozzarella or chicken)."], "output": "[['salads', 'neutral'], ['mixed green with mozzarella', 'positive'], ['chicken', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Because our daughters weren't sure what to order, and were a little intimidated at the surroundings (notwithstanding the beautiful simplicity of the decor), they ordered only appetizers while their fathers ordered dinner."], "output": "[['decor', 'positive'], ['appetizers', 'neutral'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was OK, but I could have had pasta with tomatoes anywhere."], "output": "[['food', 'positive'], ['pasta with tomatoes anywhere', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My last day visiting NYC, I went last night to great Thai food ( Tiny Thai ) and today I had lunch at the unique sushi samba restaurant."], "output": "[['Thai food', 'positive'], ['lunch', 'neutral'], ['sushi', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It's very reasonably priced considering the size of portions."], "output": "[['priced', 'positive'], ['portions', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Waitstaff is preoccupied dancing on the bar and googling at beautiful people, but who can blame them."], "output": "[['Waitstaff', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the quantity of food was a good size with tons of shrimp in our noodle dish."], "output": "[['quantity of food', 'positive'], ['shrimp', 'positive'], ['noodle dish', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["One example, I ordered an appetizer that was not prepared as the menu stated and had to argue with waitress to get it fixed."], "output": "[['appetizer', 'neutral'], ['menu', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After ordering a couple beers from the pleasant bartender, my date and I took a seat at one of MANY vacant tables next to the bar (The bar stools were full)."], "output": "[['bartender', 'positive'], ['seat', 'neutral'], ['bar stools', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["All in all, it was a decent meal but dinner for two came to $172 with tip."], "output": "[['dinner', 'neutral'], ['tip', 'neutral'], ['meal', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Very claustrophobic place so expect it to be really crowded during lunch."], "output": "[['place', 'negative'], ['lunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Ignoring the plain decor, Jo-An is one of the best options for cheap japanese food on the Upper West Side."], "output": "[['decor', 'negative'], ['japanese food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When we got our food, the waitress barely said a word as she placed our take-out on the table and grabbed the check."], "output": "[['food', 'neutral'], ['waitress', 'negative'], ['take-out', 'neutral'], ['check', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Good food, even if it's inauthentic Thai."], "output": "[['food', 'positive'], ['Thai', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["He met me for wine tasting/sampling of food the week before and made sure that the service was on their toes."], "output": "[['food', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["What I don't get is asking a high rolling, forgiving of bad service, drink guzzling table like mine to leave as soon as we finished out last sip of $12 martinis and left a 25% tip."], "output": "[['service', 'negative'], ['martinis', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had a reservation for Monday lunch and were seated promptly, which was a pleasant surprise."], "output": "[['reservation', 'neutral'], ['lunch', 'neutral'], ['seated', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My only complaint might be the beer selection - they didn't really have any dark beers, which I like to have with a steak."], "output": "[['beer s', 'negative'], ['steak', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Aside from that, the service is adequate (visible, and will help you if you ask, but lack initiative), and the food, well, could be a lot worse."], "output": "[['service', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The lemon goat cheesecake was extremely dry and practically begged for a nice sauce or some fresh fruit."], "output": "[['lemon goat cheesecake', 'negative'], ['sauce', 'positive'], ['fruit', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter ask us what kind of soufle we wanted and told us to get 2, making us believe that it was part of the pre-fixe, nope soufles are seperate and we were so full from dinner we could barely finish one."], "output": "[['waiter', 'negative'], ['pre-fixe', 'neutral'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Not very crowded, the wait staff seemed to be in full force except when you needed their attention for something like water or tea."], "output": "[['wait staff', 'negative'], ['tea', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter was miffed when we decided to order dessert (and I must say we were eating the courses as they arrived, no lingering)."], "output": "[['waiter', 'negative'], ['dessert', 'neutral'], ['courses', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["At the end of the meal the waitress asked if we wanted another drink, the after agreeing to have one she stated, actually there's a list of people waiting, can you go next door to the bar."], "output": "[['meal', 'neutral'], ['waitress', 'negative'], ['drink', 'neutral'], ['people waiting', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I even had a waiter who was carrying a tray of beers actually TELL me to get out of the way as I was making my way towards the door."], "output": "[['waiter', 'negative'], ['beers', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Hey - What better excuse to sit at the bar and try another one of their fantastic drinks."], "output": "[['bar', 'neutral'], ['drinks', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was unremarkable: generally good, but lacking the spice and flair of more memorable cuban/latin cuisine."], "output": "[['food', 'positive'], ['spice', 'negative'], ['cuisine', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Nothing beats being served platters of shrimp and wings and pitchers of beer, by the HOTTEST waitstaff in NY!!!!"], "output": "[['served platters of shrimp', 'neutral'], ['wings', 'neutral'], ['beer', 'neutral'], ['waitstaff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Limited menu but for STEAK,,, and giant onion and tomato salad."], "output": "[['menu', 'negative'], ['STEAK', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I agree with the other poster who wrote about the service: the waiter challenged every single dish we ordered with a special (I've never had a more money hungry waiter) and after waiting 20 minutes for the check we had to call the manager over; who was unapologetic."], "output": "[['service', 'negative'], ['dish', 'neutral'], ['special', 'neutral'], ['waiting', 'neutral'], ['manager', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After we in fact moved to the bar, and I told the waitress which bottle we wanted - the one we had been drinking - we were told we had to order off the limited daily specials list."], "output": "[['bar', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We arrived on a Thursday night at 6:30 and were seated immediately (they don't take reservations), but, this small place filled up very quickly, and the bar was overflowing with people when we left."], "output": "[['reservations', 'neutral'], ['place', 'negative'], ['bar', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Some of the waiters are lacking good communication skills, but that can be overlooked in light of the great food and prices."], "output": "[['waiters', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I just had dinner there with my girlfriend and we had the best time."], "output": "[['dinner', 'neutral'], ['time', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The wait was much shorter than the hostess quoted, which was great."], "output": "[['wait', 'positive'], ['hostess', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["One waitress was downright rude when we asked for the check."], "output": "[['waitress', 'negative'], ['check', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was good I had the ground beef over rice."], "output": "[['food', 'positive'], ['ground beef', 'neutral'], ['rice', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Come in the evening, sip a glass of wine, or two, and enjoy the great live jazz along with your dinner."], "output": "[['live jazz', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["not only did we not get our 'bombay' fries until after the entire meal, but we then had to wait nearly an hour for our inattentive waiter to bring our check, and only after we flagged him down."], "output": "[['meal', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My husband and I sat at the bar, and service was excellent."], "output": "[['bar', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The hostess failed to inform us of that the restuarnt was hosting a private company party when we made the reservation."], "output": "[['hostess', 'negative'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For dessert the pecan pie, comes warm with whip cream."], "output": "[['dessert', 'positive'], ['pecan pie', 'positive'], ['cream', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["One friend had the steak which he didn't care for, but after waiting so long to be seated he was hungry."], "output": "[['steak', 'neutral'], ['waiting', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["although I don't think there is any beef on the menu (but there is plenty of fish and chicken)."], "output": "[['menu', 'neutral'], ['fish', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The new fall menu has a black cod with miso broth so good I thought I was at Nobu."], "output": "[['new fall menu', 'neutral'], ['black cod with miso broth', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Be prepared to make friends with the people sitting next to you, tight seating."], "output": "[['people', 'neutral'], ['seating', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I drank beer, but I tried her apple martini, It was great not sour at all."], "output": "[['beer', 'neutral'], ['apple martini', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Despite the fact that I had called earlier in the day and was told that the place didn't take reservations and there were several empty tables for two on both floors, we were told that there would be a 30 minute wait."], "output": "[['reservations', 'neutral'], ['tables', 'negative'], ['wait', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu has many dishes that one can't find anywhere in the city."], "output": "[['menu', 'neutral'], ['dishes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The rolls are tiny so you have to order more anyway and they will often get your order wrong if you stray from the menu."], "output": "[['rolls', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After scrunching into the tiny bar area and ordering a drink, I was annoyed but couldn't help but notice the handsome bartender having a tete-a-tete with another French-speaking cutie."], "output": "[['drink', 'neutral'], ['bartender', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Overall, the quality of the food won us over, but if there's one thing the management needs to work on, it's service."], "output": "[['management', 'negative'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I would definitely recommend getting reservations as the wait can be very long."], "output": "[['reservations', 'neutral'], ['wait', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Service was fine and the food delivered in reasonable time given the crowd, but for the price I was disappointed."], "output": "[['Service', 'positive'], ['food', 'positive'], ['crowd', 'neutral'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Once in the oven (electric, mind you), he shifts pies every few seconds to attain nicely-charred, chewy crust perfection."], "output": "[['pies', 'neutral'], ['perfection', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I've never been during the dinner rush, whence I think most of the service complaints originate."], "output": "[['dinner', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In addition, the manager refused to come over to apologize - but told the waitress to offer us TWO desserts on the house- when there were FOUR people dining."], "output": "[['manager', 'negative'], ['waitress', 'negative'], ['desserts', 'neutral'], ['dining', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It took the waiter over 30 minutes to get our food because the order was misplaced."], "output": "[['waiter', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["So maybe I'm naive to the latest trends in dining, but I really didn't like it."], "output": "[['trends', 'negative'], ['dining', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The retaurant is know for the long wait but they do take reservation for group of 5-8 people, so it was just perfect for my friend BD dinner for 3 couples."], "output": "[['wait', 'negative'], ['reservation', 'neutral'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is fantastic, Gourmet comfort food and has gotten progressively better over the past year, as did the service."], "output": "[['Gourmet comfort food', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The chorizo was a memory and sounded better on the menu."], "output": "[['chorizo', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["At one point, I spilled my water glass--when I informed the waiter of this he said he would clean it up--he never got around to it."], "output": "[['water glass', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service is great - they are very attentive and fast, however, they do make faces and comments when you order alot of the ALL YOU CAN EAT food."], "output": "[['service', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the waitress was slow and forgot our drinks about 3 times."], "output": "[['waitress', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the duck is not freshly roasted, it has been sitting under the IR lamp for hours, skin is not crispy."], "output": "[['duck', 'negative'], ['lamp', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After the wonderful anipasto tray came, it was 60 minutes before our plates were removed and dinner was brought."], "output": "[['anipasto', 'positive'], ['plates', 'neutral'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["5 minutes later the same waitress came back to have us move to the next table so she could seat a party of 4."], "output": "[['waitress', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The wasabi mashed potatoes were delicious while the chicken was dry."], "output": "[['wasabi mashed potatoes', 'positive'], ['chicken', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Arriba Arriba has much better food, margs, and atmosphere with slightly higher prices, but well worth it."], "output": "[['food', 'positive'], ['prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I agree with the many posters addressing an oppressively aggressive waitstaff, and I'm in particular support of the review directed at Franny's bizarrely adamant refusal to cut pizza (or provide adaquate knives/plates for us to do it ourselves)."], "output": "[['waitstaff', 'negative'], ['pizza', 'neutral'], ['adaquate', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The tables are a little too close together, but when the food is this good it's difficult to be distracted."], "output": "[['tables', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The ambiance is nice, but the wait staff was rude and unattentive."], "output": "[['ambiance', 'positive'], ['wait staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The clean, sunny interior looks nothing like Jerry and the gang's dingy haunt, but it showcases fun ephemera like Seinfeld cast autographs and press clips on how the diner inspired the musical ode by Suzanne Vega."], "output": "[['interior', 'positive'], ['Seinfeld', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I've heard such wonderful things about Pluck U and had the pleasure of trying their infamous chicken while having learned a few things: 1) rushed service 2) limited menu 3) semi-reasonable 4) overly popular."], "output": "[['infamous chicken', 'positive'], ['menu', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Serving things like Chicken Kiev with a garlic mashed potato egg roll for $$ with the snooty attitude to match!"], "output": "[['Chicken Kiev', 'neutral'], ['attitude', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I tried the Crab Croquettes (delicious, and yes, the sauce IS hot) and the Salade Jumelle (a good, basic mesculen salad)."], "output": "[['Crab Croquettes', 'positive'], ['sauce', 'positive'], ['Salade', 'neutral'], ['Salad', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["service is quick, not overly friendly, but hey it's a small place and the servers are constantly busy."], "output": "[['service', 'positive'], ['servers', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Their service can use a little assistance, but their food is great."], "output": "[['service', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food was at best, mediocre and when the bill finally came they had nerve to add on 20% gratuity even though there was nothing stated on the menu or anywhere that gratuity was included for a party of 5 (usually a party of 6 is gratuity inclusive)."], "output": "[['bill', 'neutral'], ['menu', 'neutral'], ['Food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Costs could be better - expect to be upsold by the hovering wait staff - and come for the authentic tastes, not the interior decor (looked a littel like Cheers!"], "output": "[['hovering wait staff', 'positive'], ['interior decor', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The price was right too--I spent under $30 for my entree and two drinks."], "output": "[['price', 'positive'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I don't think the menu is particularly creative, but I've gotten solidly tasty sushi here and it's always enormous."], "output": "[['menu', 'negative'], ['sushi', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I STRONGLY recommend to try something other than typical menu items and go for the short ribs over rice, black cod, sea bass, or duck (there are two dishes that are great)."], "output": "[['menu', 'neutral'], ['ribs', 'neutral'], ['rice', 'neutral'], ['black cod', 'neutral'], ['sea bass', 'neutral'], ['duck', 'neutral'], ['dishes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["As we attempted to digest our meal and browse the dessert menu, the same staff members approached us to move along our order."], "output": "[['meal', 'neutral'], ['dessert menu', 'neutral'], ['staff members', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While we were trying to have dinner, all of the waiters spent their time playing with spilled milk at the counter, not paying any attention to the diners."], "output": "[['dinner', 'neutral'], ['waiters', 'negative'], ['counter', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter took his sweet time bringing the menus and telling us the specials and it wasn't until almost 10:15 that we put our order in."], "output": "[['waiter', 'positive'], ['menus', 'neutral'], ['specials', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["great decor, unfortunately the worst service possible."], "output": "[['decor', 'positive'], ['service possible', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The upside of Zen Palate is the open kitchen, which allows you to watch the cooks at work and removes fears of who only knows what the chefs are doing in the back."], "output": "[['Zen', 'neutral'], ['open kitchen', 'neutral'], ['cooks', 'positive'], ['chefs', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I chose Guastavinos for my wedding reception dinner (for 19 of us) and planned it through their private dining staff."], "output": "[['reception dinner', 'neutral'], ['dining staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["No bar only a waiting area with about 10 tables where you can have drinks prior to dinner."], "output": "[['bar', 'negative'], ['waiting area', 'neutral'], ['tables', 'neutral'], ['drinks', 'neutral'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We organized a party at this bar and have gotten very poor service."], "output": "[['bar', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They always greet me and my friends warmly, deliver food promptly, are happy to answer questions about the menu, and they almost always throw in a free dessert at the end of the meal!"], "output": "[['food', 'positive'], ['menu', 'neutral'], ['dessert', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["90 for a porterhouse steak for 2 (ordered medium-rare, delivered well-done, dry and tasteless) and I'm not even full."], "output": "[['steak', 'neutral'], ['delivered', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Fusion-inspired tapas, such as wasabi-honey poached garlic shrimp, show off the talents of the San Sebastian-trained chefs."], "output": "[['tapas', 'positive'], ['wasabi-honey poached garlic shrimp', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The seafood is out of this world and priced accordingly."], "output": "[['seafood', 'positive'], ['accordingly', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The spinach was the best thing on the menu, the shrooms were soaked in reduction, and the goose fat potatoes were very decent."], "output": "[['spinach', 'positive'], ['goose fat potatoes', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Basically, all the food on the menu is a half-ass'd attempt at vietnamese food, followed by a innappropriate heap of MSG to make up for the lack of any flavor."], "output": "[['menu', 'neutral'], ['flavor', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Had a terrible time making a reservation and when we arrived they still had the table count wrong, and that was after 5 phone calls!"], "output": "[['reservation', 'neutral'], ['table', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had a nice time, place was crowded but the food was very good."], "output": "[['time', 'positive'], ['food', 'positive'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Ive personally tried almost everything on the menu and been amazed at the quality and presentation."], "output": "[['menu', 'neutral'], ['presentation', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Lunch (a chicken sandwich on baguette with fries) was decent, brunch (dry, hard pancakes) was pretty bad."], "output": "[['Lunch', 'positive'], ['a chicken sandwich on baguette', 'neutral'], ['brunch', 'positive'], ['pancakes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We got there before our reservation and the seated us quickly."], "output": "[['reservation', 'neutral'], ['seated', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They offer a sushi bar with very fresh fish, and the side dishes are excellent."], "output": "[['sushi bar', 'neutral'], ['fish', 'positive'], ['side dishes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Great deal for lunch; came to something like $11 with tip and tax!"], "output": "[['lunch', 'negative'], ['tip', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere couldn't be better, and the service was outstanding -- at the time there were only two people working the entire bar, and we still got taken care of like it was a five star restaurant."], "output": "[['atmosphere', 'positive'], ['service', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter was ever so helpful as he stood back and watched my sister and I physically move our table."], "output": "[['waiter', 'positive'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I was back-to-back with the diner at the table behind me and wait staff had to hoist trays over our heads as they squeezed past us again and again."], "output": "[['diner', 'neutral'], ['staff', 'negative'], ['trays', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We hung out by the bar mostly to ourselves, not an overwelming social crowd, but there were some georgous groups of hipsters looking like it was their meeting up before going out to the clubs (a few of the girls looked like top models), but the vibe was real chill."], "output": "[['bar', 'neutral'], ['crowd', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["(food was delivered by a busboy, not waiter) We got no cheese offered for the pasta, our water and wine glasses remained EMPTY our entire meal, when we would have easily spent another $20 on wine."], "output": "[['food', 'neutral'], ['busboy', 'neutral'], ['cheese', 'negative'], ['water and wine glasses', 'negative'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While admitably, the seating is a bit cramped, and the menu a tad pricey, the staff does its best to remedy concerns."], "output": "[['seating', 'negative'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It was practically impossible to get the waitstaff's attention to order another bottle of wine."], "output": "[['waitstaff', 'negative'], ['wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It's very cheap, food is great you can bring your own bottle of wine (saves sooo much money) The waiters will uncork it bring you glasses too !"], "output": "[['food', 'positive'], ['bottle of wine', 'neutral'], ['waiters', 'positive'], ['glasses', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Menu had several fish selections (snapper, salmon, cod) but all were around $30 despite the fact that the portions would hardly fill a child's belly and the sides were 3 pieces of lettuce (literally)."], "output": "[['Menu', 'neutral'], ['fish selections', 'positive'], ['salmon', 'neutral'], ['cod', 'negative'], ['portions', 'negative'], ['sides', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I'm a serious sucker for the buns listed in the appetizer section: big, fluffy, feels like true sustenance."], "output": "[['buns', 'negative'], ['appetizer', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although I usually go out mid-week for lunch, I now make it a habit to stop out Thursday or Friday evening to enjoy the live Jazz band."], "output": "[['lunch', 'neutral'], ['live Jazz band', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Space is teeny tiny so waiting at the bar meant getting poked and bumped repeatedly, but hostesses were nice and wine selection was ample."], "output": "[['Space', 'negative'], ['waiting', 'neutral'], ['bar', 'neutral'], ['wine selection', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We went inside to the lounge and found that there were several empty tables (which never ended up being occupied)."], "output": "[['lounge', 'neutral'], ['tables', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The quality of the food used to be worth the long waits but not anymore."], "output": "[['quality', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["even when they informed us they were out of the port we chose to accompany our dessert, the manager made sure that we were offered an even better bottle that wasn't even featured on the menu."], "output": "[['dessert', 'neutral'], ['manager', 'neutral'], ['bottle', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The caesar salad was a huge bowl of iceberg lettuce, a dressing that wasn't ceasar, 1 crouton and a few slices of thin chicken -- for $12."], "output": "[['caesar salad', 'neutral'], ['bowl of iceberg lettuce', 'positive'], ['dressing', 'neutral'], ['thin chicken', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I asked the waiter about the vintages of the wines, to which he replied, I don't know, probably 2003/2004."], "output": "[['waiter', 'negative'], ['vintages', 'neutral'], ['the wines', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In Short Despite the tacky Hellenic decor, replete with faux columns and signs of the zodiac carved into plaster walls, this Greek restaurant and bar bursts with authenticity when it comes to menu and atmosphere."], "output": "[['decor', 'negative'], ['bar', 'neutral'], ['atmosphere', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The only thing whihc i (and my partner) never heard before was: the waitress mentioned the price of the specials (?"], "output": "[['waitress', 'negative'], ['price', 'neutral'], ['specials', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["small portions, average food 6) we ask for the check, the waiter says, ok, and 5 minutes later asks if we want coffee or dessert."], "output": "[['food', 'neutral'], ['check', 'neutral'], ['waiter', 'negative'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["On your way out, pick up a bar of their Swiss chocolate."], "output": "[['bar', 'neutral'], ['chocolate', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were a bit chatty so it took us a while to decide what to order, but when we made it abundantly clear we were ready (closed the menu, looked around for our waiter) he was slammed from the recent filling of the space."], "output": "[['menu', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The parade of carbs--do we need tepid yuca firees and regular fires and mashed potatoes is superfluous; better to put some of these on the salad bar."], "output": "[['fires', 'neutral'], ['mashed potatoes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["To be fair, my husband's cheeseburger was quite good, but the waitress never apologized for the long wait or attempted to explain."], "output": "[['cheeseburger', 'positive'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had the Brazailian steak and the spinach and cheese crepe for dinner - the steak was tender accompanied with mashed potatoes and salad, but salty!"], "output": "[['dinner', 'neutral'], ['mashed potatoes and salad', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Because of the delicate thin crust, take-out pies get soggy in their boxes."], "output": "[['crust', 'positive'], ['take-out pies', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Server Sean Toussaint suggested specials and specialties worth the $$$ price."], "output": "[['Server', 'positive'], ['specials', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the food is still awesome - the twist on mexican is perfect - but the service is terrible - from the apathetic hosts to the unbelievably slow servers."], "output": "[['food', 'positive'], ['hosts', 'negative'], ['servers', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After lunch, we sat at the bar and chatted with the bartender who was also very nice."], "output": "[['lunch', 'neutral'], ['bartender', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["FINALLY the waitress came with our food after an HOUR!"], "output": "[['waitress', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the staff were pleasant and easy-going and took time to explain the specials to us as well as answer any questions we might have had."], "output": "[['staff', 'positive'], ['specials', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My entree was just some noodles in a butter sauce with no texture or color, except for a little bit of spinach which was more like a garnish."], "output": "[['entree', 'neutral'], ['noodles in a butter sauce', 'neutral'], ['texture', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Attention to detail in the ingredients, always cut to the right size so as to blend the flavor with the tastes of spices pefectly in your mouth."], "output": "[['ingredients', 'neutral'], ['flavor', 'positive'], ['tastes', 'positive'], ['spices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["sashimi was meh, salmon was good but the tuna was a little white and seemed like the day before as the flavor had faded."], "output": "[['sashimi', 'positive'], ['salmon', 'positive'], ['tuna', 'negative'], ['flavor', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The two vegetarian dishes on the menu were just an afterthought--why did they even bother?"], "output": "[['vegetarian dishes', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The hostess kept me waiting 10 minutes (attempting to read seating chart which I assume was in cyrillic) before determining whether she could seat us."], "output": "[['hostess', 'negative'], ['waiting', 'neutral'], ['seating', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter, even though he was serving dinner, was SO out to lunch."], "output": "[['waiter', 'negative'], ['lunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The portions were pretty small for the price, I thought, and I never got the coffee I ordered."], "output": "[['portions', 'negative'], ['price', 'neutral'], ['coffee', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the server absolutely did not know what in the world he was talking about when we aske questios about the menu, and he barely spoke English."], "output": "[['server', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Fresh, original, creative, absolutely delicious - Perhaps I would chose a table at this cozy Italian corner versus an NYC top 5?"], "output": "[['table', 'neutral'], ['corner', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Always try one of the daily specials, in addition to all the tasty morsels on the menu."], "output": "[['daily specials', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["(dissapointed) Over price for a lunch menu, including the lunch specials(be smart."], "output": "[['price', 'negative'], ['lunch menu', 'neutral'], ['lunch specials', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I only saw one waitress for the entire place, and small as it is, she only came to our table to take our order and take away plates, not once asking us if our food was to our liking."], "output": "[['waitress', 'negative'], ['place', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Starting off with an excellent carafe of Cotes du rhone suggested by the waiter, we soon ordered a few appetizers like the steak tartare, the escargot and the goat cheese tart."], "output": "[['waiter', 'positive'], ['appetizers', 'neutral'], ['steak tartare', 'neutral'], ['escargot', 'neutral'], ['goat cheese tart', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Space gets kind of crowded in there--because it's so popular--but it's worth the wait because the food is very good."], "output": "[['Space', 'negative'], ['wait', 'positive'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Tables are a little cramped, but dinner or lunch for 2 is fine."], "output": "[['Tables', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We sat for 20-40min without water or bread and were basically ignored by the waitstaff."], "output": "[['water', 'neutral'], ['bread', 'neutral'], ['waitstaff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Server took the order and disappeared for the entire rest of the night until we had to stop him b/c the bus boy knocked over our entire bottle of red wine soaking the white table cloth, the seats and our business suits."], "output": "[['Server', 'negative'], ['seats', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For the cost of the lunch I expected much better service."], "output": "[['cost', 'neutral'], ['lunch', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went here for a dinner with some relatives from out of town that I was eager to catch up with, but the noise level at this place made that really difficult!"], "output": "[['dinner', 'neutral'], ['noise level', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The wait time for food can be long, so don't dine here if you're in a hurry."], "output": "[['wait time', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["i think that the second floor is better if you prefer a quieter environment for dinner."], "output": "[['environment', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The wait staff is friendly and helpful and kudos to the sushi chef Hero who serves up great dishes on and off the menu and is always wearing a smile."], "output": "[['wait staff', 'positive'], ['sushi chef', 'positive'], ['dishes', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Try the sticky rice in lotus leaves, and finish with the almond jellow for dessert - if you don't like these dishes then you probably don't like real Chinese food!"], "output": "[['rice', 'positive'], ['almond', 'neutral'], ['dessert', 'neutral'], ['Chinese food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter (a real cutie) had to ask us twice for our entree selections, the coffee orders were wrong and after saying, no, thanks, the pepper man poised his mill above my friend's calamari dish and ground away."], "output": "[['waiter', 'negative'], ['entree', 'neutral'], ['pepper man', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Portions enough for 2 meals."], "output": "[['Portions', 'positive'], ['meals', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the waitress was surly -- refused to bring sweetner for my tea!!"], "output": "[['waitress', 'negative'], ['tea', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I ordered the strip steak medium - the waiter or the chef reversed our requests."], "output": "[['steak', 'neutral'], ['waiter', 'negative'], ['chef', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitresses are so nice and will even help you pick a meal if you are new to spanish food."], "output": "[['waitresses', 'positive'], ['meal', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There is a bar right by the door, which is convenient while waiting in the long lines for a seat and be prepared to wait on the weekends."], "output": "[['bar', 'neutral'], ['lines', 'negative'], ['seat', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I ended up wasting $24 on the most expensive dish on the menu."], "output": "[['dish', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is well thought out and each bite should contain a little of everything on your dish for the full effect."], "output": "[['food', 'positive'], ['dish', 'neutral'], ['effect', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the food is neither tasty nor reasonably priced ($137 for four with one glass of wine total?"], "output": "[['food', 'negative'], ['priced', 'negative'], ['glass of wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I waited for 45 minutes for my entree to realize that the waiter never put the order in."], "output": "[['entree', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our hostess was more concerned about the appearance of the banquets than wether we had the right menus."], "output": "[['hostess', 'negative'], ['menus', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We sat in the tables in front of the bar and it was a good people watching spot."], "output": "[['bar', 'neutral'], ['spot', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["On top of that, when we tried to order more food half-way through our first entree order, the waitress told us that we couldn't because they needed the table for another reservation!"], "output": "[['waitress', 'negative'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["However, didnt take too long to get drinks and the hostess seated us promptly."], "output": "[['drinks', 'neutral'], ['hostess', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Their pasta isn't spectacular nor is their marinara sauce, but their appetizers are wonderful."], "output": "[['pasta', 'negative'], ['marinara sauce', 'negative'], ['appetizers', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I was craving for the Chicken Penne for a long time after that, and so I went and ordered it for lunch, but the chicken was not fresh and the bread was tough too."], "output": "[['lunch', 'neutral'], ['bread', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Its the perfect place to take a date, start out with dinner and then stick around for dancing!"], "output": "[['place', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["i went here on a whim and found out you could get sushi for half price kind of like happy hour."], "output": "[['sushi', 'neutral'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although there were many open tables, the manager insisted my party wait at the bar for over one hour."], "output": "[['manager', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the best thing is the atmosphere, but even that is overshadowed by the lack of taste and originality in the food."], "output": "[['atmosphere', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is very good for the price."], "output": "[['food', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["That, the Peruvian style rotisserie chicken (get a whole one) and a side dish plus don't forget - chicha moradas: a refreshing non-alcoholic drink made from boiled purple corn and lime juice with tiny pear cubes and a bit of sugar."], "output": "[['Peruvian style rotisserie chicken', 'positive'], ['side dish', 'positive'], ['non-alcoholic drink', 'neutral'], ['sugar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter did not come back once to reserve our wine."], "output": "[['waiter', 'negative'], ['wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We shared three appetizers, (bruschetta's a good bet) a salad, a pasta dish, a quatro (about 3 glasses?)"], "output": "[['appetizers', 'neutral'], ['bruschetta', 'positive'], ['pasta dish', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The line is long, but the staff keeps it moving and usually everyone is friendly."], "output": "[['line', 'negative'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu was still small, but the quality of food that came out of the kitchen was superb, and the service was not bad at all."], "output": "[['quality of food', 'positive'], ['kitchen', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter knows us now, and the owner bought us a round of drinks once because the dessert took too long (in his opinion, we didn't even complain)."], "output": "[['waiter', 'negative'], ['owner', 'negative'], ['round of drinks', 'neutral'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My meal here was awesome, the appetizers, the bar finger food, the service, the drinks, the entrees of Smoked fish, Lamb salad, Clay pot salmon, Lobster rolls, and the dining room is spectacular."], "output": "[['meal', 'positive'], ['bar finger food', 'neutral'], ['service', 'neutral'], ['drinks', 'neutral'], ['entrees of Smoked fish', 'neutral'], ['Lamb salad', 'neutral'], ['Clay pot salmon', 'neutral'], ['Lobster rolls', 'neutral'], ['dining room', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you happen to catch it when no one else is there, sit down at the table, get a tea and try the coconut cake."], "output": "[['table', 'neutral'], ['coconut cake', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["That said, I made sure to pay before we had coffee, so that the server was not waiting on us to pay; and I left a 30% tip, knowing we'd be there for a while."], "output": "[['coffee', 'neutral'], ['server', 'negative'], ['waiting', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waitress forgot to bring me another margarita, but somehow she managed to get it on the bill."], "output": "[['waitress', 'negative'], ['margarita', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The DJ at the bar kept the place alive."], "output": "[['DJ', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The ambiance and service is great but I wish I could say the same about the food."], "output": "[['ambiance', 'positive'], ['service', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were ignored by our waitress after our entrees had been served."], "output": "[['waitress', 'negative'], ['entrees', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu is slightly different from downtown, but they still have my favorites -- madai salad with hot sesame oil, shrimp kanzuri, the diamond roll, the crispy shrimp roll."], "output": "[['menu', 'neutral'], ['shrimp roll', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Forget the phony yuppies of Areos and The Pearl Room, and ENJOY the down home service and OUTSTANDING food here."], "output": "[['Pearl Room', 'neutral'], ['service', 'positive'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Nothing like using iceberg lettuce, cooked chicken and a tangy salad dressing just to put a fancy name like Vietnamese Lemon Grass Chicken on an overpriced dish."], "output": "[['iceberg lettuce', 'neutral'], ['Vietnamese Lemon Grass Chicken', 'neutral'], ['dish', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["ONE OF THE BEST PIZZA IN BROOKLYN , NEED AN AC FOR SUMMER."], "output": "[['PIZZA', 'positive'], ['SUMMER', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The environment is a touch loud (although the music's good), but the walls sport nifty vintage items, from license plates to pennants to movie posters."], "output": "[['environment', 'negative'], ['music', 'positive'], ['plates', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I came here b/c someone gave a trashy review to my favorite coffee place (Grey Dog's) and compared it to this place so I had to see for myself what was so great about 71."], "output": "[['coffee place', 'positive'], ['Grey Dog', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Even as a stranger, the service at the bar was excellent as was the wait staff who continuously checked back to see if I was okay while waiting for my party."], "output": "[['service', 'positive'], ['bar', 'neutral'], ['wait staff', 'positive'], ['waiting', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After a short wait at the bar (which was very crowded), we were seated upstairs at a private table."], "output": "[['wait', 'neutral'], ['bar', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Rely on your food, your chef, your decor, your impeccable service, SOMETHING other than creating some fake VIP atmosphere to make people feel as if they need to gain admission in order to feel better about themselves."], "output": "[['food', 'positive'], ['chef', 'positive'], ['decor', 'positive'], ['service', 'positive'], ['atmosphere', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Looked good, lacked in seasoning, maybe that's why they leave the Old Bay on the Table, to season everything yourself."], "output": "[['seasoning', 'negative'], ['Table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The owner circles the place asking patrons if their meals are fine."], "output": "[['owner', 'positive'], ['meals', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["OK so the decor is a little old and tacky but it adds to the atmosphere."], "output": "[['decor', 'negative'], ['atmosphere', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Yoguart/mint/jalipeno sauce for instance didn't work with asparagus."], "output": "[['Yoguart/mint/jalipeno sauce', 'negative'], ['asparagus', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I go to Hing Won pretty often for lunch because it is close by and the prices are right."], "output": "[['lunch', 'neutral'], ['prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Just make sure everyone is in your party is there together or you'll be waiting on the sidewalk or in the cramped bar next door."], "output": "[['waiting', 'neutral'], ['bar', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter, of course had no knowledge of the yet to be produced wine list and no wine steward or manager bothered to come by the table to check in."], "output": "[['waiter', 'negative'], ['manager', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For dessert I had the green tea tiramisu and ice cream- I loved both, my bf who doesn't really like green tea actually really liked the tiramisu."], "output": "[['dessert', 'neutral'], ['green tea tiramisu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The ambience is stunning and the food is really good, but the portions are RIDICULOUSLY small."], "output": "[['ambience', 'positive'], ['food', 'positive'], ['portions', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For those who don't like that you have to make a reservation, to the restaurant's credit, this allows the restaurant to remain uncrowded and seat you immediately (at least this happened to my party)."], "output": "[['reservation', 'neutral'], ['seat', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Not the ideal spot when you're really hungry -- the plates are tiny and the prices not (like every other upscale tapas place)."], "output": "[['spot', 'negative'], ['plates', 'negative'], ['prices', 'negative'], ['tapas', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The crust was good, the flavor was good (I think they grate some sort of hard cheese over the pie), but the pizza was a bit watery, with the cheese sliding off rather than clinging to the slice."], "output": "[['crust', 'positive'], ['flavor', 'positive'], ['pie', 'neutral'], ['pizza', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had to wait quite a while to get my food and the waitress almost knocked me in the head with her tray."], "output": "[['food', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["AND you can still smoke at the outermost area of the patio - the wait staff can't technically serve you there because of the smoking, but if you don't mind walking to the bar to place an order (I don't), it's a great solution for smokers."], "output": "[['area', 'neutral'], ['patio', 'neutral'], ['bar', 'neutral'], ['solution', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The last time I was there (last week) our food took a little too long and a manager promptly apologized and offered to comp our desserts (not expected but appreciated)."], "output": "[['food', 'negative'], ['manager', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Once seated, there was no waitress to give us our menus."], "output": "[['seated', 'neutral'], ['waitress', 'negative'], ['menus', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Though it can be expensive, since you buy the fish and sides seperate and soem might get tired of shelling the shrimp themselves."], "output": "[['fish', 'neutral'], ['sides', 'neutral'], ['shrimp themselves', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If going for lunch, best to go by 12:30, even if getting take-out, the place is tiny and fills up quickly, both with people eating there, and standing waiting for take-out orders."], "output": "[['lunch', 'neutral'], ['place', 'positive'], ['waiting', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Whether it is a weekend brunch, dinner, or just hanging at the bar for cocktails, we always have THE BEST TIME."], "output": "[['bar', 'neutral'], ['TIME', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["8pm reservation, place was half empty on a Saturday."], "output": "[['reservation', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It came with a (small) salad, large bowl of udon, and 6 pieces of sushi plus wrapped rice (not sure what that was called."], "output": "[['salad', 'neutral'], ['bowl of udon', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I did like the shrimp dish, but I don't know if I'd seek out their cuisine again."], "output": "[['shrimp dish', 'negative'], ['cuisine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Extremely RUDE servers who intially took our order and never returned with drinks or to see if we required anythign else."], "output": "[['servers', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The dining rooms are opulent and beautiful; Great waiter who brought out a special birthday desert for my date after asking if our dinner was a special occasion."], "output": "[['dining rooms', 'positive'], ['waiter', 'positive'], ['desert', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I tried several dishes, while at dinner with friends, and was amazed to discover that even their Caesar Salad was completely lacking in flavor."], "output": "[['dinner', 'neutral'], ['flavor', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["4-Got attitude from the waitress at every moment she was at the table."], "output": "[['waitress', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There was a short wait for a table, which we spent at the bar, then we were seated on their patio."], "output": "[['wait', 'positive'], ['table', 'neutral'], ['bar', 'neutral'], ['patio', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": [") Not only do they do the shabu write with good ingredients, the sauces are both great, i recommend sesame for the meats and the other one for vegetables."], "output": "[['ingredients', 'positive'], ['the sauces', 'positive'], ['sesame', 'neutral'], ['meats', 'neutral'], ['vegetables', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["From the sushi to the terayki the food is excellent and the service (with a smile) is unmatched."], "output": "[['sushi', 'neutral'], ['food', 'positive'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food Chef Tom Kearney (Blue Hill, Jean-Georges) presides over the contemporary, pared-down menu."], "output": "[['Food Chef', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["i've been there for lunch - when the place is empty- and the waiter spent more time outside, soaking up the sun for himself, like he was a patron."], "output": "[['lunch', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Yesterday they had numerous bartenders as well as servers and the place wasn't packed and it still took 1/2 an hour to make a martini."], "output": "[['bartenders', 'positive'], ['servers', 'positive'], ['place', 'positive'], ['martini', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If the food is out of your price range then at least go for happy hour for a drink - although the drinks cost a bit more then the average happy hour bar after you receive one you would agree that it is worth it."], "output": "[['price', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["These are all new items on the menu the waiter told us, and they were delicious!"], "output": "[['menu', 'neutral'], ['waiter', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service was good and the price was decent but it wasn't enough to overcome the bland tasting food and the bland decor of the restaurant."], "output": "[['service', 'positive'], ['price', 'positive'], ['food', 'negative'], ['decor', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My date enjoyed his food, he had some type of jambalaya dish."], "output": "[['food', 'positive'], ['dish', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was pretty good but the portions were smaller than what I would expect for brunch."], "output": "[['food', 'positive'], ['portions', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["On my last visit we arrived around 9 on a Saturday, and although it wasn't crowded, the waitress acted like we were inconveniencing her, forgot bread, drinks, etc."], "output": "[['waitress', 'negative'], ['bread', 'neutral'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I wouldn't say Bubby's will blow you out of the water, but they provide a solid bunch served with good coffee."], "output": "[['water', 'neutral'], ['coffee', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Waiters poured wine like water, my guests were wondering out loud if they would get straws for the wine next."], "output": "[['Waiters', 'negative'], ['water', 'neutral'], ['wine next', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Went there for dinner last night w/ my boyfriend and a friend after work and got there around 7 so we were able to score seats in this tiny cramped space."], "output": "[['dinner', 'neutral'], ['space', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The sevice and food were excelent, but at the bottom of the menu were the words, cash only."], "output": "[['food', 'positive'], ['menu', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The staff is very friendly too~  Everything is wonderful about this place except for the bathroom."], "output": "[['staff', 'positive'], ['bathroom', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is simply remarkable as is the fiery female master sommelier!"], "output": "[['food', 'positive'], ['sommelier', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After an hour of waiting at an overcrowded bar with our coats in our hands and no room to move, I approached the host (who never bothered to give us an update throughout our wait) to ask him how much longer, He was incredibly rude and dismissed me with his hand and walked away from me while I was trying to talk to him!"], "output": "[['waiting', 'neutral'], ['bar', 'negative'], ['room', 'negative'], ['host', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If it's atmosphere you want go to the River Cafe under the bridges and pay an arm and a leg for hospital-type food."], "output": "[['atmosphere', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The mussles appetizer was delicious along with my peppercorn steak."], "output": "[['mussles appetizer', 'positive'], ['steak', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In Short This old-fashioned luncheonette, festooned with artificial flowers and signs touting the cherry lime rickeys, egg creams and banana-walnut pancakes, is favorite pitstop for folks visiting the Brooklyn Museum and Botanical Gardens."], "output": "[['cherry lime rickeys', 'positive'], ['egg creams', 'positive'], ['pancakes', 'positive'], ['Gardens', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In the middle of dessert, the waitress silently passes by and drops the check."], "output": "[['dessert', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["As the night rolls on the place turns into a bar/lounge so the wait staff is constantly rushing you to eat up and move out, not the kind of atmosphere you want for the price you are paying for your entree."], "output": "[['wait staff', 'negative'], ['atmosphere', 'negative'], ['price', 'neutral'], ['entree', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service was professional if somewhat slow, though we didn't mind since it is such a welcoming place to have dinner."], "output": "[['service', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went here with my family for dinner expecting the usual great pizza."], "output": "[['dinner', 'neutral'], ['pizza', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It seemed to take the new staff forever to figure out what they were doing; I had one nightmare of a brunch where the registers didn't seem to work and it literally took over an hour to get our check."], "output": "[['new staff', 'negative'], ['brunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Place was empty, waitress was rude, told us that even though there were drink specials at the bar (2 for 1 margaritas), we couldn't have them at our table and we couldn't go up to the bar to get drinks."], "output": "[['Place', 'negative'], ['waitress', 'negative'], ['drink s', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My appetizer of endive and bleu cheese salad was a surprisingly large serving which balanced the striped bass entree (served on a bed of vegetables)."], "output": "[['appetizer', 'neutral'], ['serving', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The outdoor tables overlooking bucolic Irving Place, or the wooden ones inside, are prime spots for brunch featuring all the usual suspects--omelets, pancakes, French toast--served on cast iron skillets and griddles."], "output": "[['outdoor tables', 'neutral'], ['Place', 'neutral'], ['brunch', 'neutral'], ['suspects', 'positive'], ['pancakes', 'neutral'], ['French toast--served', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The wine was great and they kept bringing us bread, these were the two best things about the meal."], "output": "[['wine', 'positive'], ['bread', 'neutral'], ['meal', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After stopping by on a whim a few months ago, I was so extremely impressed by the fresh Sushi and quality service that I now go there quite often for lunch as well as the occasional take-out dinner."], "output": "[['Sushi', 'positive'], ['service', 'positive'], ['lunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["On top of which, the waiter doesn't write down your order, the busboy brought us the wrong food 3 times, and there's barely any room while you're waiting to sit and have a drink."], "output": "[['waiter', 'negative'], ['busboy', 'negative'], ['food', 'negative'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Lunch box deal where you can pick two for $10 including rice and an ice tea is one of the best luches in the area."], "output": "[['Lunch', 'neutral'], ['ice tea', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I never have to wait a long time to get my food, so it's a great place to go if you're really hungry and/or in a hurry."], "output": "[['wait', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["noteworthy menu items that we tried - tasting menu 6 courses for $50 with 2 glasses of wine - great value - frog's legs, knuckle sandwich, lobster mac cheese, octopus salad and venison chop - just fantastic."], "output": "[['courses', 'neutral'], ['glasses of wine', 'neutral'], ['frog', 'neutral'], ['sandwich', 'positive'], ['lobster mac cheese', 'positive'], ['octopus salad', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Service was horrendous the night we went for dinner."], "output": "[['Service', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Odd considering my brunch turned out to be a nuked hors d'oevre quiche tart on a plate with some wilted/slightly spoiled salad - what a rip-off!"], "output": "[['brunch', 'neutral'], ['tart', 'neutral'], ['spoiled salad', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the grain salad was ok, the calf liver was stringy and the roast onions that came with it too heavy."], "output": "[['grain salad', 'positive'], ['calf liver', 'negative'], ['roast onions', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was average for brunch anywhere in NYC, and priced well above average."], "output": "[['food', 'negative'], ['brunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They do make great burgers for the money and give big portions of fries with it."], "output": "[['burgers', 'positive'], ['money', 'neutral'], ['portions of fries', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Went to Chow Bar for dinner, I thought it was kind of pricey, but the food and the service was good - but it wasn't incredibly busy, so maybe they just had more free time to devote to us."], "output": "[['Chow Bar', 'neutral'], ['dinner', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was OK, but trying to get anything, like a drink refill or the check, was an ordeal, and this was when the place was nearly empty!"], "output": "[['drink', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A simple shrimp seviche with fresh cocktail sauce shines on the lunch menu, while dinner items tend to be more sophisticated, such as turkey filet mignon with bacon and a bold mole negro."], "output": "[['shrimp seviche', 'positive'], ['cocktail sauce shines', 'positive'], ['lunch menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu and food make the restaurant a 10 - healthy; affordable; different; huge selection to choose from including Pastas; fishes; chicken and beef."], "output": "[['menu', 'positive'], ['food', 'positive'], ['Pastas', 'neutral'], ['fishes', 'neutral'], ['chicken', 'neutral'], ['beef', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The music got a bit loud around 9pm, but otherwise, the dim lighting and decor gave it a very sexy feel."], "output": "[['music', 'negative'], ['decor', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["our waitress couldn't explain or describe the specials to us, and a group of five people seemed to overwhelm her."], "output": "[['waitress', 'negative'], ['specials', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I took 8 clients to lunch and was appaled by the overall service."], "output": "[['lunch', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Before our server took our drink order she told us that the prices on the menu were going to be higher that night because of the party."], "output": "[['server', 'negative'], ['drink', 'neutral'], ['prices', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter (someone I know has been working there since it was just LCB) POURED MY WINE FROM THE DIRTY GLASS INTO A CLEAN ONE AND SERVED IT TO ME!"], "output": "[['waiter', 'negative'], ['WINE', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Cornelia Street looks like a Broadway set for West Side Story and the inside of Po is so cool quaint you really can't top the setting for a romantic dinner in NYC."], "output": "[['setting', 'neutral'], ['dinner', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Ok, so the service can be a little spotty, but despite this Cafe Con Leche has good food, and decent prices."], "output": "[['service', 'negative'], ['Cafe', 'neutral'], ['food', 'positive'], ['prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["However, they do bring you a lot of food for your buck, and despite the unremarkable food it strikes me as a good place to fill up on the cheap for lunch or after a night of drinking."], "output": "[['place', 'positive'], ['lunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["i've had practically everything on their menu as i dine out alot but their burgers and mussels with fries are what bring me there every friday night."], "output": "[['menu', 'neutral'], ['burgers', 'positive'], ['mussels with fries', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It's served cold with carmelized onions atop, with mashed potatoes on the side and it's the best darn thing this side of the Hudson."], "output": "[['served', 'positive'], ['carmelized onions atop', 'neutral'], ['mashed potatoes', 'neutral'], ['darn', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I said, that would be fine and had the hostess confirm my reservation before hanging up."], "output": "[['hostess', 'negative'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have been there for lunch many times and have always enjoyed my sushi."], "output": "[['lunch', 'neutral'], ['sushi', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["However the hostess completely ignored us, we waited 40 min at the bar (even with reservation), our waitress was incredibly uninterested in us (never even offered dessert menus) and the somelier could have taken a look at the label before he made a mistake about his favorite wine."], "output": "[['hostess', 'negative'], ['bar', 'neutral'], ['reservation', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The host's explanation was they could not control when people finish dinner."], "output": "[['host', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had been to Blue Fin previously for drinks and appetizers and thought the atmosphere was very good (expecially for people watching)."], "output": "[['drinks', 'neutral'], ['atmosphere', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The lobster bisque had a pasty bitter taste and the softshell crab was deep fried, served on a bunch of greens it had 0 flavor."], "output": "[['lobster bisque', 'negative'], ['greens', 'neutral'], ['flavor', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The free champaign and desserts do not really help me to even consider going back."], "output": "[['champaign', 'positive'], ['desserts', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["As if that wasnt enough, after another in the group mentioned that a portion of the sushi on her plate was not what she had ordered, the waiter came back with chopsticks and started to remove it (as she was eating!)"], "output": "[['portion', 'neutral'], ['sushi', 'neutral'], ['waiter', 'negative'], ['chopsticks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Smiling servers quiz diners with movie trivia, but forget to fill their water glasses."], "output": "[['servers', 'positive'], ['diners', 'neutral'], ['water glasses', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I highly recommend the chicken hearts, but remember: ask the waiters, since they're not usually available and will be cooked upon request (and will go fast)."], "output": "[['chicken', 'positive'], ['waiters', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had at least 10 of the appetizers on the menu, which all were delicious."], "output": "[['appetizers', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While the recently added outdoor seating was what drew me and my friend to the restaurant, the food, service and overall experience were what drove us out!"], "output": "[['outdoor seating', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["prices were low, you got a good deal, sushi was ok; everybody wins."], "output": "[['prices', 'negative'], ['sushi', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Was greeted and seated with no attitude from the host and hostess, despite no reservation."], "output": "[['hostess', 'negative'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food - The cheese plate contained flavored spreads instead of decent chesses."], "output": "[['Food', 'neutral'], ['cheese', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After arguing about this and requesting tap water instead of a bottled variety, we were exiled to customer Siberia, and the staff seemed eager get us out of the restaurant as soon as possible."], "output": "[['tap water', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The wait was long which is understandable but the waiters were rude to us while we waited, rushed us to order, ignored us while we ate and needed more drinks, and rushed us when they wanted the table for another couple."], "output": "[['waiters', 'negative'], ['drinks', 'neutral'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["That was totally acceptable and we found some great seats at the bar."], "output": "[['seats', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The place is small, the host was friendly and communicative -- we had to wait 45 minutes for a table but they don't take reservations and clearly it's a popular spot."], "output": "[['place', 'negative'], ['reservations', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The ices and the spumoni were perfect desserts to the pizza."], "output": "[['spumoni', 'positive'], ['desserts', 'positive'], ['pizza', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["And forget about having a drink at the bar to take the edge off because the space between tables is so narrow that you'll be shoved by the wait staff who are desparate to get their job done."], "output": "[['drink', 'neutral'], ['bar', 'neutral'], ['wait staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The foi gras empanadas were OK--I would try another dumpling."], "output": "[['foi gras empanadas', 'positive'], ['dumpling', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service was not the greatest, but the place is huge and it has a nice setting."], "output": "[['service', 'negative'], ['place', 'positive'], ['setting', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Fried appetizers, tuna steak and other dishes are also available, as well as an assortment of sakes, graphed on the menu according to flavor components."], "output": "[['dishes', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["First, we waited 40 minutes for our food, but after a thrity minute wait, the waitress asked me to clarify what I had ordered (I ordered off their menu, with no changes)."], "output": "[['food', 'neutral'], ['waitress', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waitress was rather un-friendly, seemed annoyed that we didn't want appetizers and we waited 15 minutes before our wine arrived."], "output": "[['waitress', 'negative'], ['appetizers', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The view is the reason to go to this restaurant, not the food nor the service."], "output": "[['view', 'positive'], ['food', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Trish, our waitress was really great - the food was mediocre."], "output": "[['waitress', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter showed up two minutes later to take our order and showed up with our drinks 25 minutes later and they were not crowed."], "output": "[['waiter', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food Diners are prompted to order several shareable dishes which, considering the food isn't what's drawing most of the crowd, are surprisingly good."], "output": "[['Food Diners', 'positive'], ['crowd', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["From chicken wings and smoked beef brisket to pulled pork and Texas links, the menu features many barbecue favorites."], "output": "[['smoked beef brisket', 'positive'], ['pork', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While the bar is expansive, the ceilings are high, the tables are spacious and the plates are oversized, where is the food?"], "output": "[['bar', 'positive'], ['tables', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The space and furnishings are too spartan and the service amateur and scattershot (no smiles offered here - busboy serves mains with who gets the."], "output": "[['space', 'neutral'], ['busboy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While the appetizers, entrees, and desserts arrived in a timely manner, our water glasses maintained consistently empty (at one point one of us had to ask for water twice!)"], "output": "[['appetizers', 'neutral'], ['entrees', 'neutral'], ['water glasses', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They offer a small but good selection of beer and wine from India, and their cuisine can please the most spice-averting palates of those American friends of yours who claim to not like Indian food."], "output": "[['beer and wine', 'positive'], ['cuisine', 'positive'], ['Indian food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It's made with cauliflower, wild mushrooms, and no rice at all."], "output": "[['wild mushrooms', 'neutral'], ['rice', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["By this I mean that the guy selling hotdogs outside of Grand Central has given me better service."], "output": "[['guy selling hotdogs', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Don't miss the crema catalana the waiter recommended us for dessert."], "output": "[['waiter', 'positive'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Yes it's pricey for counter service, sawdust floors and deafening chatter but the pastrami makes it all worth it."], "output": "[['counter service', 'negative'], ['pastrami', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have never had a bad meal or service (on a couple of occasions I waited past my reservation time)."], "output": "[['meal', 'positive'], ['service', 'positive'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Actually, upon being seated in the tea room, we weren't even offered the tea menus and had to ask for it."], "output": "[['the tea room', 'neutral'], ['tea menus', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter didn't even bothered to ask for dessert."], "output": "[['waiter', 'negative'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Delivery wasn't the fastest, but the food was still hot so I won't complain."], "output": "[['Delivery', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The crowd is not young, but hey, go somewhere else to get a drink afterward."], "output": "[['crowd', 'negative'], ['drink afterward', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Everything that we tasted on the menu was great, particularly the shrimp tapas (if you don't order it yourself, the waiter will surely recommend it)."], "output": "[['menu', 'neutral'], ['shrimp tapas', 'positive'], ['waiter', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["By the time you get to the table, it'll have been WELL worth the wait."], "output": "[['table', 'neutral'], ['wait', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A lot of energy and I loved the actors who came to our table."], "output": "[['actors', 'positive'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For desset, I had Cecilia's Chocolate Marquise served with vanilla sauce and crushed pistachios."], "output": "[['Chocolate Marquise served with vanilla sauce', 'neutral'], ['pistachios', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After ordering a good amount of sushi the waiter asked me if that was all I wanted."], "output": "[['sushi', 'positive'], ['waiter', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The fish of the day can be prepared five different ways according to the menu, but fails to mention that those five different ways are just five different sauces that come out with the whole, deep fried fish."], "output": "[['menu', 'neutral'], ['sauces', 'positive'], ['deep fried fish', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I ordered the $39 filet and ordered it medium and it came to the table well done and tasted like a goodyear tire."], "output": "[['filet', 'neutral'], ['tire', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They have a great selection of wines, and have recently expanded with a Wine Bar around the corner that's accessible through the main dining room."], "output": "[['selection of wines', 'positive'], ['Wine Bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The only saving grace is the sweet tea - but even that isn't worth the wait."], "output": "[['sweet tea', 'positive'], ['wait', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The happy hour crowd at the bar was mostly just out of worker blowing off steam."], "output": "[['crowd', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is ok at best, but the service and the uncomfortable accomidations have such a negetive effect, that one can only wonder why they waited so long for so little."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For entrees, my favorites were the coriander and honey pork ribs or the seared scallops, both of which were to die for."], "output": "[['entrees', 'neutral'], ['coriander and honey pork ribs', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["5 hour meal (we ordered the tasting menu)."], "output": "[['hour meal', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was good overall, but unremarkable given the price."], "output": "[['food', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["then, the waiter had nerve to charge me for the fruit salad and bloody mary (which we didn't drink) that came with the omelet (brunch special)."], "output": "[['waiter', 'negative'], ['fruit salad', 'neutral'], ['omelet', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The lobster is good but over-priced; go for lunch and it's only $35 and served prixe-fix with all the trimmings."], "output": "[['lobster', 'positive'], ['lunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["i do agree with the comment about their waitstaff, they tend to make you feel like you have to rush through your meal."], "output": "[['waitstaff', 'negative'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I only had lunch here, but i had great shrimp and a spectacular lobster, and the dessert was heavenly."], "output": "[['lunch', 'neutral'], ['shrimp', 'positive'], ['lobster', 'positive'], ['dessert', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Sure, the wait was a bit long for a table, but the service was good and the food was pretty good too."], "output": "[['wait', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is a melding of Moroccan comfort food and Spanish tapas fare: tagines, stews and salads, with surprises like baby eggplants and olives where you might not expect them."], "output": "[['Spanish tapas fare', 'neutral'], ['salads', 'neutral'], ['baby eggplants and olives', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["tuesday at 545pm pre-show dinner - great food - amazing service - was strange to find both at one place!"], "output": "[['pre-show dinner', 'neutral'], ['food', 'positive'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service is good, but the staff is not too friendly."], "output": "[['service', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After a show we had surperb steaks and had cocktails at the bar."], "output": "[['steaks', 'positive'], ['cocktails', 'neutral'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We approached the host and manager politely after the meal but only received a simple and insincere Sorry."], "output": "[['host', 'negative'], ['manager', 'negative'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My best friend and I went to dinner on Friday, November 8, 2002 and we both enjoyed our meals."], "output": "[['dinner', 'neutral'], ['meals', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food  Crave's two chefs have resumes that boast stints at Payard, Nobu and Industry (food), so it's no surprise their menu is full of unusual twists on old favorites."], "output": "[['Industry', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My friend's entree wasn't presented as described in the menu, but we didn't want to add to the drama."], "output": "[['entree', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The host came by and told us that they made a mistake and would have to seat us at a two-person table."], "output": "[['host', 'negative'], ['seat', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Noisy atmosphere makes the place even more fun, though it may become hard to get in after 5PM on Friday- almost every table would be reserved."], "output": "[['atmosphere', 'negative'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had to ask for water multiple times, there were no paper towels in the bathroom and even after informing a staff person they still were none an hour later."], "output": "[['water', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It appeared that they used a cheese pizza cooked earlier that day or the day before and just added the raw topping to it, then delivered it."], "output": "[['cheese pizza', 'neutral'], ['topping', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["What a pleasant surprise to have found a restaurant where you can sit at the bar and feel like a glamourpuss, yet whose staff and even other patrons make you feel like you are already a family friend."], "output": "[['bar', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In Short Many Murray Hill locals gladly overlook the dull green walls and fluorescent lighting for Jaiya's quick and affordable Thai cooking--if not, they take meals to go or get them delivered."], "output": "[['walls', 'negative'], ['lighting', 'negative'], ['Thai cooking', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When he mentioned that a pinot noir would be a decent match with two disparate plates of a first course (and the even further disparate second course- yes we informed him of our total meal choices PRIOR to our wine selection)."], "output": "[['pinot noir', 'positive'], ['meal', 'neutral'], ['wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They had a definite buzz at the bar, but the place is so big that we felt like we had our own private room in the back."], "output": "[['bar', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food is average, service is awful, and the attitude isn't New York - it's just plain rude - and most of NYC is caring and courteous."], "output": "[['Food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We arrived at 5:30 and had leave at 7:30 without dessert or coffee because the kitchen took insanely long between courses."], "output": "[['kitchen', 'negative'], ['courses', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was abundant and good but wasn't worth the unpleasant wait."], "output": "[['food', 'positive'], ['wait', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It says it on the menu and the servers explain it to you as soon as you sit down so I'm surprised by how many people on this site complain about the portion sizes."], "output": "[['menu', 'neutral'], ['servers', 'negative'], ['sizes', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The bar was so crowded there was no point in ordering a drink, and when we were finally seated we got no service at all for 20 minutes."], "output": "[['ordering', 'neutral'], ['drink', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I absolutely hate communal seating and closely spaced tables and this place had both, but the atmosphere and the food were such that I was able to get beyond the grumpy mood that put me in to have a really good experience."], "output": "[['spaced tables', 'negative'], ['atmosphere', 'positive'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waitress kept forgetting our drinks."], "output": "[['waitress', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although my waiter had about as much personality as a dead fish, I loved the great solid food and would definately go back."], "output": "[['waiter', 'negative'], ['fish', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The busboy kept our glasses full; the waiter warmed up to our table at the end of the night by cracking jokes."], "output": "[['glasses', 'neutral'], ['waiter', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene The bruising thoroughfare that is East 57th Street is the last place you'd expect to find an intimate, adorably decorated Northern Italian spot where it's actually possible to have a quiet, pleasant dinner."], "output": "[['Scene', 'neutral'], ['dinner', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I love the creative rolls that they have on their menus, and none of them were a disappointment."], "output": "[['rolls', 'negative'], ['menus', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["had dinner there last night, max the waiter was great."], "output": "[['dinner', 'neutral'], ['waiter', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Hoegardden on tap is an added bonus if you're not drinking from the well versed wine menu."], "output": "[['tap', 'neutral'], ['wine menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The halibut cheek appetizer came with a generous portion of foie gras, but that's about the only positive thing I can say about the meal."], "output": "[['halibut cheek appetizer', 'neutral'], ['portion of foie gras', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We started at the bar with a nice bottle of wine, which was priced fairly and sampled several different cheeses."], "output": "[['bar', 'neutral'], ['bottle of wine', 'positive'], ['cheeses', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The best out of the three entree's we had was the goat cheese ravioli."], "output": "[['entree', 'neutral'], ['goat cheese ravioli', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I made the mistake of coming here with 5 friends for brunch so the wait was extremely long and then we got stuck at the only table big enough for 6 (downstairs near the bathroom away from all of the other patrons) so that was dissapointing but I will be back soon with 1 or 2 friends."], "output": "[['brunch', 'neutral'], ['wait', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While waiting there was no room for standing and the bar staff and their drinks were horrendous."], "output": "[['waiting', 'neutral'], ['bar staff', 'negative'], ['drinks', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We walked out the door with only a drink in each of us and the bill was still over $100."], "output": "[['drink', 'neutral'], ['bill', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The owners are incredibly nice too, comping pitchers of margaritas if you sit there and eat for a couple of hours."], "output": "[['owners', 'positive'], ['margaritas', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Wether you want a Regular Slice, their DELICIOUS marinara sicilian, or one of their specialty pizzas like Chicken Parm, Ravioli, or Taco pizza once you eat a Rosas Pizza you will never go anywhere else."], "output": "[['marinara sicilian', 'positive'], ['specialty pizzas', 'positive'], ['Chicken Parm', 'neutral'], ['Ravioli', 'neutral'], ['Rosas Pizza', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This is of course after waiting forever for menus and eventually having to ask for them."], "output": "[['waiting', 'negative'], ['menus', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["As a former waitress, I get this conceptually, and I am even understanding of the fact that I had to wait 30minutes to get my first drink because the bar was backed up."], "output": "[['waitress', 'positive'], ['drink', 'neutral'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Salads are a delicious way to begin the meal."], "output": "[['Salads', 'positive'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My only complaint is waiting a bit between the appetizer and the main course but it was well worth it."], "output": "[['waiting', 'negative'], ['main course', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Additionally, one of the waiters found it necessary to walk around the restaurant, telling people how to eat their food."], "output": "[['waiters', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The only time the waitress paid any attention to us was when she took our order and at the end of our meal to ask if we wanted dessert (by then we had already packed up our leftovers and were waiting for change from our bill)."], "output": "[['waitress', 'negative'], ['meal', 'neutral'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They deliver and I've used their food for quick executive type lunches in my office."], "output": "[['food', 'neutral'], ['lunches', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The high light was the fondue, that we never got because again the server said the kitchen was too busy."], "output": "[['fondue', 'positive'], ['server', 'neutral'], ['kitchen', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Waitress took FOREVER to take our drink order (it was not crowded) and she forgot our chips guac."], "output": "[['drink', 'neutral'], ['chips guac', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Don't miss the creamed spinach, skip the frieeees."], "output": "[['creamed spinach', 'positive'], ['frieeees', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["But the place is so great that patrons don't mind waiting outside rather than go to another restaurant which you can find at least 10 in short walking distance."], "output": "[['place', 'positive'], ['waiting', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The rice was warm and didn't have a hint of vinegar."], "output": "[['rice', 'positive'], ['hint', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["With one drink each, apps, entrees, and three desserts (nothing great) the bill came to $200 for four."], "output": "[['drink', 'negative'], ['entrees', 'negative'], ['bill', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Sure, the burgers are good, but not good enough to make up for the abominable service and disgusting, filthy atmosphere."], "output": "[['burgers', 'positive'], ['atmosphere', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere is nice, food is really worth it, especially for such prices, but service sucks:  I first ordered 2 different martinis and never got the one I asked for;  they brought the wrong dishes -although it was quick!- and then we had to ask for chopsticks to be able to eat our dishes."], "output": "[['atmosphere', 'positive'], ['food', 'positive'], ['prices', 'positive'], ['service', 'negative'], ['martinis', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter was stuffed with attitude and didn't bother explaining things on the menu that he clearly knew we could not understand."], "output": "[['waiter', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is not five star but the prices reflect that."], "output": "[['food', 'negative'], ['prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This has to be the HUGEST steak I've ever seen and the value here is OUTRAGEOUS."], "output": "[['steak', 'positive'], ['value', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Went to Brasserie for restaurant week dinner and maybe it was the menu but the food was very bland and it was something that I could have eatten at home."], "output": "[['dinner', 'neutral'], ['menu', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My advice: go the bathroom at home, and then go to Ginza for EXCELLENT sushi and service."], "output": "[['bathroom', 'neutral'], ['sushi', 'positive'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["About a half hour wait with reservations."], "output": "[['wait', 'negative'], ['reservations', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We stumbled onto this diamond in the rough after our dinner plans at Schiller's were thwarted by a 90 minute wait."], "output": "[['dinner', 'neutral'], ['wait', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Great pizza and heros, without the variety and selection of that star wars-style canteena hipster crowd pizzeria on Bedford (Anna Maria's) but with 5X the flavor."], "output": "[['pizza', 'positive'], ['flavor', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["45 minutes later our less-than-stellar pizza and their even less-than-stellar gnoccho was dropped at the table; no explanation or apology or attempt to acknowledge the ridiculous wait."], "output": "[['pizza', 'neutral'], ['table', 'neutral'], ['wait', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene Service bustles through the energetic, sprawling space with the precision of expert merengue dancers, and everyone else goes along with the flow suggested by the tall, curving ceilings."], "output": "[['Scene Service', 'neutral'], ['space', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went to Sushiden on a Friday night around 8:00, the place was pretty empty, we had reservations, but we didnt need them."], "output": "[['place', 'negative'], ['reservations', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had reserved space one one side of the bar, but when the staff tried to force the Pre-Fixe on all 15 members of the party to stay there, we moved to the other side (the difference in decor was minimal)."], "output": "[['bar', 'neutral'], ['staff', 'negative'], ['Pre-Fixe', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The characters were very entertaining, and while the prices are a little steep, it is well worth the cost."], "output": "[['characters', 'positive'], ['prices', 'negative'], ['cost', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The shrimps looked old and had a sheen to them that you see at an all you can eat buffet at Sizzler."], "output": "[['shrimps', 'negative'], ['buffet', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Chino's has become my new regular Lunch spot after trying their awesome pork sandwhich and calamari salad."], "output": "[['Lunch', 'neutral'], ['pork sandwhich', 'positive'], ['calamari salad', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Don't let the all-Italian menu intimidate; the waitstaff patiently translates each item."], "output": "[['menu', 'neutral'], ['waitstaff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Good food, but they could expand their desert menu."], "output": "[['food', 'positive'], ['menu', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Panini or pizzettes loaded with fresh Italian ingredients such as prosciutto, mozzarella and artichokes make it worth staying for dinner."], "output": "[['Panini', 'neutral'], ['ingredients', 'positive'], ['prosciutto', 'positive'], ['mozzarella', 'positive'], ['dinner', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Mushroom appetizer was doused in a gross mayonnaise like sauce and had not been described that way on the menu."], "output": "[['Mushroom appetizer', 'negative'], ['gross mayonnaise like sauce', 'neutral'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Nonetheless, our waiter gave us prompt service and a smile every time he came over to take an order, bring us drinks, or check up on how we were doing."], "output": "[['waiter', 'positive'], ['service', 'positive'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A bright spot: the server was immeadiately apologetic and whisked problem plates away, and replacements were prompt."], "output": "[['server', 'positive'], ['plates', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We waited FOREVER for a table and when the appetizers arrived they were cold or frozen in the middle!"], "output": "[['table', 'neutral'], ['appetizers', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food Mafrici's approach to modern Italian fare may seem gimmicky: The menu lists eight seasonal ingredients, each prepared as an appetizer, pasta and entree."], "output": "[['menu', 'neutral'], ['ingredients', 'positive'], ['pasta', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The portions are miniscule -- a pasta entree was the size of a small appetizer, we were all hungry at the end of the meal but they certainly supersize the prices."], "output": "[['appetizer', 'negative'], ['meal', 'neutral'], ['prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The ambience is diner-like and the wait staff is rushed, but at these prices, I can't complain."], "output": "[['ambience', 'positive'], ['wait staff', 'negative'], ['prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A sushi chef creating entrees of art that will have you talking as much as eating."], "output": "[['sushi chef', 'positive'], ['entrees', 'neutral'], ['art', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene This vintage Cuban diner, with white acrylic tables, soft Spanish music humming pleasantly in the background and regulars casually hugging the counter, serves some of the cheapest, tastiest fare in the area."], "output": "[['Scene', 'neutral'], ['diner', 'neutral'], ['white acrylic tables', 'neutral'], ['Spanish music', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In Short The weathered bar, well-worn tables, and chipped black paint on the walls give this corner tavern a lived-in feel."], "output": "[['bar', 'neutral'], ['tables', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The bartender was skilled, the owners were very friendly, but the wait for my burrito was longer than I would have liked."], "output": "[['owners', 'positive'], ['wait', 'negative'], ['burrito', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food In a less-than-booming economy, it's a joy to find an East Village bistro with entrees that rarely top 15 bucks."], "output": "[['Food', 'positive'], ['entrees', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["our waitress finally made time to take our order - bread was never brought, water never refilled and wine never got to be ordered - had to ask for everything ourselves."], "output": "[['waitress', 'negative'], ['bread', 'negative'], ['refilled', 'negative'], ['wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Though the crowd is a bit more mature than a typical New York hot spot, if you are looking to impress a classy woman, look know further."], "output": "[['crowd', 'negative'], ['spot', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the service is so-so; our waiter told us there was a table for us, then took us back to the entrance , we then waited another fifteen minutes- confusion seems to reign."], "output": "[['service', 'negative'], ['waiter', 'neutral'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The desserts were both essentially the same, and the service was on the slow side."], "output": "[['desserts', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Lastly the waiters and bartender should learn to have argurments in private and not in front of customers."], "output": "[['waiters', 'negative'], ['bartender', 'negative'], ['private', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Sometimes service was a bit slow, and we had to ask for salads, water, etc a couple of times, but this was all done with good humor and no resentment."], "output": "[['service', 'negative'], ['salads', 'neutral'], ['water', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter, who was missing when we wanted to place our order, hovered over us throughout the meal, as if in a hurry to get us out of there."], "output": "[['waiter', 'negative'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["you go all out with dress, tastes, and performance, and in the end its really about having a good time where you truly indulge yoursef in good vodka, compnay, music, and food."], "output": "[['dress', 'neutral'], ['vodka', 'positive'], ['music', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Also, the waiter wrongly described a wine I had inquired about causing the sommelier to have to make a trip to the table to offer an alternate recommendation."], "output": "[['waiter', 'negative'], ['wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We've been staying in a hotel and Burger Heaven has delievered quite a few meals for us which is 100% better than the hotel food."], "output": "[['meals', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had six different items on the menu (yes, I am a trencherman) and three were simply OUTSTANDING: the steak, the sweetbreads (best I've ever had), and the monkfish liver (also the best I've ever had)."], "output": "[['menu', 'neutral'], ['steak', 'positive'], ['monkfish liver', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had a sit down dinner and cannot tell you how satisfied I was with the quality of service and food."], "output": "[['dinner', 'neutral'], ['service', 'positive'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Intimate dinner upstairs, dessert on the sidewalk as you take in all the nuisance of New York City living are experiences that give a feeling you are doing much more than just dining out."], "output": "[['dinner', 'positive'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The bar downstairs is a lot of fun, so if you get stuck waiting, just have drink."], "output": "[['waiting', 'negative'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My snack was fava bean hummus chips which was the perfect amount to hold me til dinner."], "output": "[['fava bean hummus chips', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["), but our waiter was had a horrible attitude, couldn't remember to bring lemon for our water, or soy sauce for our sushi rolls, the food was wonderful, but unfortunately the service ruined our visit."], "output": "[['waiter', 'negative'], ['soy sauce', 'neutral'], ['sushi rolls', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The ONLY negative was when we asked the waiter to secretly bring birthday cake and some other desserts for the table."], "output": "[['waiter', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Charging full price for half pie toppings, and refusing delivery (1 block) for orders under $20."], "output": "[['price', 'negative'], ['half pie toppings', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter was well versed with the menu and provided us with great service, he didn't hover over the table as some servers tend to do in high end restaurants."], "output": "[['waiter', 'positive'], ['service', 'positive'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I also do not think waiters there are rude- yes there are not friendly and chatty, but do provide great service."], "output": "[['waiters', 'negative'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["if you do though just wait at the bar (yummy drinks!"], "output": "[['bar', 'neutral'], ['drinks', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I was really excited when our waiter read off the list of specials."], "output": "[['waiter', 'neutral'], ['specials', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["At least you have the ambiance and lovely live piano musice being played for you while you wait."], "output": "[['ambiance', 'neutral'], ['live', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["we completed our cocktails long before the waiter brought our starters (which did not come until 30 minutes after we had been seated)."], "output": "[['cocktails', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We did not have reservations so we sat at the small bar with the friendly bartender for 10 minutes."], "output": "[['reservations', 'neutral'], ['bartender', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After waiting 40 minutes for a table and 30+ for our entrees, our waiter was distracted."], "output": "[['waiting', 'neutral'], ['table', 'neutral'], ['entrees', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My only complaints are the less spectacular sides and menu items other than steak."], "output": "[['sides', 'negative'], ['menu', 'negative'], ['steak', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiters are sometimes grouchy and the decor doesn't change, but the food is always delicious and satisfying."], "output": "[['waiters', 'negative'], ['decor', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Be warned though, this plaice gets packed at lunch - and the service can be rottenly slow-going."], "output": "[['lunch', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene North Square's discreet, sedate decor appeals to the largley older crowd occupying the dining room whilst a younger set parties in the back bar."], "output": "[['Scene', 'neutral'], ['decor', 'positive'], ['crowd', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were never offered dessert because our waiter spent about 20 minutes at the bar calculating the checks instead."], "output": "[['dessert', 'neutral'], ['waiter', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter poured our wine into my water glass, rolled his eyes when I asked for a new water, and definitely didn't offer to comp the wasted glass of wine."], "output": "[['waiter', 'negative'], ['water glass', 'neutral'], ['glass of wine', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The actors try to draw your attention away from the better stuff that is happening below."], "output": "[['actors', 'neutral'], ['stuff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["for ANYONE to come and take our dessert order (we had previously seen our waitress going outside for a cigarette break and never coming back)."], "output": "[['dessert', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["food was just ok,, to many high end places in such a cool lower east side neighborhood,like prune and apizz, prices to high in these places for this hood."], "output": "[['food', 'positive'], ['prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The rest of the meal was good, but a little over priced for Chinese take out style food."], "output": "[['priced', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Went to Spice Restaurant for dinner and loved my meal."], "output": "[['dinner', 'neutral'], ['meal', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I am not one to waste dessert but we threw away the box after taking a few bites of it."], "output": "[['dessert', 'neutral'], ['box', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitstaff chatted at the bar amongst themselves and completely ignored us for the entire meal-- which took some work, as the place is small enough with the garden closed!"], "output": "[['waitstaff', 'negative'], ['bar', 'neutral'], ['garden', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["never had a bad pizza, the staff has always been friendly, if not overly solicitous, and the only downside is the occasional wait on line outside."], "output": "[['pizza', 'positive'], ['staff', 'positive'], ['wait', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Well, no secret that a brunch here on Saturday or Sunday will be a long wait - but once you bite into those pancakes, it will have been worth every minute."], "output": "[['brunch', 'neutral'], ['wait', 'negative'], ['pancakes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["He hooted and hollered -- and told every staff person at the bar, not to serve us."], "output": "[['staff', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went for lunch yesterday and had a lovely time."], "output": "[['lunch', 'neutral'], ['time', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The decor has not quite made the transition--some really nice artifacts are still there, but there are several layers of different remodeling efforts visible."], "output": "[['decor', 'negative'], ['artifacts', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While the food is terrific, you must overlook the often apathetic service, and the sometimes downright rude Manager that seats people."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When we got up to leave and the waiter tried to charge us 18% for the two mediocre apetizers and one drink they did serve us."], "output": "[['waiter', 'negative'], ['apetizers', 'negative'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They later told us that our waiter had to fix the 'computer' - that was the reason he couldn't bring us our drinks."], "output": "[['waiter', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Thin crust, lots of sauce and very little cheese, it's not your typical Sicilian slice of pizza, but can't explain why I have a hard time eating less than 4 of those babies!"], "output": "[['crust', 'positive'], ['Sicilian slice of pizza', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Basically the comfort is lacking but the food is the focus."], "output": "[['comfort', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After the wine experience, I actually expected worse than what was served."], "output": "[['wine', 'neutral'], ['served', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Patrons are a mix of pre-theater and local regulars whose relaxed laughter and gesturing conversations add much to the restaurant's flavor."], "output": "[['Patrons', 'neutral'], ['pre-theater', 'neutral'], ['flavor', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The manager came over to our table at the end of our entree course to get our review."], "output": "[['manager', 'positive'], ['entree', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I let the waiter know and he offered me a free dessert."], "output": "[['waiter', 'positive'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food Despite the restaurant's name, the menu is remarkably Atkins-friendly, from the nibble bowls of spicy fried chickpeas to the grilled slabs of salt-flecked, smoky rib-eye, succulent chunks of rosemary roast chicken and fat tubes of springy grilled squid."], "output": "[['Food', 'neutral'], ['menu', 'positive'], ['bowls', 'neutral'], ['rosemary roast chicken', 'neutral'], ['springy grilled squid', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If she was a bit more sophisticated, she wouldn't have been impressed with the list, but rather with the clientele and atmosphere."], "output": "[['list', 'negative'], ['atmosphere', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The raw bar that we were served was abyssmal, and our dinners of salmon (mine overcooked) and chicken (hers, very bland) weren't much better."], "output": "[['bar', 'neutral'], ['served', 'negative'], ['dinners of salmon', 'negative'], ['chicken', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I'd say the menu is generally below-average for the neighborhood, but if you want a burger, this is the place to go."], "output": "[['menu', 'negative'], ['burger', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The porterhouse is as good a steak you are going to find in NYC or the surrounding area."], "output": "[['steak', 'positive'], ['area', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter was not attentive he gave me the wrong drink twice and the bill for three people who had appertizers, a drink and an entree was $200."], "output": "[['waiter', 'negative'], ['entree', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I didn't realize how good the food was until I went for dinner the other night."], "output": "[['food', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A dining beacon in an otherwise residential 4 or 5 block radius, Sorrel pleases on every course--from the cold spicy tomato soup and beet salad starters to the delectable skate, the scallops, or steak tartare, straight through to the strange but tasty melon soup or flan-esque orange-and-caramel custard (so bad with names)."], "output": "[['dining', 'neutral'], ['tomato soup', 'positive'], ['beet salad', 'neutral'], ['scallops', 'positive'], ['steak tartare', 'positive'], ['melon soup', 'positive'], ['orange-and-caramel', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene The bright mix of colors painted on the cafe's walls matches the vivid margaritas that sit on nearly every table and litter the sceney bar."], "output": "[['mix', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["At best, it's a mediocre restaurant, forget about the fish variety, I asked for Char (A sushi staple), and received a blank look from the waiter, same fish here as any grocery store."], "output": "[['sushi', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Didn't like having to flag down waiters for drinks, nor having to wait almost 15 minutes for a check after asking two servers."], "output": "[['waiters', 'negative'], ['drinks', 'neutral'], ['servers', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The bar's waitresses seem to have a sixth sense for when customers have reached the bottom of a drink or are scratching their forks against empty plates."], "output": "[['bar', 'neutral'], ['waitresses', 'positive'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Just walking past this establishment during dinner hours will make you dream of garlic empowered sauce covering a tender veal cutlet."], "output": "[['dinner', 'neutral'], ['garlic empowered sauce', 'positive'], ['veal cutlet', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The place was bustling at 8:30pm on a Wednesday night- we arrived earlier than our reservation and got situated at the bar."], "output": "[['place', 'negative'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Later two waiters decided to bodyguard our table; when my fork hits the plate it's snatched away."], "output": "[['waiters', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Drinks were well priced and the buyback rate was fantastic."], "output": "[['Drinks', 'neutral'], ['priced', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["However when I returned to my table the waiter immediately came over and said So I guess we are celebrating a birthday here."], "output": "[['table', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I spent more time looking for a waiter than I did enjoying my meal."], "output": "[['waiter', 'negative'], ['meal', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was simple but exploded with flavor and the presentation was as if it was out of a cook book."], "output": "[['food', 'neutral'], ['flavor', 'positive'], ['presentation', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After arriving for a pre-theatre reservation to find the kitchen closed due to a mechanical failure, the problem was fixed an hour later (after many drinks at the bar, none of which management offered as a concession to the wait) and we were served a very good dinner in time to make the play."], "output": "[['bar', 'neutral'], ['management', 'negative'], ['wait', 'neutral'], ['served', 'neutral'], ['dinner', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Brunch at Cafe des Artistes was hands down the most terrible dining experience I have had in New York."], "output": "[['Brunch', 'neutral'], ['dining', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Got the check tossed on table 10 minutes after being served and hostess came by to rush us some more."], "output": "[['served', 'neutral'], ['hostess', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["i always get the apple pie, but the past two times i visited, the waiter burnt the pie while he was supposed to warm it up."], "output": "[['apple pie', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Sometimes, the take-out and seating lines can be long, but the staff help move things along."], "output": "[['take-out', 'neutral'], ['seating lines', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My favorite was the apple dessert, which came with little squares of pear and apple jelly."], "output": "[['apple dessert', 'positive'], ['apple jelly', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food An ideal meal here starts with lusty, cheese-encrusted onion soup or a salad of frisee and bacon capped with a soft-poached egg."], "output": "[['Food', 'neutral'], ['meal', 'positive'], ['salad of frisee', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["calle ocho is definitely high on my list, the food and mojitos are excellent (the sangria is a miss, flor de sol has much better sangria) but the service leaves much to be desired."], "output": "[['calle', 'positive'], ['food', 'positive'], ['mojitos', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Entree choices seem endless--braised beef, pounded chicken, garlic shrimp, poblano chile, hanger steak-- the platter of subtly spiced pulled pork, served with whipped plaintains, is the restaurant's best."], "output": "[['Entree', 'positive'], ['braised beef', 'neutral'], ['pounded chicken', 'neutral'], ['garlic shrimp', 'neutral'], ['served with whipped plaintains', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Order ended up being double the price of a normal lunch."], "output": "[['price', 'negative'], ['lunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I must admit that when my friend said we were going to Astoria for dinner, I expected a diner sytle restaurant, where the decor, food and service would not suffice."], "output": "[['dinner', 'neutral'], ['diner', 'neutral'], ['decor', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["But, as I said, it's a dive bar, so it's not someplace you'd take a high-maintenance individual."], "output": "[['bar', 'neutral'], ['individual', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service is disorganised, no one gave us a menu for 15 mins once we were seated, but after that it went smoothly enough but no where near the stella performance of many half as pretensious restaurants."], "output": "[['service', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For appetizers try the tuna carpaccio with wasabi creme fraiche, lobster tempura with tarter sauce."], "output": "[['appetizers', 'neutral'], ['tuna carpaccio with wasabi creme fraiche', 'positive'], ['lobster tempura with tarter sauce', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For $19 in a place that specializes in breakfast I did expect perfect eggs benedict."], "output": "[['breakfast', 'neutral'], ['eggs benedict', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have lived in Japan for 7 years and the taste of the food and the feel of the restaurant is like being back in Japan."], "output": "[['taste', 'positive'], ['food', 'neutral'], ['feel', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When the group arrived for the Noon lunch the restaurant was only partially set up and the group was forced to eat lunch while the staff noisily set up the restaurant around them."], "output": "[['Noon lunch', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you think the prices are outrageous, just take the family, enjoy the ride and go in and order a few appetizers as prelude to a real dinner."], "output": "[['prices', 'negative'], ['family', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Service was friendly, but not terribly attentive, took 30 minutes after dinner to clear our plates, and another 20 to get our check."], "output": "[['Service', 'positive'], ['dinner', 'neutral'], ['plates', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I was NOT told this before when I made the reservation and explained to the manager RICHARD who has the poorest customer service ever and rude and said he didn't believe me."], "output": "[['reservation', 'neutral'], ['manager', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Only problem was - an older gentleman (well-dressed but a little enebriated) chose to sit down right next to me - despite the fact that all 15 other seats were free - order himself a martini, and then describe how dry and dissapointing the burger was when he ordered it a few days ago."], "output": "[['gentleman', 'negative'], ['seats', 'negative'], ['martini', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the only things u could really taste are the very salty soy sauce (even its low sodium), the vinegar-soaked rice, and the scallion on top of the fish."], "output": "[['soy sauce', 'negative'], ['scallion', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Desserts are showstoppers, namely the caramelized banana tower with toasted marshmallows in a tall hazelnut shell."], "output": "[['Desserts', 'positive'], ['shell', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have to agree with the previous review that the atmosphere isn't much, but Mister Falafel can't be beat for quick, delicious, cheap takeout."], "output": "[['atmosphere', 'negative'], ['Falafel', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the place looks cool, but the food is not really that good."], "output": "[['place', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Its a sicilian slice made with freshly grilled veggies which lie on top of a sumptous tomato sauce."], "output": "[['sicilian slice', 'neutral'], ['grilled veggies', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Overall, the food makes up for what is missing in the ambience and service."], "output": "[['food', 'positive'], ['ambience', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I really like the decor and it made it feel like I was having drinks at a mansion."], "output": "[['decor', 'positive'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Best steak i have ever tasted in my life, the side dishes are amazing as well as the bread basket they put out that could be a meal in its self."], "output": "[['steak', 'positive'], ['side dishes', 'positive'], ['bread', 'positive'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The portions are miniscule and the size of an entree could be half-and appetizer if even that large."], "output": "[['portions', 'negative'], ['entree', 'neutral'], ['appetizer', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter disappeared entirely, our food, when we were finally able to order it, arrived without plates (we had to go and track down a busboy to get them), and when we were finished, we couldn't get the check, even after walking across the restaurant to request it."], "output": "[['waiter', 'negative'], ['food', 'neutral'], ['plates', 'neutral'], ['check', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There is actually space to breathe and the decor sets the tone for an intimate dinner."], "output": "[['space', 'neutral'], ['decor', 'positive'], ['dinner', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I've been accustomed by the restaurant group's great service, so I was disappointed by the long wait for my lunch."], "output": "[['service', 'positive'], ['wait', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After making reservations almost a month in advance, I was very disappointed to be seated in a secluded area for dinner next to the sushi bar and KITCHEN!!!!!!!"], "output": "[['reservations', 'neutral'], ['seated', 'negative'], ['sushi bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The brightly-lit takeout spot with a few non-descript tables and chairs looks like any other, but it tastes ten times more homespun."], "output": "[['takeout spot', 'positive'], ['tables', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The owner and staff are all Japanese as well and that adds to the entire ambiance."], "output": "[['owner', 'neutral'], ['staff', 'neutral'], ['ambiance', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["you may have to wait a bit for service but you will not be disappointed with the food."], "output": "[['service', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I dined there on a Wednesday night, the restaurant was practically empty, and we had to ask our waiter for everything, the menu, more water, the check, etc."], "output": "[['waiter', 'negative'], ['menu', 'neutral'], ['water', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had dinner with a few of my friends, and it was the best we've had in a long time."], "output": "[['dinner', 'positive'], ['time', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Though you will undoubtedly be seated at a table with what seems like barely enough room (no matter what the size of your party), the warm atomosphere is worth the cramped quarters- you'll have fun and forgot about the tight spot you're in."], "output": "[['table', 'neutral'], ['room', 'negative'], ['spot', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Free edamame (nice perk) and we ordered four rolls between the two of us, and each of us had a drink."], "output": "[['edamame', 'positive'], ['rolls', 'neutral'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["but the wait for seating can be exasperating."], "output": "[['wait', 'negative'], ['seating', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Sometimes when I come home from work I stop at the bar to have a plate of oysters and something delicious for dinner."], "output": "[['bar', 'neutral'], ['plate of oysters', 'neutral'], ['dinner', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While the space is exceptionally small and the seating can be uncomfortable, the food is well worth the few inconveniences."], "output": "[['seating', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service is excellent and always informative without an air."], "output": "[['service', 'positive'], ['air', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had afternoon tea which featured a pot of tea and several pastries and tea sandwiches, all of which were delicious."], "output": "[['afternoon tea', 'positive'], ['pot of tea', 'neutral'], ['pastries', 'positive'], ['tea sandwiches', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After the bar, they sat us on the side with the wine room with a nice view of everything."], "output": "[['bar', 'neutral'], ['view', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitress interrupted us halfway through our meal to say that if we wanted dessert we had to order it then, because the kitchen wanted to close."], "output": "[['waitress', 'negative'], ['meal', 'neutral'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Yet the maitre d still sat us next to the bar."], "output": "[['maitre', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Lobster bisque is a 10+ and Steaks ; fish and cajun shrimp app are standouts!"], "output": "[['Lobster bisque', 'positive'], ['Steaks', 'neutral'], ['fish and cajun shrimp app', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A few of us went the other night for cocktails (half price!)"], "output": "[['cocktails', 'neutral'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went on a saturday and the atmosphere was no more exciting than eating dinner at home."], "output": "[['atmosphere', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The staff treated them like true royalty."], "output": "[['staff', 'neutral'], ['royalty', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The salad I received was Iceberg lettuce with nothing else in it (no tomatoes, carrots)."], "output": "[['salad', 'neutral'], ['Iceberg lettuce', 'neutral'], ['carrots', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The dinner lasted about 3 hours, that waiter continued to refill our water even though we finished the whole meal(including desserts) an hour and half before."], "output": "[['dinner', 'neutral'], ['waiter', 'negative'], ['meal', 'neutral'], ['desserts', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["And the owner didnt seem to care, she was more interested in talking at the bar than hearing from me."], "output": "[['owner', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food was good, but not worth the wait."], "output": "[['Food', 'positive'], ['wait', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went there for Easter Dinner and the pork chops were quite tasty."], "output": "[['Dinner', 'neutral'], ['pork chops', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The ribs are a second runner up, poo poo platters are never out of style."], "output": "[['ribs', 'neutral'], ['poo platters', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you want peace quiet, ambience and patient service, go elsewhere."], "output": "[['ambience', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Their appetizer portions are not huge, just right since the entrees are much larger."], "output": "[['appetizer portions', 'negative'], ['entrees', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["i took another 45 minutes so i called back the waiter and said that if the food was ready now ill just pay for it."], "output": "[['waiter', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The bar is also a must after dinner: have a raspberry martini!"], "output": "[['bar', 'positive'], ['dinner', 'neutral'], ['raspberry martini', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the food tastes like home cooking."], "output": "[['food', 'neutral'], ['cooking', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There is no way the food and service here are worth the prices they charge."], "output": "[['food', 'neutral'], ['prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Meal was acceptable, Lamb was tough although rare like I asked, green beans were overcooked, my girlfriend ordered steak frites rare, came medium, steak was tough, lots of nerves,steak au poivre sauce was mediocre."], "output": "[['Meal', 'positive'], ['Lamb', 'negative'], ['steak frites', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Super friendly neighboorhood atmosphere where even a lady can go alone and have a drink and feel comfortable."], "output": "[['atmosphere', 'positive'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The last time I went to the restaurant, the waitress made me wait to take my order, then left me without anything to drink throughout the entire meal."], "output": "[['waitress', 'negative'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Blue Ribbon Sushi has far more than a cult following, packed daily from Noon till 3 AM, with hipsters, celebrities, Sashimi Lovers, and of course SOHO locals, it's breath taking menu, Superb Fare, Lengthy Sake List, and pro seating system have earned it a 5 STAR rating with The Sushi Times: 6 years running."], "output": "[['Ribbon Sushi', 'positive'], ['Sashimi', 'positive'], ['menu', 'neutral'], ['Fare', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The sandwiches from the take out window are delicious too."], "output": "[['sandwiches', 'positive'], ['take out window', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For far better fish at the same price (but less interesting roll combinations), try Yama, just around the corner."], "output": "[['fish', 'positive'], ['price', 'neutral'], ['roll', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Steer away from the parmesan fries (they use powdered parmesan), their house wine selections, and mixed drinks (there's no alcohol in them!!!)"], "output": "[['parmesan fries', 'negative'], ['house wine selections', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The duck burrito with mole sauce is out of this world and the prices are definitely affordable $12-16 for most entrees."], "output": "[['duck burrito with mole sauce', 'positive'], ['prices', 'positive'], ['entrees', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene Inconspicuous Bottino is an ideal stop for a light lunch or full dinner while gallery-hopping through Chelsea."], "output": "[['Scene', 'neutral'], ['lunch', 'positive'], ['dinner', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although the cheesecake didn't taste like cheescake and the homefires were horrible, overall my friends love this place and they love the food."], "output": "[['cheesecake', 'negative'], ['homefires', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have been there for dinner as well and one would think that if you pay more for dinner than the buffet you would get better quality food from the tandoor."], "output": "[['buffet', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter disappeared after dropping off the food so I had no choice but to eat it as is."], "output": "[['waiter', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In addition, our waiter seemed to have short-term memory loss because he kept forgetting to bring us our drink order even after I asked him on three separate occasions."], "output": "[['waiter', 'negative'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you're a meat eater, try the mixed grill of two types of Chicken, two types of Lamb and grilled shrimp, served on a sizzling platter with onions and peppers."], "output": "[['meat', 'neutral'], ['mixed grill', 'positive'], ['platter with onions', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It was the WORST Sangria ever, and their house drink has just a shot of Malibu rum, and at a price of $9 you want more than a shot of a 40% alcohol."], "output": "[['Sangria', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["servers never ONCE asked how we were doing - they brought out food late and if extra additions were requested, they came out 20 min after."], "output": "[['servers', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I live around the corner and I miss the unpretentious and always lovely, Irving on Irving, that used to occupy this space where you didn't need a reservation three weeks in advance to eat dinner after 5:30 and before 11 pm."], "output": "[['space', 'positive'], ['reservation', 'neutral'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When the food arrived, the portions were really small, and didn't really reflect the awesome descriptions on the menu."], "output": "[['food', 'neutral'], ['portions', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Then the manager said, hey we'll give you shrimp instead, which would have taken another hour."], "output": "[['manager', 'negative'], ['shrimp', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Drinks are a bit pricey ($10-12) but delicious - no wine is less than $10/glass either."], "output": "[['Drinks', 'positive'], ['wine', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["probably not worth the wait on the weekend when pomodoro is a block away but worth getting for delivery if you are in the area or for dinner during the week."], "output": "[['wait', 'negative'], ['delivery', 'neutral'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The bar bites weren't anything special (we had calamari and wings, very ordinary), but our dinner was phenomonal, as was our service."], "output": "[['bar bites', 'neutral'], ['calamari', 'neutral'], ['dinner', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Come hungry but be careful not to order too large an appetizer because it would be a shame to waste their scallion pancakes because you've gotten too full prematurely."], "output": "[['appetizer', 'positive'], ['scallion pancakes', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["ambience and decoration was nice but for a check of $330 for 5 for brunch and with just average food."], "output": "[['ambience', 'positive'], ['decoration', 'positive'], ['brunch', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Here's how it works: you walk in, sit down, and have a vegetarian thali (group of little portions of curries) that invariably includes lentiles, a small salad, some rice, some kind of samosa-like pastry, yogurt, rice, and a couple of sauces."], "output": "[['portions', 'negative'], ['yogurt', 'neutral'], ['sauces', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["And I'm saying that dinner has actually taken about an hour more than it should, just because of the slow service."], "output": "[['dinner', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We actually enjoy eating there earlier for lunch definatly a more relaxed atmosphere."], "output": "[['lunch', 'neutral'], ['atmosphere', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you like a cleaner (more generic) flavor then other places may provide the norm."], "output": "[['flavor', 'positive'], ['norm', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The prices were moderate for fine dining, and although the restaurant is relatively small, it was easy to have a quiet conversation even though the tables are fairly close together."], "output": "[['dining', 'positive'], ['tables', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter took my boyfriend's order, snatched away the menus and stormed away from the table without even looking at me."], "output": "[['waiter', 'negative'], ['menus', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["this guy should work in a dinner ,didn't even know the menu ,he couldn't explain me anythings ,a real nightmare."], "output": "[['guy', 'negative'], ['dinner', 'neutral'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The place is plain as well: forget about Nobu-style ambiance, Bond-like music and bar, Next door Nobu good-looking crowds etc - just plain, got it?"], "output": "[['place', 'negative'], ['bar', 'neutral'], ['crowds', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["my husband has certain food allergies, and they were 100% accomodating even for the tasting menu which is seven courses for $50 - they even substituted dishes for ones that he couldn't have."], "output": "[['food', 'neutral'], ['menu', 'positive'], ['dishes', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu looked good, except for offering the Chilean Sea Bass, but the server does not offer up the specials that were written on the board outside."], "output": "[['menu', 'positive'], ['Chilean Sea Bass', 'negative'], ['server', 'negative'], ['specials', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The lamb was wonderful, although I could do without all the beans."], "output": "[['lamb', 'positive'], ['beans', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Go there for dinner this time and find it unusually bad in taste and not pleasent service at all."], "output": "[['dinner', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Good Italian spot, but should raise the bar on the food before some newcomers challenge its standings."], "output": "[['spot', 'positive'], ['bar', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Basic facts: sub-par limited menu; poorly made drinks; random crowd; and a waitress (although entertaining) that was doing shots behind the bar."], "output": "[['waitress', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We waited 15 minutes for a menu, another 20 for a tea, another 15 for an appetizer, then when the plates came out, the waitress had to ask me what I'd ordered."], "output": "[['menu', 'neutral'], ['tea', 'neutral'], ['appetizer', 'neutral'], ['plates', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["go there and get really good food, just don't expect to get out of there quickly and when the server comes to your table ask for everything you'll be needing for the rest of the evening."], "output": "[['food', 'positive'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I dined in the Main Dining Room which is surrounded by authentic Spanish decorations."], "output": "[['Main Dining Room', 'neutral'], ['decorations', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The place was jumping on a Mon nite, as was the bar, but with a nice mixed crowd."], "output": "[['bar', 'neutral'], ['mixed crowd', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My only suggestion would be to avoid long waits for food by adding extra servers when there are large groups."], "output": "[['food', 'neutral'], ['servers', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene The windowed bar and front waiting area seems bright and airy compared to the somewhat stuffy main room."], "output": "[['Scene', 'neutral'], ['windowed bar', 'positive'], ['front waiting area', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I ordered the Prix Fixe Pasta while my husband and children ordered from the menu - we were all happy with our choices."], "output": "[['Prix Fixe Pasta', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Beers on tap were pretty good and we had a great waiter but the food left much to be desired."], "output": "[['tap', 'neutral'], ['waiter', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Trendy decor doesn't make up for the avg food, adequate service and relatively high prices."], "output": "[['avg food', 'negative'], ['service', 'positive'], ['prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They took 10 minutes to refill our water, they never asked if we would like another drink, and the waiter was nice but just not efficient."], "output": "[['drink', 'neutral'], ['waiter', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had the lentils and cous cous for lunch the next day because my friend and I had appetizers before our entrees-- portions are pretty decent for the price, and tasty to boot."], "output": "[['lunch', 'neutral'], ['appetizers', 'neutral'], ['entrees', 'neutral'], ['portions', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In summer, the small outdoor garden is an ideal place to sip coffee while reading under a canopy of trees and sky."], "output": "[['outdoor garden', 'positive'], ['coffee', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went there for lunch with my mom, it was just excellent, the sole and cremed spinach dish I had was divine."], "output": "[['lunch', 'neutral'], ['sole', 'positive'], ['spinach dish', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Before our food arrived I asked our waitress if we could be moved and she just stared blankly at me."], "output": "[['food', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter just slapped my food down and then never returned until he slapped my check down."], "output": "[['waiter', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The only thing that I was unhappy about was that one time, the restaurant received a delivery of supplies and the rolled it in through the dining area into the back kitchen, with the deliverymen shouting loud things to each other in chinese."], "output": "[['dining area', 'neutral'], ['back kitchen', 'neutral'], ['deliverymen', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["One gentleman ignored us most of the time and would plunk the coffee down and spill it on the table without saying a word."], "output": "[['gentleman', 'negative'], ['coffee', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Waterview is one of the best diners I've evr been to interms of the quality and taste of the food."], "output": "[['diners', 'positive'], ['quality', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The scene is reasonably cool but unworth more than a drink."], "output": "[['scene', 'positive'], ['drink', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["1 hour for water, 1 hour for drinks, 1 hour for food, as you can see we were there for almost 5 hours before our bill came, not for enjoyment but pure frustration."], "output": "[['water', 'neutral'], ['drinks', 'neutral'], ['food', 'neutral'], ['bill', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere was really nice and inviting but our waiter was awful!"], "output": "[['atmosphere', 'positive'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["As soon as he sat, a waiter came over not once but twice, the first time to suggest he move to the bar b/c our large booth didn't accomodate an extra person, the second time to insist he move."], "output": "[['waiter', 'negative'], ['bar b/c', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My favorites are the chili seared shrimp appetizer, Macadamia chicken salad, yukon gold potato dumplings, maple turkey breast wrap, seared yellowfin tuna burger and for dessert you have to do the lemon ribbon pie (if you're a fan of ice cream) or for the wintery months, the healthy pumpkin pie made with tofu."], "output": "[['chili seared shrimp appetizer', 'positive'], ['maple turkey breast wrap', 'positive'], ['yellowfin tuna burger', 'positive'], ['dessert', 'neutral'], ['ice cream', 'positive'], ['tofu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Warning, you are supposed to order multiple dishes, so if you order just an entree per person you probably won't have enough."], "output": "[['dishes', 'positive'], ['entree', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have seen the crowd go from ultra hip to BT and I still love it becuause of the food."], "output": "[['crowd', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Alongside the USDA prime dry-cut steaks, the menu features standard steakhouse fare: appetizers like shrimp cocktail, fresh oysters and clams, an array of salads, soups, pastas and vegetable sides, and non-steak entrees like lamb, veal and pork chops, lobster and more."], "output": "[['USDA prime dry-cut steaks', 'neutral'], ['menu', 'positive'], ['soups', 'neutral'], ['pastas', 'neutral'], ['vegetable sides', 'neutral'], ['lamb', 'neutral'], ['veal and pork chops', 'neutral'], ['lobster', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were crammed next to the people who were seated to the right of us, who repeatedly took phone calls during dinner, while the rude wait staff did nothing despite the warning on the menu that cell phones were not to be used in the dining room."], "output": "[['dinner', 'neutral'], ['wait staff', 'negative'], ['menu', 'neutral'], ['dining room', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["No extra pickles, no AC, no ice water, slow service, the whole thing was just dissapointing."], "output": "[['water', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["No bread basket for the table, the server came around with a basket and we each got 1 piece of bread."], "output": "[['table', 'neutral'], ['server', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the soups were superb and only $2 a bowl, and the entire dinner, with beers, cost less than $30 for two people."], "output": "[['soups', 'positive'], ['bowl', 'neutral'], ['dinner', 'neutral'], ['beers', 'neutral'], ['cost', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["However the manager came over and aplogized and all drinks were on him."], "output": "[['manager', 'positive'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service always ruins your food if it's poor."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had: *Soup, forget what kind but it was great *Appetizer-Snails in garlic sauce, which was so good, we confused the snails for mushrooms *Entrees - We had the duck confit lamb shank."], "output": "[['garlic sauce', 'positive'], ['mushrooms', 'neutral'], ['duck confit lamb shank', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Chef Shea Gallante takes up residence in the former kitchen of Waxman, now walled off from the diners but visible through glass service doors."], "output": "[['Chef', 'positive'], ['kitchen', 'neutral'], ['diners', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Pink Pony's brunch is among the very best in the city!"], "output": "[['Pony', 'neutral'], ['brunch', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The bar is available while you waiting for the table, the DJ is nice."], "output": "[['bar', 'neutral'], ['DJ', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Ofcourse the restaurant is new and perhaps they have some kinks to work out, but it for the same price you can get a higher caliber brunch at Banania or Cafe Luluc on Smith St."], "output": "[['price', 'neutral'], ['brunch', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When we got there (6 women), we were not even allowed in when a staff member with a bad attitude wearing a suit told us that we absolutely needed a reservation (yes, we've gone from an artsy community to this)!"], "output": "[['staff member', 'negative'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["BBQ is ordinal, and cole slaw is not even worth trying."], "output": "[['BBQ', 'neutral'], ['cole slaw', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It's cheesy, great herbs,good bread and large slices But it's in a very dirty area, good for take out and bring it home kind of place."], "output": "[['herbs', 'positive'], ['bread', 'positive'], ['area', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The only problem my party found was that when people asked for knives and forks (there were only chopsticks on the table) the waitress laughed at them."], "output": "[['chopsticks', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Waitress was unenthusiastic and refilled my water only after I asked her to but did not refill my date's empty water glass?!?!?"], "output": "[['Waitress', 'negative'], ['water glass', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The worst occasion, and the final straw for me was when myself and four friends were told that we could have a table if we moved away from our stools at the bar."], "output": "[['final straw', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Staff dissappeared after 2PM and we had to send a search party to find our waitress who was parked at a table upstairs reading a newspaper."], "output": "[['Staff', 'negative'], ['waitress', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Warning Service is decent, but it takes forever to get the check."], "output": "[['Service', 'positive'], ['check', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["PS : to the waitresses and waiters at Shanghai Cafe(new name of Shanghai Gourmet) if you don't like your job, don't work there."], "output": "[['waitresses', 'negative'], ['waiters', 'negative'], ['Shanghai Gourmet', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went to Joy hoping to find some great Indian, but unfotunately found curry that was no better than average."], "output": "[['Indian', 'positive'], ['curry', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["i recently had brunch at the new hill diner let me tell you it was great."], "output": "[['brunch', 'positive'], ['diner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although the mediterreanian plate was delicious, it was NOT what I'd expect from a tea salon."], "output": "[['mediterreanian plate', 'positive'], ['tea salon', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My wife and I had an 8:30 reservation, we show up a few minutes before and the host mumbles something to us about waiting at the bar and they'll tell us when the table is ready."], "output": "[['reservation', 'neutral'], ['host', 'negative'], ['waiting', 'neutral'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Little Italy-style hambone performances by the waiters (actually saying fugettaboutit 4 times during specials) was embarassing and did nothing to hide the fact of of being charged for 4 bottles of wine when we only ordered 3."], "output": "[['waiters', 'negative'], ['specials', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The miso soup lacked flavor and the fish was unfortunately not as well prepared as in the past."], "output": "[['miso soup', 'neutral'], ['flavor', 'negative'], ['fish', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the food sucked straight up looks like a nice place to go out with date and have a couple of drinks."], "output": "[['food', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The baked penne came out in a small bowl, burnt with barley any sauce for $18."], "output": "[['baked', 'neutral'], ['sauce', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["it did fill up pretty quickly for lunch, but nobody seemed to have to wait too long, and i'm guessing they might be less busy for dinner."], "output": "[['lunch', 'neutral'], ['wait', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Helpings are HUGE and most come with choice of rice and beans, or salad and plantains."], "output": "[['Helpings', 'positive'], ['rice', 'neutral'], ['beans', 'neutral'], ['salad', 'neutral'], ['plantains', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["fresh home-made tomato sauce with chunks of awesome tomatoes fire it all up in a brick oven."], "output": "[['home-made tomato sauce', 'positive'], ['chunks of awesome tomatoes', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Main dishes - Vindaloo chicken OK, massive hunk of lamb decent."], "output": "[['Main dishes', 'neutral'], ['Vindaloo chicken', 'neutral'], ['lamb', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Prices are not cheap, but not expensive but the meal is worth every penny."], "output": "[['Prices', 'negative'], ['meal', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The only downside was the service was slow and our waitress kept forgetting to bring our drinks."], "output": "[['service', 'negative'], ['waitress', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They have samosas, chicken tikka masala, and a lot of other dishes you can think of."], "output": "[['chicken tikka masala', 'neutral'], ['dishes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When you order a ploughman's lunch you don't even get bread (which confounded me) and the mini yorkshires were dry as a bone."], "output": "[['lunch', 'neutral'], ['mini yorkshires', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The decor and the service definitely is not the greatest, but I can overlook those things since their food is just so damn good."], "output": "[['decor', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The best thing though was when they messed up the fish order they not only gave us each a free glass of wine, but they took that fish order off our bill!!!"], "output": "[['glass of wine', 'positive'], ['bill', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although Nobu requires a 2-3 month advanced reservations, it's worth the wait!"], "output": "[['reservations', 'neutral'], ['wait', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu offers favorites from all over China: mellow Lake Tung-Ting shrimp from Hunan; peppery Sichuan tofu with minced pork; and Shanghainese soups with pickled mustard greens."], "output": "[['menu', 'neutral'], ['Tung-Ting shrimp', 'positive'], ['Sichuan tofu with minced pork', 'positive'], ['soups', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Upstairs they have an entirely separate hostess, as if it was a different restaurant all together, where after being asked once again if we had a reservation we were seated in a small seat, in the corner, of a practically empty room."], "output": "[['hostess', 'negative'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They bought the same surly staff, it still took way too long for food, drink, ANY SERVICE and the food is still $ 12."], "output": "[['surly staff', 'negative'], ['drink', 'neutral'], ['SERVICE', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was average; I could have had a better meal at the local pizza place."], "output": "[['meal', 'positive'], ['pizza place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Once the manager loudly referred to the customers patiently waiting at the all-you-can-eat buffet line as 'hungry animals attacking for food'"], "output": "[['manager', 'negative'], ['waiting', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We ordered coffee, and then he ordered a bacon cheeseburger (for $12, ridiculous even for New York) The waiter then announced he was going to charge us a $4 sharing charge."], "output": "[['coffee', 'neutral'], ['bacon cheeseburger', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Get plenty on food for the price."], "output": "[['food', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Coffee, treats, and the best of eerything."], "output": "[['Coffee', 'neutral'], ['treats', 'neutral'], ['eerything', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["And that is a shame as the restaurant is a pizzeria with a very limited menu outside of pizza."], "output": "[['menu', 'negative'], ['pizza', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had to flag down the waiter even to refill water glasses!"], "output": "[['waiter', 'negative'], ['water glasses', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["On each table there's a variety of sauces and spices, which you're encouraged to add to your dish; by the end of the meal you mind up with something completely different in your bowl from you started, but it will still be so satisfying."], "output": "[['variety of sauces', 'neutral'], ['spices', 'neutral'], ['dish', 'neutral'], ['meal', 'neutral'], ['bowl', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Cocktails were ok, not so good with chinese food so hot tea was fine for us."], "output": "[['Cocktails', 'positive'], ['chinese food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter ignored us for ten minutes, the restaurant was empty, got our drink orders wrong, got one main dish order wrong and the disappeared for another ten minutes before we could get the check."], "output": "[['waiter', 'negative'], ['drink', 'negative'], ['main dish', 'negative'], ['check', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Succulent, buxom mussels can be had four ways: with classical white wine, tomatoes, luxurious Pernod and cream, or chorizo and white beans."], "output": "[['mussels', 'positive'], ['white wine', 'neutral'], ['tomatoes', 'neutral'], ['Pernod', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The meal arrived just as we were finishing the appetizers, each good portions."], "output": "[['appetizers', 'neutral'], ['portions', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Owner Mary Redding keeps things fish camp-y with rod-and-reel rental prices and a list of rules on the backs of the menus."], "output": "[['Owner', 'neutral'], ['fish', 'neutral'], ['prices', 'positive'], ['menus', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It looks like a small pizza joint, and it is, but the food and service are out of this world."], "output": "[['pizza', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I sometimes long for their chicken fried steak and a beer, this place does the trick every time."], "output": "[['chicken fried steak', 'positive'], ['beer', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We went on a Monday night around 6:30pm and were seated right away in the backroom, which is dimly-lit, casual, cozy--kind of felt like you were sitting in a spacious dining galley of a ship or a cabin."], "output": "[['seated', 'neutral'], ['dining', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Now residing in Chicago, the only quality pies are the deep dishes, which I do like."], "output": "[['quality pies', 'neutral'], ['deep dishes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Their menu is limited, they serve miniscule omelettes that may be suitable for a child (with what seems like a teaspoon of stuffing) with a salad (have to pay even more for fries) for $10- which was poorly washed and there were bits of soil all over it!!"], "output": "[['menu', 'negative'], ['fries', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service is pleasent, but they did forget to bring my mother in law's appetizer."], "output": "[['service', 'positive'], ['appetizer', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The wait staff pushed us to get desserts immediately after we finished our main course and we had to continuously tell them we are not ready yet."], "output": "[['wait staff', 'negative'], ['desserts', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["HIGHLY RECOMMENDED, MAKE RESERVATIONS FAR IN ADVANCE TO AVOID LONG WAIT TIMES."], "output": "[['RESERVATIONS', 'neutral'], ['WAIT TIMES', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food choices were a bit unique so if you are a steak and potatos person then this may not be the place for you."], "output": "[['food choices', 'positive'], ['steak', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They gave us desert menus but never came back for a desert order, instead we had to ask for the check and a bus boy retreived it for us."], "output": "[['desert menus', 'neutral'], ['desert order', 'negative'], ['check', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Days later, you'll dream about luscious polenta beneath braised rabbit with thyme and olive gravy, tender calves' liver slivered over sweet and sour onions, meaty monkfish with lemon-rosemary escarole and sublime chocolate pear tart."], "output": "[['braised rabbit', 'neutral'], ['thyme', 'neutral'], ['olive gravy', 'neutral'], ['calves', 'positive'], ['sour onions', 'neutral'], ['chocolate pear tart', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Their olive oil (for dipping purposes) has at the bottom a great mix of italian basil etc, try to get it on your bread without getting a clogged artery!!!"], "output": "[['olive oil', 'neutral'], ['mix of italian basil', 'positive'], ['bread', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["But once we spoke up (and they figured out what happened with the menus) they re-did the dish in a butter sage sauce, which was awesome."], "output": "[['menus', 'neutral'], ['a butter sage sauce', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A dish of chewy smoked seitan evokes Peking duck, while an entree of wide green-tea noodles is served in a tasty faux Bolognese sauce."], "output": "[['dish', 'neutral'], ['smoked seitan evokes Peking duck', 'positive'], ['entree', 'neutral'], ['wide green-tea noodles', 'neutral'], ['served', 'neutral'], ['Bolognese sauce', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["However service was quite slow for a lunch hour."], "output": "[['service', 'negative'], ['lunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter, Momir, was on top of everything the whole time-not to mention entertaining us by constantly hitting on the two blond souther girl sitting at the table next to us-- and the free wine and after dinner espressos were much appreciated."], "output": "[['waiter', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["after the main course the waitress brought desert menus and never came back."], "output": "[['waitress', 'negative'], ['desert menus', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If I went back, I'd have dinner in the bar--better service and even better atmosphere."], "output": "[['dinner', 'neutral'], ['bar', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Though weekend nights and Sunday brunch draw the largest crowds, neighborhood residents master this vegan menu of quinoa-lentil cakes, seitan piccata, and sweet-potato pumpkin pie by popping in daily."], "output": "[['brunch', 'neutral'], ['menu', 'neutral'], ['quinoa-lentil cakes', 'neutral'], ['pumpkin', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This is also when the waiter told us that half the menu was sold out."], "output": "[['waiter', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I like the smaller portion size for dinner."], "output": "[['portion', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our server never bothered to inquire as to whether or not we wanted coffee."], "output": "[['server', 'negative'], ['coffee', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["considering the prices on the menu, i'd rather go somewhere else where they know how to refill water and real chairs for everyone, something you can even get at mcdonald's."], "output": "[['prices', 'neutral'], ['menu', 'neutral'], ['water', 'neutral'], ['chairs', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The centerpiece of the menu is a range of sushi and sashimi sets: standard pieces and rolls that are adequately fresh and reliable."], "output": "[['menu', 'neutral'], ['sushi', 'positive'], ['sashimi', 'positive'], ['rolls', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It may not be cuisine at it's hautest, but Grand Canyon does a mean burger and great big fluffy fries."], "output": "[['cuisine', 'negative'], ['burger', 'positive'], ['fluffy fries', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our server paid little attention to refilling our drinks, the runners brought the entrees out less than 1 minute after the appetizer, the server delivered another table's bill to us before we had even had entrees, and my partner's entree has a very noticable hair on his plate."], "output": "[['drinks', 'neutral'], ['runners', 'positive'], ['appetizer', 'neutral'], ['table', 'neutral'], ['bill', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is really great but the service is absolutely horrible!"], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My complaint was the service was not that good but the food made up for it."], "output": "[['service', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The restaurant has a Family feel, not least with regard to the portions which are enormous; the veal alone could have single-handedly solved third world famine."], "output": "[['portions', 'positive'], ['veal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The line moves quickly, perhaps because there are no alcoholic drinks, which cuts lingering at the tables to a minimum."], "output": "[['line', 'positive'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["00 bottle of wine, we had to endure the waiter's attitude, like he was doing us a solid, if you're into huge Euro crowds and don't care about what you eat and how it is served to you, Baraonda is your kind of place."], "output": "[['attitude', 'neutral'], ['crowds', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Waiters then recite an impossibly long list of specials; pay attention or you'll miss out on voluptuous porcini mushroom ravioli or hefty lamb chops with rosemary crust."], "output": "[['Waiters', 'positive'], ['specials', 'positive'], ['voluptuous porcini mushroom ravioli', 'neutral'], ['hefty lamb chops', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I was not allowed to transfer my credit card to the table, and was treated disgracefully while the hostess waited for the bar to sign off my card."], "output": "[['hostess', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitress didn't seem to know anything about the menu, she forgot our drinks, took away our wine list after I asked to keep it, and then said, I'm sorry, I only slept 3 hours last night."], "output": "[['waitress', 'negative'], ['menu', 'neutral'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["pineapple, kiwi, guava, and raspberry sorbet."], "output": "[['pineapple', 'neutral'], ['sorbet', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food It's billed as Asian street food, but since the menu is a creative collaboration between expert chefs Vongerichten and Gray Kunz, dishes show unmistakable finesse."], "output": "[['Asian street food', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Service was good except the waitress brought over the check before I asked her."], "output": "[['Service', 'positive'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waitress was so fun- I wanted her to join us for dinner."], "output": "[['waitress', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Careful when ordering soup, the portion is huge, you need to share, but its worth spending the extra couple bucks on just to taste it -- its all home-made food."], "output": "[['soup', 'neutral'], ['portion', 'positive'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We ate brunch here with my parents on a Sunday afternoon -- delicious food, lovely service, great value."], "output": "[['brunch', 'neutral'], ['food', 'positive'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Waiter was very arrogant, though tha staff was attentive and when a waiter pilled a glass of water on one of our guests, the hostess ran with a dry cleaning voucher even though we did not make a big deak of it - just an accident and only water."], "output": "[['staff', 'positive'], ['glass of water', 'neutral'], ['hostess', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Upon calling to reserve a table outside for Brunch, the manager requested a cc nbr to secure the table for 6 (I was 8 months pregnant and there was a little baby)."], "output": "[['Brunch', 'neutral'], ['manager', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Chinese menu is gone, along with most of the good dishes."], "output": "[['Chinese menu', 'neutral'], ['dishes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["However, the restaurant is nothing special and and the food is hit or miss - perhaps the chef should tend more to his main dishes rather than mingling with the customers."], "output": "[['food', 'negative'], ['chef', 'negative'], ['main dishes', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The ribs superb, the steak, the chicken wings, the french fries, the hamburger."], "output": "[['ribs', 'positive'], ['steak', 'neutral'], ['chicken wings', 'neutral'], ['french fries', 'neutral'], ['hamburger', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We started ordering wine and, since we don't know much about it, we decided to let the waiter choose for us; we were pleased with his recommendation."], "output": "[['wine', 'neutral'], ['waiter', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Don't ever bother - the drinks were awful, but it was the people who work there that really made this the worst experience at dining."], "output": "[['drinks', 'negative'], ['people', 'neutral'], ['dining', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is first-rate awful - they managed to offend two countries in one meal - my husband's middle eastern platter (hummous, falafel, stale chips) was lo ta'im (not tasty) - and my mexican salad (bean, avocado, lettuce, stale chips) was muy repugnato."], "output": "[['hummous', 'negative'], ['falafel', 'negative'], ['lettuce', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Generous portions on the entrees."], "output": "[['portions', 'positive'], ['entrees', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Oh, and kudos to the hostess who appeared out of thin air with extra napkins just moments after a glass of water was knocked over - she's upping the bar on service here."], "output": "[['hostess', 'negative'], ['air', 'negative'], ['glass of water', 'neutral'], ['bar', 'neutral'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Pork chops is probably the best choice on the menu."], "output": "[['Pork chops', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Binegar, soy sauce, pish sauce, garLIC, ginger, chicken, lechon, oh man, it was sooooooooooooooooooooooooooooooo good."], "output": "[['soy sauce', 'neutral'], ['pish sauce', 'positive'], ['garLIC, ginger, chicken', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["However, it was a very long wait (over 45 min) and I confronted the hostess who stated that she could not find me at the bar and she had seated 6 other parties before me."], "output": "[['wait', 'negative'], ['hostess', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the dishes are a little too recherche and too trendy for their own good and there is not enough on the menu for vegetarians."], "output": "[['dishes', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is spectacular, from the appitizers to the main course, and then of course the desserts, (WOW) you'll need no more."], "output": "[['food', 'positive'], ['appitizers', 'positive'], ['main course', 'positive'], ['desserts', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter had started to circle around our table like a shark after our 2nd dish, taking out plates when we were not even done."], "output": "[['waiter', 'negative'], ['table', 'neutral'], ['plates', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["From a solid homey, affordable Italian menu in a warm, exhileratingly crowded location they've gone to a 30$ minimum per person on opera nights with a quality of food and drink that just does not warrant the prices."], "output": "[['menu', 'positive'], ['quality of food', 'neutral'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Even without this hiccup, the service seemed very amateur--not snooty, as I've read in other reviews--just nowhere near as good as it should be given the price of the meal."], "output": "[['service', 'negative'], ['price', 'neutral'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Upon arrival I attempted to give a waiter my name (there doesn't seem to be a hostess) and tell him I had a 9pm reservation, but was told to just go get in line and wait for a table."], "output": "[['waiter', 'negative'], ['hostess', 'negative'], ['reservation', 'neutral'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Main courses include char-grilled whole brook trout, baby lamb sotee, and (of course) kebabs of lamb and chicken; Try the thick Turkish coffee with a dessert of Kunefe with cheese !"], "output": "[['baby lamb sotee', 'neutral'], ['kebabs of lamb', 'neutral'], ['chicken', 'neutral'], ['Turkish coffee', 'positive'], ['Kunefe', 'neutral'], ['cheese', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["food is heaven  we were greeted by the hostess and sat down immediatly the space was very crowded and and we decided to order drinks promptly food can wait."], "output": "[['hostess', 'positive'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter, and someone at the next table, were both correct when they said that the lobster was delicious, but I though the price was a little steep."], "output": "[['waiter', 'positive'], ['lobster', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Tony's gone, sadly Ernie's passed on and now the waiters have corn rows and less finish to their chosen profession but it still maintains it's class and place as a brooklyn landmark."], "output": "[['waiters', 'negative'], ['corn rows', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The line gets a bit claustrophobic, since you're jammed against the counter, but the enormous Greek salad (replete with herbed feta, slightly sweet dolmades and a plethora of olives), the baba ghanouj and the eponymous falafel are great, as are the spanokopita and other spur-of-the-moment pastries they always seem to be featuring."], "output": "[['Greek salad', 'positive'], ['plethora of olives', 'neutral'], ['eponymous falafel', 'positive'], ['pastries', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The wait can be long especially during brunch time but worth it."], "output": "[['wait', 'negative'], ['brunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The wait staff had good recommendations and when i broke a wine glass, they reacted in a way to put me out of my embarrassment quickly and even filled me a new glass of wine."], "output": "[['wait staff', 'positive'], ['glass of wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When you're sitting in their main dining room (which has a spectacular, hand-painted high ceiling) you'd never know there was a world outside."], "output": "[['main dining room', 'neutral'], ['ceiling', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went for dinner at Lucy the other night with five friends and it was the best experience I've had in a long time."], "output": "[['dinner', 'neutral'], ['time', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter snubbed us when we asked if there was dessert (there wasn't), and my meal would have been the same price had it not been restaurant week."], "output": "[['waiter', 'negative'], ['dessert', 'neutral'], ['meal', 'neutral'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The first time my husband and I went there, both the appetizer and entreee I ordered were not available, but we had a waitress who was really on top of things."], "output": "[['appetizer', 'neutral'], ['waitress', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Half an hour after our appetizer was cleared, the waiter told us it would take more time to get our main courses."], "output": "[['appetizer', 'neutral'], ['waiter', 'negative'], ['courses', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Plenty of tables to allow for some alone time with a friend in an otherwise sometimes crowded bar area."], "output": "[['tables', 'positive'], ['bar area', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service is friendly, if not the most prompt in the world, the food is great, and the prices, while not cheap, won't put your wallet out of commission."], "output": "[['service', 'positive'], ['food', 'positive'], ['prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The wait staff is very attentive; though if the place is really packed, then you may have to flag someone."], "output": "[['wait staff', 'positive'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitstaff is helpful and they'll get your favorite meats to circle your table more often if you just ask."], "output": "[['waitstaff', 'positive'], ['meats', 'positive'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Part of the charm is in the earnest service; part of it is the colorful clientele; but the real charm comes from what emerges from the kitchen."], "output": "[['service', 'positive'], ['clientele', 'positive'], ['kitchen', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter must have been a 'stand-in' because he did not know the menu, choices or basic service protocol (bread plate on the left)."], "output": "[['waiter', 'negative'], ['menu', 'neutral'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our server seemed out of it, and drinks took 15 minutes to arrive."], "output": "[['server', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["for instance, i sat next to this couple who experienced problems with their food and the asked to speak to a manager."], "output": "[['food', 'negative'], ['manager', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Whatever happen to FAMILY STYLE Thai cooking, the portion are too small and tradtional thai cooking uses MSG which I prefer not to have in my body."], "output": "[['STYLE Thai cooking', 'neutral'], ['portion', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We asked for our check (to pay for our drinks and leave), and received the quickest service all evening."], "output": "[['drinks', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After spending about 2 hours in the restaurant our waiter decided to call it a night without even asking if we wanted dessert."], "output": "[['waiter', 'negative'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was cold and did not match the description on the menu, the waiter could not be bothered with me (and I am nice to deal with since I work in the industry), and it was way over priced."], "output": "[['description', 'negative'], ['menu', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went to the tasting before Nobu opened and the menu and service has greatly improved since then."], "output": "[['menu', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["At almost $70/person with a glass of wine, the food is overrated."], "output": "[['glass of wine', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Nostalgic lodgey bric-a-brac adorns the livelier front dining room and bar, while the dim, non-smoking back room is decorated with stained glass and modern, Mission-style chairs."], "output": "[['livelier front dining room', 'neutral'], ['bar', 'neutral'], ['dim', 'neutral'], ['non-smoking back room', 'neutral'], ['chairs', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Besides the food, the ambience reminds one of being in your grannie's dining room."], "output": "[['food', 'neutral'], ['ambience', 'neutral'], ['dining room', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My dinner at Diner 24 is highlighted by rude waiters, overpriced food and unprepared dishes."], "output": "[['dinner', 'neutral'], ['waiters', 'negative'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We did complain to the manager, but she just said there are problems in the kitchen and took the drinks off bill."], "output": "[['manager', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This closet-sized little eatery has a great collection of wine, by the glass, carafe, and bottle."], "output": "[['collection', 'positive'], ['wine', 'positive'], ['glass', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Their relatively recent introduction of a version of the Sicilian pie is called the Grandma pie featuring a thin crust, much sauce, with less cheese, and chopped Basil."], "output": "[['Sicilian pie', 'neutral'], ['sauce', 'positive'], ['chopped Basil', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The brunch entrees were shockingly overpriced, even for the area, and especially given the food quality."], "output": "[['brunch entrees', 'negative'], ['area', 'neutral'], ['food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After being seated at an outdoor table on a 45 degree tilt, the surly waitress gave us menus."], "output": "[['seated', 'neutral'], ['outdoor table', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["You should not go to a Brazilian BBQ place and have to chase the waiters and go to the hostess ASKING FOR MEAT."], "output": "[['Brazilian BBQ', 'neutral'], ['waiters', 'negative'], ['hostess', 'negative'], ['MEAT', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I looked for months for a reasonably priced place that could accommodate about 40 people for a wedding rehearsal dinner on a Friday night."], "output": "[['priced place', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The place is very loud, good for drinks by the bar not to eat and yell."], "output": "[['place', 'negative'], ['drinks', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitor never gave us the specials menu (which they gave to a another couple who sat next to us 20 minutes later) and the service was very slow even for the basics (bread and water, for which we had to ask a couple of times)."], "output": "[['service', 'negative'], ['water', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When we finally got our waiters attention - and explained to him we were unhappy with our entrees, his demeanor changed completely, he took our dishes and walked away without taking another order for us or asking if he could get us anything else."], "output": "[['waiters', 'neutral'], ['entrees', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After we sat down and started ordering, the waiter informed us that they were really only into serving dinners."], "output": "[['waiter', 'negative'], ['serving dinners', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["First of all we ordered a wine from the menu listed as 2000 but the waiter brought the 2001 vintage and tried to pass it off as the 2000."], "output": "[['wine', 'neutral'], ['menu', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene The space, fit with imported giant urinals, zinc-topped bar, large antique mirrors, mosaic floor tiles and mahogany trim, looks like it's been around forever."], "output": "[['Scene', 'neutral'], ['space', 'neutral'], ['bar', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We arrived about 15 minutes late for a Friday 12:30 reservation, but the staff couldn't have been nicer."], "output": "[['reservation', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I would not return for a $30 entree of inadequate portions."], "output": "[['entree', 'neutral'], ['portions', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The place was empty except for one table, but they were just having drinks (red flag #1)."], "output": "[['place', 'negative'], ['table', 'neutral'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service and atmosphere may not set your mood but when you're done you will realize that it's only the food that counts!"], "output": "[['atmosphere', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene Quartino's airy dining room, wrapped in high windows, hinges around a trendy bar where regulars sip wine out of blunt tumblers while swapping stories--often in Italian."], "output": "[['Scene', 'neutral'], ['airy dining room', 'neutral'], ['bar', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A friend and I had a lovely bottle of wine, two appetizers, two main courses and two coffees and we had change from $40."], "output": "[['bottle of wine', 'positive'], ['appetizers', 'neutral'], ['main courses', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["As we were finishing our dessert, a nearby waitress dropped a tray and HOT CHOCOLATE SAUCE splattered all over my neck, hair and sweater and my boyfriend's clothes."], "output": "[['dessert', 'neutral'], ['waitress', 'negative'], ['HOT CHOCOLATE SAUCE', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We sat, missing a place setting for a while before the waitress came to ask if we wanted water and then ran away."], "output": "[['setting', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Upon entering Alta the bar and restaurant decor ironically misguide the patron."], "output": "[['bar', 'neutral'], ['decor', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Don't bother looking at a menu- Shrimp cocktail, steak for 1,2,3, or more, creamed spinach and hash browns, and save room for the pecan pie and cheese cake, and don't forget the SCHLAG!!!!"], "output": "[['menu- Shrimp cocktail', 'neutral'], ['spinach', 'positive'], ['pecan pie and cheese cake', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We recently visited Madiba for lunch, and our waitress was sweet but ineffective."], "output": "[['lunch', 'neutral'], ['waitress', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The ingredients used are of a good quality and the taste is superb."], "output": "[['ingredients', 'neutral'], ['quality', 'positive'], ['taste', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Space aside, service is ok but the food is really well done."], "output": "[['Space', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After two terrific meals in the dining room, we opted to sit at the bar on our third visit."], "output": "[['meals', 'positive'], ['dining room', 'neutral'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["not to mention that the waiter offered putting a scoop of ice cream on my dessert."], "output": "[['waiter', 'negative'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The place was not crowded for dinner on a Sunday night at 8:30pm."], "output": "[['place', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Waiter suggests a beer, and offers to bring a small glass, to taste it and see if I like it, before I even order the beer!"], "output": "[['Waiter', 'positive'], ['glass', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["And then he'll forget to bring your drink every time you order one, won't pay attention to your table of 8, will give you unwarranted attitude, and never be friendly or smile."], "output": "[['drink', 'neutral'], ['attitude', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is good whether you are going for dinner or just for a couple of drinks and a small appetizer."], "output": "[['food', 'positive'], ['dinner', 'neutral'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I can honestly say that while some of the dishes I have had at other places I might have rated on an individual basis higher I have not enjoyed a total dining experience more."], "output": "[['dishes', 'neutral'], ['dining', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The kitchen staff either cannot or will not accomodate special diets which is surprising given that there are so many fine dining establishments that do have special menus to cater to vegetarians."], "output": "[['kitchen staff', 'negative'], ['menus', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It is nearly impossible to get a table, so if you ever have the chance to go here for dinner, DO NOT pass it up."], "output": "[['table', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our margaritas came after 1/2 an hour - and they didn't ever ask if we wanted more - the server brought all our food to the wrong table - my dinner came after my boyfriend had finished his plate and they ran out of a certain dish at 9PM on a Friday!!"], "output": "[['margaritas', 'neutral'], ['dinner', 'neutral'], ['dish', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was good but not worth the price."], "output": "[['food', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Village salad had a lot more cucumbers than tomatoes most likely because tomatoes are expensive in US and they want to earn more taking advantage of people who don't know about Greek food."], "output": "[['Village salad', 'neutral'], ['Greek food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I can't speak on the food, but I went there for a show the other week and here is my experience: one of the friendliest servers ever (no attitude); the drinks were avg."], "output": "[['food', 'neutral'], ['servers', 'positive'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Wait staff is seemingly non-existant, and food servers are way too agressive - our food was thrown on the table, and even knocked a member of my party in the head with a plate with little acknowledgement."], "output": "[['Wait staff', 'negative'], ['food servers', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Actually she want to eat sushi, but their staff reject to serve it."], "output": "[['sushi', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The irony of it all is that I tried the fish and chips at a sports bar across the street the following week, 1/2 the price (w/ fries included), and the portion was bigger and much tastier."], "output": "[['chips', 'neutral'], ['bar', 'neutral'], ['price', 'neutral'], ['w/ fries', 'neutral'], ['portion', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene This tiny jewel of a spot is simply decorated with white walls and plate glass."], "output": "[['Scene', 'neutral'], ['spot', 'positive'], ['glass', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Amazing views of NYC regaled us at lunch earlier in the week and then at dinner this evening."], "output": "[['views', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Bartender seemed cool, so maybe I'd go back for a drink."], "output": "[['Bartender', 'positive'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Then another pleasant surprise - the menu said we had to share the entree for each couple."], "output": "[['menu', 'neutral'], ['entree', 'neutral'], ['surprise', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the rest of my table disliked their food, and also had to send drinks back because it was not what they ordered."], "output": "[['food', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It took an hour for us to order, another hour and 15 min to get our entree's I had to go to the bar to order my champange, and carry it back myself, the waiter got our entrees mixed up and placed them in the wrong place and sat there and watched me switch them around."], "output": "[['bar', 'neutral'], ['waiter', 'negative'], [\"entree's\", 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have to say that I've been there only during brunch time but the service even though slow, it was good."], "output": "[['brunch', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["throughout the whole meal, all I kept thinking was AVERAGE, AVERAGE, AVERAGE until the bill came, which was a little more than average,to say the least."], "output": "[['meal', 'neutral'], ['bill', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["although the food was well-prepared, it was not worth the price, especially when it does not include dessert!"], "output": "[['food', 'positive'], ['price', 'negative'], ['dessert', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We decided to order soup (over $6 a bowl), thinking that would be quick, however our waitress then said the soup is OUT OF A CAN and still would be a 20 minute wait since the tickets are processed in order."], "output": "[['bowl', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When we first walked in, we saw other diners wiping their plates with bread- so we though that the food was good -but we very soon realized that the portions really were so small that you really have to lick your plate clean - afterall, their dinners costs a fortune."], "output": "[['food', 'positive'], ['portions', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Were told we could not share one menu and called over the horrible manager."], "output": "[['menu', 'neutral'], ['manager', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were even able to call in advance to make sure there was space at the bar because I was on crutches and the owner reserved the seats til we got there."], "output": "[['bar', 'neutral'], ['owner', 'negative'], ['seats', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["From the bottomless cup of coffee to the basket o' scones mini-muffins to the delicious entrees, Dizzy's is the place to be."], "output": "[['cup of coffee', 'positive'], ['basket', 'neutral'], ['entrees', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It's the New York you thought was long gone; orders are spoken, not yelled, and the staff knows the names of patrons' dogs."], "output": "[['staff', 'negative'], ['patrons', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We ordered off the restaurant week menu, which at other establishments means automatic second-rate service, but not here."], "output": "[['menu', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For desert take the tiramisu, it is by far the best there."], "output": "[['desert', 'neutral'], ['tiramisu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After being seated by a very kind, but quite stressed, young lady, we took in the room and menu."], "output": "[['seated', 'neutral'], ['menu', 'neutral'], ['lady', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I don't like places that sacrifice quality for money or play tricks on you by hiding drink prices till check time (everyone at the place was drinking Sangria, so that, it seems, must be the money-maker)."], "output": "[['quality', 'negative'], ['drink prices', 'negative'], ['Sangria', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Somewhat agree with the previous reviews about service and the long wait but once seated, the food is well worth it."], "output": "[['service', 'negative'], ['long wait', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene This cosmopolitan cousin of the legendary Harry's Bar in Venice is frequented by a wealthy and insouciant crowd, the types who don't bother looking at menu prices when they order."], "output": "[['Bar', 'neutral'], ['crowd', 'negative'], ['menu prices', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I also asked for a chef (thought that may be able to talk about the food for the party), but the waitress said that there was no chef at the restaurant."], "output": "[['food', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["MY FATHER ASKED FOR A MARTINI MADE A CERTAIN WAY THE WAITER HAD NO CLUE WHAT HE WAS TALKING ABOUT."], "output": "[['MARTINI', 'neutral'], ['WAITER', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It is never a ridiculous wait no more than 30 minutes, in the meantime you can chat with your friends and start the week-end off right with a signature drink from the bar!"], "output": "[['wait', 'negative'], ['bar', 'neutral'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["As we sat waiting for our menus, we started noticing the frowns on the faces of the people around us, watching as patrons tried to flag down waiters without luck, asking for things like water."], "output": "[['waiting', 'neutral'], ['menus', 'neutral'], ['waiters', 'negative'], ['water', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I was tempted to try the dessert because I've heard rave reviews about it, but we were stuffed, as the portions are fairly large."], "output": "[['dessert', 'neutral'], ['portions', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service is almost stifling polite (they pushed in my chair behind me every time I returned from the bathroom), though the sushi chef preparing my food was casual and chatty."], "output": "[['chair', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The choices on the menu were very limited-discounting raw items, there were practically no appetizers The foie gras de canard was mediocre with a syrupy sauce."], "output": "[['choices', 'negative'], ['menu', 'neutral'], ['appetizers', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["And I agree with a couple of reviews down that the asparagus and egg app is very very good, but not light on calories -- also huge and low-ish on carbs, so you Atkiners could eat that for an entree."], "output": "[['asparagus and egg app', 'positive'], ['entree', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We probably would have stuck out the wait if we could have gotten a drink at the bar but apparently it was closed or only for show."], "output": "[['wait', 'negative'], ['drink', 'neutral'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Not only did they refuse to give me any milk but they charged me full price ($9) for plain udon noodles - no broth, veggies, or meat just wet noodles in a bowl."], "output": "[['price', 'negative'], ['bowl', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Service was good throughout the dinner but when it came time to get the check, we waited over 20 min."], "output": "[['Service', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I haven't tried their brunch, partly because their coffee is a bit weak to me."], "output": "[['brunch', 'neutral'], ['coffee', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter asked us several times after dinner whether we had paid our bill yet, and after we had, he came over to make sure that we hadn't just hidden it from him or something."], "output": "[['waiter', 'negative'], ['dinner', 'neutral'], ['bill', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Aged beef charred on the outside, red on the inside."], "output": "[['beef', 'negative'], ['outside', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Great from appetizer to dessert including a wonderfully created vegetarian plate that is not on the menu."], "output": "[['appetizer', 'positive'], ['dessert', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We took seats at the bar with 2 amazing bottles of wine (one for the appetizers and one to match the entrees) Monsieur Zucco was very accomodating and kept a sharp eye at filling our glasses at the right time at the right level."], "output": "[['bar', 'neutral'], ['bottles of wine', 'positive'], ['appetizers', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A big pile of seasonal fruit and strawberry butter on french toast, good coffee, a hopping crowd, friendly service."], "output": "[['seasonal fruit and strawberry butter on french toast', 'neutral'], ['coffee', 'positive'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["we saw another waitress spill hot coffee on another diner's foot."], "output": "[['waitress', 'negative'], ['hot coffee', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The steak and sides at Luger's are definitely tasty, but the legendary status it seems to hold lead me to be disappointed after the actual meal."], "output": "[['steak', 'positive'], ['sides', 'positive'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The spring rolls are great, tastes like any other rolls with meat filling and I had the soy protein ham dish (bad idea)."], "output": "[['spring rolls', 'positive'], ['meat', 'neutral'], ['soy protein ham dish', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My girlfriend had a margarita she said was ok, and I had a soda that somehow tasted terrible, like the line was dirty."], "output": "[['margarita', 'positive'], ['soda', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Only quibbles are so-so wine service, and while Prix-fixe is reasonable at $68, extra charges for additional dishes/tastings can be high."], "output": "[['wine service', 'neutral'], ['Prix-fixe', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["1) they gave us the wrong table had to wait 10 minutes until they gave us the one we wanted 2) had to wait 15 minutes for a waiter 3) ordered chicken and brocolli."], "output": "[['table', 'negative'], ['waiter', 'neutral'], ['chicken', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitress, host, and bus staff were sitting around at the bar while the patrons were all complaining about the service."], "output": "[['waitress', 'negative'], ['host', 'negative'], ['staff', 'negative'], ['bar', 'neutral'], ['patrons', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The place was empty with three waiters working and it still took 15 minutes to bring us menus."], "output": "[['place', 'negative'], ['waiters', 'negative'], ['menus', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It took us about 30 minutes to get seated, the burgers came without lettuce, they brougt us the wrong drinks, and the flavor of the burgers were below average."], "output": "[['seated', 'neutral'], ['drinks', 'negative'], ['flavor', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu was in Italian- might as well have been in Esperanto;that put us at the mercy of the waiter for recommendations."], "output": "[['menu', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We too had reservations but the gentleman never checked a book to see our names or check us off."], "output": "[['reservations', 'neutral'], ['gentleman', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Dessert was speedily served as I still had a beer to drink and this is after I requested a few extra moments until it arrives."], "output": "[['Dessert', 'positive'], ['served', 'positive'], ['beer', 'neutral'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The prices are reasonable but they don't have a sushi lunch."], "output": "[['prices', 'positive'], ['sushi lunch', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our server (after 4 reminders) finally got around to getting our cocktail orders during the meal (at a time when the establishment was not full)."], "output": "[['server', 'negative'], ['cocktail', 'neutral'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Myself along with every other patron were forced to wait in an overcrowded bar while employees carry chairs and such over our heads to prepare for dinner in the next room, shoulder to shoulder we stood there like cattle waiting to be fed."], "output": "[['bar', 'negative'], ['employees', 'neutral'], ['chairs', 'neutral'], ['dinner', 'neutral'], ['cattle waiting', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The appetizer, conch fritas was yummy; entree, spicy shrimp with coconut rice (just a hint of coconut - not overwhelming); and the dessert tres leches de mango with calle ocho cafe was unbelievable!"], "output": "[['appetizer', 'positive'], ['fritas', 'positive'], ['spicy shrimp with coconut rice', 'neutral'], ['coconut', 'neutral'], ['dessert tres leches de mango with calle', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Generally, the food was fine, but the table is too small to eat comfortably."], "output": "[['food', 'positive'], ['table', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The tables are close so you can hear every conversation going on around you, but if you're here with someone who enthralls you, you will notice no one else but your dinner date."], "output": "[['tables', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The dinner menu promises creative-yet-comforting fare, such as beef brisket in a red wine and fig sauce, panko-crusted tofu over hijiki salad, and a six-spice beef burger."], "output": "[['fare', 'positive'], ['beef brisket in a red wine', 'neutral'], ['panko-crusted tofu over hijiki salad', 'neutral'], ['six-spice beef burger', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We weren't sure we'd even get a table,surprisingly the lovely hostess assured us she'd get us in if we gave her 15 minutes in the bar."], "output": "[['table', 'neutral'], ['hostess', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["even though he wasn't our waiter that evening, chris had 2 glasses of champaigne sent over to our table and later on the manager sent over a desert with a candle in it and congratulated us."], "output": "[['waiter', 'neutral'], ['manager', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Since it changed owners/chefs, the portions are smaller (I always used to ask for a doggie bag for my chic-parm), now I can finish and still be hungry even after appetizers (which aren't as good anymore)."], "output": "[['portions', 'negative'], ['appetizers', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When I go out for dinner which is quite often, I have never encountered such rudeness from a waiter or owner as I did at this smoke filled, tight spaced, cash only restaurant."], "output": "[['dinner', 'neutral'], ['waiter', 'negative'], ['owner', 'negative'], ['smoke', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu reads well, and it sounds like the chef knows whats up."], "output": "[['menu', 'neutral'], ['chef', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My favorite is a dish I've treasured since childhood, linguine with white clam sauce, cooked with pepperoncino."], "output": "[['dish', 'positive'], ['white clam sauce', 'neutral'], ['pepperoncino', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The decor was mediocre and honestly, I can get a better brunch at a Cracker Barrel restaurant."], "output": "[['decor', 'negative'], ['brunch', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We ended up hanging out for a few hours at their bar with a staff that we felt like we've known for years."], "output": "[['bar', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The wait staff rushed us through our meal, took away our food before we were finished (even though we told them we were still eating) and then, as we were lingering over the bill, asked us to leave."], "output": "[['wait staff', 'negative'], ['meal', 'neutral'], ['bill', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The kitchen finds success with classics like a homemade, cognac-rich duck terrine and well-seasoned steak frites (although the fries tend to be heavily salted)."], "output": "[['kitchen', 'positive'], ['cognac-rich duck terrine', 'neutral'], ['well-seasoned steak frites', 'neutral'], ['fries', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We went ot Al di La a bit earlier than we usually go to dinner, mainly due to the fact that reservations are not accepted."], "output": "[['dinner', 'neutral'], ['reservations', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu offers all the usuals: inexpensive spring rolls, vegetable sweet-sours, pad thai."], "output": "[['menu', 'positive'], ['spring rolls', 'positive'], ['vegetable', 'neutral'], ['thai', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I KEPT WAITING FOR THE FLAVORS IN THIS RICH LOOKING SAUCE TO TAKE OVER, BUT THEY DID NOT, THE SCALLOP WAS A LITTLE RUBBERY."], "output": "[['FLAVORS', 'neutral'], ['SAUCE', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["its a cool place to come with a bunch of people or with a date for maybe a mild dinner or some drinks."], "output": "[['place', 'positive'], ['dinner', 'neutral'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food Outstanding soup choices include the chicken curry, which mixes egg noodles with eggplant, potatoes, and fresh lemon, all in a spicy coconut curry broth."], "output": "[['Food', 'positive'], ['soup choices', 'positive'], ['chicken curry', 'positive'], ['mixes egg noodles with eggplant, potatoes', 'neutral'], ['lemon', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Diners sit around large tables where chefs ostentatiously chop, slice, stir-fry and grill."], "output": "[['chefs', 'negative'], ['Diners', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When there is so much GREAT food in New York, why go for the high-priced mediocre meal?"], "output": "[['food', 'positive'], ['meal', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["get the mussels as an appetizer and try to save room for dessert."], "output": "[['mussels', 'neutral'], ['appetizer', 'neutral'], ['dessert', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In the dim lighting, I thought the portions were impressive and dug in."], "output": "[['dim lighting', 'neutral'], ['portions', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I guess Mars 2112 keeps the food bland for the family fare, but it only serves to detract from its overall experience."], "output": "[['food', 'negative'], ['family fare', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Pecorina brusselsprouts tasted only from the cheese, baccala appetizer was like something from out of a can, beet with pistacchio was ok but could have used someth extra likelemon juice, Saltimbocca was dry and uninspired and the pasta not any better than all the million Italian restos around Bleecker."], "output": "[['baccala appetizer', 'negative'], ['pistacchio', 'positive'], ['Saltimbocca', 'negative'], ['pasta', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene An outing to this ski lodge-sized hot spot, with one of the city's most expansive and popular outdoor patios, feels more like a night spent at a fashion show than dinner at a restaurant--and not just because of the celebrity sightings."], "output": "[['outdoor', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Knew we were in trouble when the waiter spilled our cocktails on the table and couldn't be bothered to bring new silverware."], "output": "[['waiter', 'negative'], ['cocktails', 'neutral'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food Chef-owner Tom Valenti's food makes just as much noise; he cooks in a masculine, big-flavored, meat-and-potatoes style, rich with terrines, mustards, eggs and bitter greens."], "output": "[['noise', 'negative'], ['eggs', 'neutral'], ['greens', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The owner asked the waitress what I said and then proceeded to shout profanity at me from the entrance of the caf."], "output": "[['owner', 'negative'], ['waitress', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Horrible experience, from bartenders trying to pocket the $6 change for a $14 glass of wine, to inattentive and smug service, for sub-par food."], "output": "[['glass of wine', 'neutral'], ['service', 'negative'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["One of the best things about this place are the appetizers, since they have so many unique things to choose from (I always get the clams and the zucchini!)"], "output": "[['appetizers', 'positive'], ['clams', 'neutral'], ['zucchini', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food presented well and the service once we were seated was great but we had a long wait for our table (about half an hour) even though I had pre-booked."], "output": "[['Food', 'positive'], ['seated', 'positive'], ['wait', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["From the outside this place looks cute, however, once inside loud as a disco!"], "output": "[['place', 'positive'], ['disco', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["And while a narrow wood counter and three stools provide desperation seating, most folks choose to take lunch and dinner to go."], "output": "[['wood counter', 'negative'], ['seating', 'negative'], ['lunch', 'neutral'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter was pretty anxious to get us in-and-out, although there were ample tables and my friend and I opted to sit at the bar."], "output": "[['waiter', 'negative'], ['tables', 'neutral'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This is the perfect spot to meet up with friends and have a drink at the bar or stay a while and enjoy the scene and savor the food."], "output": "[['spot', 'positive'], ['drink', 'neutral'], ['bar', 'neutral'], ['scene', 'positive'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although the portions seemed a little diminutive at first, they turned out to be the perfect size once the dinner was over."], "output": "[['portions', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Once we were seated our water order was taken promptly but they never came back with a menu."], "output": "[['water order', 'positive'], ['menu', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["You must eat the cheese fondue (I usually have a special one - my favorite was made with carmelized onions) with medium rare beef tips!!"], "output": "[['cheese fondue', 'neutral'], ['onions', 'positive'], ['beef tips', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We went at 1 am, we got food, fast service and Excellent drinks."], "output": "[['food', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I've since been back for a regular dining night out, it was packed and I should have made a reservation (the wait was a little long)."], "output": "[['dining', 'neutral'], ['reservation', 'neutral'], ['wait', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["they made a good mojito, but the first bite of food, our appetizer, black pepper crab dumplings were so bad that they rendered my palate useless, seriously, and we had to cut our dinner short and wash our mouths out with soap."], "output": "[['appetizer', 'negative'], ['black pepper crab dumplings', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When we sat, our dinner was delivered promplty (Like FAST) and we had plenty of time to make The Goat, which by the way I also recommend highly (Great Show!"], "output": "[['dinner', 'positive'], ['Goat', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["So, if you don't care about speedy service, go; but if you aren't in the habit of lighting your cigarette with twenties, avoid the tapas."], "output": "[['service', 'positive'], ['tapas', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Service is not particularly warm, but I've gone back again and again (for dinner) over the years on an almost monthly basis."], "output": "[['Service', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is not large and I could have had a few slices of pizza after I left."], "output": "[['food', 'negative'], ['slices', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["As for the food, apart from the Chef's Omakase, the appetizers and rolls are just below mediocre for the price they charged."], "output": "[['food', 'neutral'], ['Chef', 'neutral'], ['appetizers', 'negative'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["He was not accommodating at all and the handful of dishes I sampled that night failed to compare to anything you would find elsewhere in the city for less than half the price."], "output": "[['dishes', 'neutral'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["sort of crouched in a chair, leaning over a table, while someone did that obnoxious karate chop sort of thing on her back for way too long."], "output": "[['chair', 'neutral'], ['table', 'neutral'], ['chop', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I called ahead and was told that there would be no problem seating a party of two at 5:30, arrived at 5:30, was told there would be a 5 to 10 minute wait."], "output": "[['seating', 'neutral'], ['wait', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you consider throwing food at your when they remember good service, then go for it."], "output": "[['food', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There was no price on the menu and the waitress recommended it."], "output": "[['price', 'neutral'], ['menu', 'neutral'], ['waitress', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Appetizers were by far the best, entrees were subpar but desserts were sublime."], "output": "[['Appetizers', 'positive'], ['entrees', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went into the buffet style ordering counter, got my plate and was surprised when I bit into a cold plate of chicken and sweet potato."], "output": "[['plate of chicken', 'negative'], ['potato', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I usually order the specials but if not there are at least 5 great dishes that I would choose from any given night."], "output": "[['specials', 'neutral'], ['dishes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My friend and I did have to wait a few minutes for a table, but only because Amanda Hesser (the new NY Times food critic) showed up and, obviously, needed a copious level of attention from the greetings staff."], "output": "[['table', 'neutral'], ['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["PLUS the best wine can be found in the bar but they refused to sell us a bottle!!"], "output": "[['wine', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter came back after I had finished my appetizer to correct himself and let me know that it wasn't vegetarian (chicken stock) after all."], "output": "[['waiter', 'negative'], ['appetizer', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was great but the music was loud and hip-hop and the wait was ridiculous and the prices were out of this world."], "output": "[['food', 'positive'], ['wait', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For appetizers, I'd recommend the crab napolean or the monkfish mousse."], "output": "[['appetizers', 'neutral'], ['monkfish mousse', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Anyway the food was really good, the portions are not big however very filling and exceptionally good."], "output": "[['food', 'positive'], ['portions', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were planning to get dessert but the waitress basically through the bill at us before we had a chance to order."], "output": "[['dessert', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["from drinks at the bar, to our perfect round table!"], "output": "[['bar', 'neutral'], ['round table', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Do not go to this restaurant unless you like paying high prices for small protions, ordering a drink that arrives 20 minutes later, or ordering a meal only to get the side dish 5 minutes after you're done."], "output": "[['prices', 'negative'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitstaff told us that they had already run out of one of the entrees (before 8 p."], "output": "[['waitstaff', 'negative'], ['entrees', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We waited for 1 hour each time the waitress came over to our table."], "output": "[['waitress', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["You can't go wrong with any of the mojitos and the food is very tasty and presented beautifully."], "output": "[['mojitos', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our booth style seats would've been more romantic if our waitress, though nice, was less intrusive, and the loud music from its bar didn't filter thru so much."], "output": "[['booth style seats', 'positive'], ['waitress', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was then rushed unappealing never once were we asked if we'd like a a second bottle of water let alone a second drink."], "output": "[['food', 'negative'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They pray to their Food Gods to make them into a good pizza like VT's."], "output": "[['Food', 'neutral'], ['pizza', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Heck even if they had awful service and atmosphere I would still come to this place for their dumplings, luckly that is not the case."], "output": "[['service', 'negative'], ['atmosphere', 'negative'], ['dumplings', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The chef will not alter any of the three tasting menus."], "output": "[['chef', 'negative'], ['menus', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went with two friends and had the smores bar - two yummy chocolate chip cookies with marshmallows and chocolate melted between, and they serve it piping hot!"], "output": "[['bar', 'neutral'], ['chocolate chip cookies', 'positive'], ['marshmallows', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The crowd was non-existent on the Wednesday we went, which had the advantage of no wait for our table (even though we called an hour early and they said they only have a reservation for 9:00 pm)."], "output": "[['crowd', 'positive'], ['wait', 'positive'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the trendy atmosphere and high price fooled me into thinking that somehow the food would be innovative."], "output": "[['atmosphere', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Maybe go there for the view, but don't bother eating there, go to the bar."], "output": "[['view', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Every time I eat there I feel as if the chef and waitstaff have cooked, prepared and served a meal as if I am the only customer/guest."], "output": "[['waitstaff', 'positive'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["staff is still working out their kinks and learning about the menu but no real complaints."], "output": "[['staff', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Excellent Steaks, the attitude of the Servers could be a little better but the food makes up for everything."], "output": "[['Steaks', 'positive'], ['attitude', 'negative'], ['Servers', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service is sweet and attentive, the wine is delicious and the new wine bar around the corner has the most amazing selection, as well as cheeses and tapas."], "output": "[['service', 'positive'], ['new wine bar', 'neutral'], ['selection', 'positive'], ['cheeses', 'positive'], ['tapas', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Apparently the same hostess was also trying to kick out a group of women having drinks at a table and giving them a hard time for holding up a table."], "output": "[['hostess', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["As appetizers we enjoyed the Drunken Goat Cheese Salad and Lobster Empanadas."], "output": "[['appetizers', 'neutral'], ['Drunken Goat Cheese Salad', 'positive'], ['Lobster Empanadas', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I ordered pasta in a pomodoro sauce and it tasted like it came out of a can."], "output": "[['pasta', 'negative'], ['a pomodoro sauce', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We placed a delivery order - 2 pastas and a caprese and they took and 1 1/2 to get here and the food was inedible when we received it."], "output": "[['delivery', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiters were getting a wine class from a very loud manager and ignoring all the patrons - someone should have been giving them a class on serving instead."], "output": "[['waiters', 'neutral'], ['wine', 'neutral'], ['manager', 'negative'], ['patrons', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My dining partner ordered the turkey burger and declared this also to be the best one ever."], "output": "[['dining', 'neutral'], ['turkey burger', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There were 6 servers standing around watching me eat but they never asked if I needed anything or even offered me water."], "output": "[['servers', 'negative'], ['water', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu was nicely sized with five small plates, eight appetizers and seven entrees."], "output": "[['menu', 'positive'], ['plates', 'neutral'], ['appetizers', 'neutral'], ['entrees', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["But the appetizer is a litlle pricey, especialy $6 for 3 pieces sushi, but iutside that it was a great experience, food was great, and not too costly over all."], "output": "[['sushi', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I don't mind paying a high price for a really good meal, but this was really average food."], "output": "[['price', 'negative'], ['meal', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["As the afternoon progresses, you'll see as many waitstaff as customers scurrying after food carts with bill cards in hand, clutching stacks of steamers back to their tables."], "output": "[['waitstaff', 'negative'], ['food carts with bill', 'neutral'], ['tables', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food and beer make up for it, but it would be nice if the staff weren't such buzz kills!"], "output": "[['beer', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Didn't have room for dessert, but will definitely be back to try the coconut mousse."], "output": "[['dessert', 'neutral'], ['coconut mousse', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food did not come out on time or together and the waiter never came to explain why."], "output": "[['food', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Midway through the meal the waiter came over and said we were being charged $40 a head since there were 7 of us, and they never said that when i made the reservation."], "output": "[['meal', 'neutral'], ['waiter', 'negative'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Silky black bass with porcini mushrooms carries smoky, earthy and buttery overtones that somehow never overpower the fish, and whole-roasted baby pig includes belly meat, braised for 24 hours in five spice-ginger glaze, and yet the pork flavor is still fully present."], "output": "[['fish', 'neutral'], ['braised', 'neutral'], ['pork flavor', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had their eggs benedict for brunch, which were the worst in my entire life, I tried removing the hollondaise sauce completely that was how failed it was."], "output": "[['eggs benedict', 'negative'], ['brunch', 'neutral'], ['hollondaise sauce', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["However, the cheese fondue had too much wine and not enough cheese, the escargot was too stewy and the salmon was very average."], "output": "[['wine', 'positive'], ['escargot', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waitress bought us a round of after drinks too."], "output": "[['waitress', 'positive'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter told us he knew all the wines on it quite well, and he did!"], "output": "[['waiter', 'positive'], ['wines', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Seating is limited, so you will probably want to order take-out, but a better take-out pizza you will not find!"], "output": "[['Seating', 'negative'], ['take-out pizza', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This place is so unexpected, just a tiny little bar, but it serves dinner and even a really good weekend brunch."], "output": "[['place', 'positive'], ['bar', 'negative'], ['brunch', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For the money, it's a dependable and fun place to get sushi - bring friends and share the 2 for 1 rolls (they have to be 2 of the same."], "output": "[['money', 'positive'], ['place', 'positive'], ['sushi', 'neutral'], ['rolls', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the filet came out and was absolutely delicious, on a bed of julienned vegetables in a balsamic vinagarette sauce."], "output": "[['filet', 'positive'], ['julienned vegetables', 'neutral'], ['balsamic vinagarette sauce', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went to Ciao on a Saturday evening and the food was not up to the price asked for."], "output": "[['food', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["As for the menu, I've never been disappointed, but the Margarita chicken salad is my favorite."], "output": "[['menu', 'neutral'], ['Margarita chicken salad', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Then the staff behind the buffett just haven't gotten their groove yet, so you order your food and wait five minutes while it sits behind the glass on a plate, getting cold."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['glass', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Basically traditional menu could have been boring and old-fashioned, but is instead updated enough to please modern palate: steaks, seafood, fish, poultry - ample portions (we took half home), seasoned with care and imagination."], "output": "[['menu', 'neutral'], ['portions', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Disappointed in the selection on the restaurant week menu (which did not include any steak entrees) but impressed with the actual food- everything was very good- fresh and innovative- saffron risotto was not too powerful and the entrees were all good."], "output": "[['menu', 'neutral'], ['steak entrees', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["You'd expect one to have more dessert options, other than rice pudding."], "output": "[['dessert options', 'positive'], ['rice pudding', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter returned seconds later to complain that dozens of people wanted our table then poured her beer into a paper cup-- presumably to encourage us to leave faster."], "output": "[['waiter', 'negative'], ['table', 'neutral'], ['cup', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The mac and cheese is to die for as are many other main dishes including the pork ribs, roast chicken and traditional spaghetti meatballs."], "output": "[['mac and cheese', 'positive'], ['dishes', 'neutral'], ['pork ribs', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The first course of scallops and caviar coupled with celery seemed very bland and left me totally under whelmed; the immense use of oil, coupled with the over cooked vegetables, left my fish entre inedible."], "output": "[['scallops and caviar coupled with celery', 'neutral'], ['cooked vegetables', 'negative'], ['fish', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is mediocre, burgers are ok, the pizza tastes like the box it's delivered in."], "output": "[['burgers', 'positive'], ['pizza', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["perhaps the place is better after the theatre crowd is gone but we were in the midst of it and it wasn't a very enjoyable experience."], "output": "[['place', 'positive'], ['theatre crowd', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Great place to go for a lunch date or for coffee after a date."], "output": "[['lunch', 'neutral'], ['coffee', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["At lunch, try something with chicken."], "output": "[['lunch', 'neutral'], ['chicken', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Service was a little slow, but going on a Monday night during the Brooklyn Restaurant Week, where 20 bucks each got a friend and I appetizer, entree, and dessert was phenomenal."], "output": "[['Service', 'negative'], ['appetizer', 'neutral'], ['dessert', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The overpriced food that's supposed to come off as homestyle diner just doesn't work when the atmosphere is supposed to be super cool but the food is super bland."], "output": "[['diner', 'neutral'], ['atmosphere', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When the spastic waiter finally stopped by our table, we told him we were going to order everything at once b/c we were getting pretty hungry."], "output": "[['waiter', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["To top it off, when we mentioned it to our lovely waitress, she responded as though it was no big deal along with Well now you know for the next time."], "output": "[['waitress', 'positive'], ['time', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Prime Rib was cold and very fatty--Drinks were good though--Very expensive--I've had much better for less."], "output": "[['Prime Rib', 'negative'], ['Drinks', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our oh-so-chic waitress obstained from half the items on the menu (give me a break) so she couldn't make subjective recommendations."], "output": "[['waitress', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["dips, lamd shops, beans, fresh fish."], "output": "[['beans', 'neutral'], ['fish', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The wait staff was not as attentive as I would have liked, we had to ask several times for water and refills of water, and after the food was served, no one returned to check on us."], "output": "[['wait staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the food was pretty nice, but it's on the expensive side."], "output": "[['food', 'positive'], ['side', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We ended the dinner with a surprisingly light and flaky apple tarte tatin."], "output": "[['dinner', 'neutral'], ['apple tarte tatin', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["at the end of the meal the hostess came to us and rudely ask us to leave the table, we were astonished by her attitude."], "output": "[['hostess', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For the price and quality of the food, the service should have been a lot better than it was."], "output": "[['price', 'neutral'], ['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The only drawback is the need for reservations around the typical pre-theatre times."], "output": "[['reservations', 'neutral'], ['times', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The bigger sin is the service --our waiter was late with our main dishes, late with the bill, which was totaled incorrectly (twice)."], "output": "[['waiter', 'negative'], ['main dishes', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There is no waiting area, so we had a crowd hovering over our table, this is just testament to how many people want to eat there."], "output": "[['waiting area', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter took our drink orders and never came back!"], "output": "[['waiter', 'negative'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food Surprisingly tasty Texas-style barbecue gives this place culinary flexibility beyond that of most wrap-and-burrito shacks."], "output": "[['Food', 'positive'], ['shacks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We went in March'03 on Sunday - the food was just so-so, but we had to beg for a glass of water (and never got it anyway), but the worst part - the forks and knives were totally dirty (you could see someone's scrambled eggs on them)."], "output": "[['glass of water', 'neutral'], ['eggs', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["he politely asked about what happened, we told him about the hostess behaviour, the manager apologized for the her behavior and treated us to a drink at the bar."], "output": "[['manager', 'positive'], ['drink', 'neutral'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The space is tiny and intimate, so if you score a table, or a good seat at the bar, you're set for the night."], "output": "[['space', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Went for dinner around 9pm on a Sunday night and sourdough bread they brought right away was warmed to perfection and delicious."], "output": "[['dinner', 'neutral'], ['bread', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I've sampled several other dim sum places here, and none feature the winning combination that Triple 8 offers: reasonable prices, large range of standard _and_ less common dim sum, little/no wait (not like the Mott St."], "output": "[['dim sum places', 'neutral'], ['prices', 'positive'], ['wait', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter was constantly puching us to have drinks, he told us that we were not ordering properly and insisted on bringing to the table his recommendations."], "output": "[['waiter', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had to wait an hour before our food was served, then another hour inbetween courses, all the while whilst the staff were naughtily hiding in an attempt to avoid our 'where's out food?'"], "output": "[['served', 'neutral'], ['courses', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Captain was showing his impatience for a crowded Monday night and the dinner I was served was not prepared the way he told me it would be."], "output": "[['Captain', 'negative'], ['dinner', 'neutral'], ['served', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["not large portions - my boyfriend's entree looked more like an appetizer, and all we got out of the dinner was a $100 tab and hunger for more food."], "output": "[['portions', 'negative'], ['entree', 'neutral'], ['appetizer', 'neutral'], ['dinner', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The only con is the price ($110 for two people for a full meal)."], "output": "[['price', 'neutral'], ['meal', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Their new style of all you can eat is: They bring barely enough food for the table, mostly just bread ,until you ask a waiter to bring some more."], "output": "[['food', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I work nearby so I've eaten here countless times (breakfast, lunch, dinner, even Sunday brunch), and been to several really cool parties--the food's delicious, and the setting is spectacular."], "output": "[['brunch', 'neutral'], ['food', 'positive'], ['setting', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere would have been almost perfect if it werent for the fact that we were seat right naext to the noisy kitchen but I guess the speedy service comes with a price."], "output": "[['kitchen', 'negative'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["He roasts tomatoes in the oven to make his fantastic sauce."], "output": "[['tomatoes', 'neutral'], ['sauce', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Multiple televisions on both sides of the cozy room ensure unobstructed sight lines for fans, whether they're sipping pints at the oak bar or snacking on pub munchies--like baked clams, nachos, and buffalo wings--at tall tables in front."], "output": "[['lines', 'positive'], ['baked clams', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Opt for the spectacular Emperor's Meal, a multi-course tasting menu loaded with velvet-textured pumpkin soup, mesclun greens sparked by a simple but savory sesame-soy vinaigrette, crispy sauteed tofu noodles and steamboat soup, a heady clear-broth crock of cabbage, carrots, watercress, mushrooms, walnuts, dates and cherries."], "output": "[['Meal', 'positive'], ['menu', 'positive'], ['pumpkin soup', 'positive'], ['sesame-soy vinaigrette', 'positive'], ['sauteed tofu noodles', 'positive'], ['steamboat soup', 'neutral'], ['cabbage', 'positive'], ['carrots', 'positive'], ['watercress', 'positive'], ['mushrooms', 'positive'], ['cherries', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["You can spend $25 per entree at a much fancier place."], "output": "[['entree', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Another hour waiting for our food, we spoke to the manager, he told us he would give us a discount off our bill."], "output": "[['waiting', 'neutral'], ['food', 'neutral'], ['manager', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I took a few clients for lunch and the service was lackluster, food was fair at best, and the prices were outrageous - Don't wast your time with this place !"], "output": "[['lunch', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Their yogurt breads are very good, but I wasn't impressed with their sandwiches."], "output": "[['yogurt breads', 'positive'], ['sandwiches', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the sushi was good and the service was not as bad as some would have you think but the crowd was more business than hip, more wall st."], "output": "[['sushi', 'positive'], ['crowd', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I've only had take-out from here but a couple of their dishes, along with the spicy green and orange sauces, are amazing."], "output": "[['take-out', 'neutral'], ['dishes', 'neutral'], ['spicy green and orange sauces', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The prices are up there without being over the top but the quality of the food commands it."], "output": "[['prices', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I ordered the empanadas sampler, crab croqueta, and something else I don't remember but I remember (all appetizers) thinking this was the best Cuban meal I had ever eaten."], "output": "[['crab croqueta', 'neutral'], ['appetizers', 'neutral'], ['Cuban meal', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Recently, I celebrated my birthday at this restaurant - it was a brunch for 60 people, all of whom said the food was exceptional."], "output": "[['brunch', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After admitting that the items on the bill were not in line with the menu, the manager reserved the right to price at her own discretion!"], "output": "[['bill', 'neutral'], ['menu', 'neutral'], ['manager', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There wasn't even a decent waiting area--on a Friday night the lounge is full--and when we tried to sit on the only available seating (granite ledge outside of the restaurant) another bouncer w/ an earpiece told us to move."], "output": "[['waiting area', 'negative'], ['lounge', 'negative'], ['seating', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A reservation did not save us from a wait at the bar, but the food was worth it; a grilled calamari appetizier with mushrooms was delicious as was a mixed seafood pasta main course."], "output": "[['reservation', 'neutral'], ['bar', 'neutral'], ['grilled calamari appetizier with mushrooms', 'positive'], ['mixed seafood pasta main course', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["that the waiting is horrific but the food is great."], "output": "[['waiting', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The place is not meant for in house dining, but if you want to grab a meal on the go, this is the perfect choice."], "output": "[['place', 'negative'], ['house dining', 'neutral'], ['meal', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["service, one would be overpaying for the experience and for the food."], "output": "[['service', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The restauarnt is Ok in terms of decor, but the food was really lacking - things were not cooked to order."], "output": "[['restauarnt', 'positive'], ['decor', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The pricing isn't quite clear and look out for that asterisk on the menu where they add on that extra 6-8 bucks."], "output": "[['pricing', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Party of 4 after a Sunday matinee, no reservation, seated promtply, but service was slow."], "output": "[['reservation', 'neutral'], ['seated', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Happy Hour is the best I've ever been too, and the chocolate chip cookies that are passed around throughout dinner are to die for."], "output": "[['chocolate chip cookies', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The bartenders could have been a lot nicer but the drinks they shook up kind of made up for their poor attitude."], "output": "[['bartenders', 'negative'], ['drinks', 'positive'], ['attitude', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food The menu is a paper buffet--pick your cut of meat, dress it in either a sauce or a baked-on chapeau and then pick accessories, such as Yukon gold mashed potatoes, bitter greens or wilted tomatoes with blue cheese."], "output": "[['menu', 'neutral'], ['buffet', 'neutral'], ['meat', 'neutral'], ['sauce', 'neutral'], ['gold mashed potatoes', 'neutral'], ['greens or wilted tomatoes with blue cheese', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter suggested a fantastic Greek wine that was far less expensive then we were willing to spend."], "output": "[['waiter', 'neutral'], ['Greek wine', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food was much better then I had remembered (smaller menu) Great place for lunch."], "output": "[['Food', 'positive'], ['menu', 'negative'], ['lunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Other dishes get a matriarchal moniker: Mom's Meat Loaf with Neapolitan-style Potatoes and Homemade Lasagna, Mom's Style."], "output": "[['dishes', 'neutral'], ['Homemade Lasagna', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiters actually roll their eyes when you order something, as if you are imposing on them by ordering food."], "output": "[['waiters', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["our waiter noticed it was my bday w/o me saying, and brought me cake w/ candles."], "output": "[['waiter', 'positive'], ['candles', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["She then sent over the owner, and his only recourse was to give us a free bottle of sparkling wine."], "output": "[['owner', 'positive'], ['sparkling wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I didn't know what to expect from Frankie and Johnnie's when I made the reservation after my friend told me it was the best steak he had had."], "output": "[['reservation', 'neutral'], ['steak', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For the price you pay, you get good quality and deliciously thin sliced beef."], "output": "[['price', 'neutral'], ['quality', 'positive'], ['beef', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Its two massive rooms are frequented predominantly by Greeks who chow down on traditional mezze--spinach pie, feta cheese and stuffed grape leaves--and entrees--kebabs, sandwiches and pasta dishes."], "output": "[['rooms', 'positive'], ['spinach pie', 'neutral'], ['feta cheese', 'neutral'], ['stuffed grape', 'neutral'], ['sandwiches', 'neutral'], ['pasta dishes', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the food arrived and a 1/3 of the way through my meal i realised that two-thirds of my fish was uncooked."], "output": "[['food', 'neutral'], ['meal', 'neutral'], ['fish', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["when the waitress finally took our order after being seated at the table for over 30 minutes only to wait another 45 minutes for food and when the food arrived the order was incomplete."], "output": "[['waitress', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We waited about 10 minutes for a table and enjoyed peanuts and cocktails at the bar (drinks are $3."], "output": "[['table', 'neutral'], ['peanuts', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Dim, candlelit dining room is accented by a funky star pointed bar and multi-colored ceiling lamps, with trendy upbeat music in the background."], "output": "[['bar', 'neutral'], ['ceiling', 'positive'], ['music', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["a red curry shrimp dish where the only thing on the plate that's tasty is the rice?"], "output": "[['red curry shrimp dish', 'neutral'], ['rice', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The small wooden bar and counter up front incorporate a wine rack and dessert display."], "output": "[['wooden bar', 'negative'], ['wine rack', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["What the sparse space lacks in decor it makes up for in atmosphere."], "output": "[['space', 'negative'], ['decor', 'negative'], ['atmosphere', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["$20/person value included a drink, some bread, and various breakfast selections."], "output": "[['drink', 'neutral'], ['bread', 'neutral'], ['breakfast selections', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["So we said we would have a drink at the bar (the only redeaming quality or value in the whole place was the bartender and the big vodka sour she made me)."], "output": "[['drink', 'neutral'], ['quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Apps- chili shrimp, tempura sashimi, entree's- rack lamb, kobe tartar, crispy spinach."], "output": "[['tempura sashimi', 'neutral'], [\"entree's- rack lamb\", 'neutral'], ['kobe tartar', 'neutral'], ['spinach', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food again was not just a name on the menu but very well made and fresh."], "output": "[['Food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although the wait staff was friendly, the atmosphere was not."], "output": "[['wait staff', 'positive'], ['atmosphere', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Recently a seafood dish was so salty that that one flaw overshadowed otherwise excellent 'side' dishes, apps desert."], "output": "[['seafood dish', 'negative'], [\"'side' dishes\", 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Service during either brunch or dinner could be quicker and more attentive at times."], "output": "[['Service', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["05 bar of melted chocolate in a cup."], "output": "[['bar', 'neutral'], ['chocolate', 'positive'], ['cup', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We decided on several appetizers, the clear winner was the sardines, something I normally wouldnt have tried."], "output": "[['appetizers', 'neutral'], ['sardines', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My companion went to the bathroom and overheard the waiter singing near the back of the place The cappuccino machine is broken, It's broken."], "output": "[['bathroom', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["With so many $20 bottles of wines from which to choose, our waiter helped pick a good one."], "output": "[['wines', 'neutral'], ['waiter', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["From the overstuffed menu to the placemats advertising spectacularly festive drinks, to the comfy booths, the decor signals -- this is indeed your grandfather's diner and thank goodness for it."], "output": "[['booths', 'positive'], ['decor', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Not only is there very little on the menu besides steak, but you really have no choice of what cut of meat to get."], "output": "[['menu', 'neutral'], ['steak', 'positive'], ['meat', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The main meal, a red snapper, was not bad, but after hoping I would experience a true spanish experience, the remaining dinner lost its appeal."], "output": "[['red snapper', 'positive'], ['remaining dinner', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The only complaints (minor) was a 15 minute wait when we had a 10 PM reservation and the tables are pretty close to one another."], "output": "[['wait', 'negative'], ['reservation', 'neutral'], ['tables', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After a couple of drinks upstairs before our meal, we slipped downstairs to a nice corner table that offered plenty of privacy in this 'loud' place."], "output": "[['drinks', 'neutral'], ['corner table', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although tiramisu was ordered on every other table, and looked very yummy, at the end of our meal I was simply too full to try."], "output": "[['tiramisu', 'neutral'], ['meal', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["employees not fighting with each other in front of clients 3 having ALL the ingredients for the meals they have on there menue."], "output": "[['employees', 'negative'], ['ingredients', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I came in for brunch with my parents on Saturday and the place was packed."], "output": "[['brunch', 'neutral'], ['parents', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The staff was gracious enough to keep her arrival a secret by letting us wait at the bar and holding our table for us until she and our father arrived 45 minutes late (delayed flight)."], "output": "[['staff', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My wife and I, from Houston, and another couple from Conneticut were visiting Manhattan for the weekend and I chose Shula's for dinner because I had heard that it was a good steak house."], "output": "[['dinner', 'neutral'], ['steak house', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I would wait for a table next time, the food was that good."], "output": "[['table', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Also excellent is the okonomiyaki, a tangy cabbage, pork and shrimp frittata topped with bonito flakes and a dollop of mayonnaise."], "output": "[['cabbage', 'positive'], ['pork', 'positive'], ['shrimp frittata topped', 'neutral'], ['mayonnaise', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My sashimi was just ok with very little flavor from the sauces they supposedly put on them and the napolean had something that stuck out in the flavor, not in a good way."], "output": "[['sashimi', 'positive'], ['sauces', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The simple corn tamale comes with a mild homemade sour cream, and the inexpensive enchiladas, prepared with expertly spiced strips of beef, could easily serve as an entree."], "output": "[['corn tamale', 'positive'], ['homemade sour cream', 'positive'], ['spiced strips', 'positive'], ['entree', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They make pizza the way you should with lots of sauce."], "output": "[['pizza', 'neutral'], ['sauce', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We ordered a platter that was an asssortment of appetizers which was great recomendation."], "output": "[['platter', 'positive'], ['appetizers', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Choppy service with a bit of attitude thrown in -when we asked for the restaurant week prix fix menus the aiter made a face."], "output": "[['service', 'negative'], ['menus', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The wait staff while attentive did nothing to address the hair that was found in one of our dishes."], "output": "[['wait staff', 'positive'], ['dishes', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had the tuna, which tasted like dead fish that laid in the sun for 3 wks."], "output": "[['tuna', 'neutral'], ['fish', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After waiting an hour and a half, a delivery man - with heavily bleeding gums - told me not to worry, that my meal had been replaced with fresh food, and that my old order had been RE-SERVED to another customer."], "output": "[['delivery man', 'negative'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service sucks every time, but the food is usually tasty, even though the menu leans toward the boring and expected of French fare."], "output": "[['service', 'negative'], ['food', 'positive'], ['French fare', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Get it served with rice and vegetables (yummy), some house red wine, nice big plate of tzatziki, saganaki and you'll be in heaven."], "output": "[['rice and vegetables', 'positive'], ['red wine', 'neutral'], ['plate', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Waiter had to lean on my husband to give people next to us their food."], "output": "[['Waiter', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In fact, our waiter mis-pronounced many of the items on the menu."], "output": "[['waiter', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Their menu has just been updated featuring new rolls and more choices."], "output": "[['menu', 'neutral'], ['new rolls', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the foods so tasty(the soup maybe a little blandbut ill forgive them only because everything else is out of this world."], "output": "[['foods', 'positive'], ['soup', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This place basically has the same menu as Penang but everything is cheaper, including the atmosphere."], "output": "[['menu', 'neutral'], ['atmosphere', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The turkey burgers are thick and juicy and they pile the mushrooms on!"], "output": "[['turkey burgers', 'positive'], ['mushrooms', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When the bill came, the waiter snatched it back so he could add the $3 difference to the wine."], "output": "[['waiter', 'negative'], ['wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Bread had a oil on it so it was messy."], "output": "[['Bread', 'negative'], ['oil', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["To sum it up: Service varies from good to mediorce, depending on which waiter you get; generally it is just average Ok."], "output": "[['Service', 'negative'], ['waiter', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I didn't take a look at the rest menu, but the oysters were fantastic."], "output": "[['menu', 'neutral'], ['oysters', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Before we can even order desert, the waitress comes and tells us we have to leave because the host wanted our table."], "output": "[['waitress', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I ordered their famous buffalo steak which originally would come with homemade potatoe gnocchi but I chose the sauteed spinach with garlic instead, which turned out to be exceptional."], "output": "[['buffalo steak', 'positive'], ['potatoe gnocchi', 'neutral'], ['spinach with garlic', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Everything we had from the scallop starter to the rare ribeye, right through dessert was impeccible."], "output": "[['scallop starter', 'neutral'], ['dessert', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The bread was served, one razor thin slice on our bread plate, by the waiter."], "output": "[['served', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food and service were very good but prices were a bit high for the portions."], "output": "[['Food', 'positive'], ['service', 'positive'], ['prices', 'negative'], ['portions', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My wife I went here for a Birthday dinner and were immediately impressed with the wine list."], "output": "[['dinner', 'neutral'], ['wine list', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I asked the captain to bring the food in separate bags and he loudly said, Oh, I guess you are not getting lucky tonight."], "output": "[['captain', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food The most dependable route is to stick to appetizers--the cheese bread is quite good--and drinks."], "output": "[['Food', 'positive'], ['appetizers', 'neutral'], ['cheese bread', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["During my meal the waiter and waitress gathered with other friends that had arrived and they spent the whole time talking and ignoring the clientele."], "output": "[['meal', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This is a don't miss if you are anywhere close to the area, but if you're going for lunch, be there by noon to avoid a wait."], "output": "[['are a', 'neutral'], ['lunch', 'neutral'], ['wait', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Mostly, this small restaurant offers eggs, hot sandwiches and traditional American platters."], "output": "[['eggs', 'neutral'], ['hot sandwiches', 'neutral'], ['American platters', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When we went up to get what we assumed would be our second drink at no charge, the bartender charged us $5 a piece."], "output": "[['drink', 'neutral'], ['bartender', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had perhaps the finest buffalo mozerella and tomato salad - the cheese seemed to melt in my mouth, and the tomatos were red, ripe and sweet."], "output": "[['finest buffalo mozerella and tomato salad', 'neutral'], ['cheese', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the solitary waitress was friendly though i found her service a little slow."], "output": "[['solitary waitress', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I thought it was great, best service I've ever had in a long time."], "output": "[['service', 'positive'], ['time', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This is authentic Japanese food - California roll is not on the menu."], "output": "[['Japanese food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The salads were like those we were served in Paris, and the Eggs Benedict were out of this world."], "output": "[['salads', 'neutral'], ['Eggs Benedict', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu is limited: chicken, rice beans, frozen fish (shrimp, whiting, crab sticks), and french fries, but one receives EXCELLENT value for the money and it is SO WORTH walking down the block for."], "output": "[['menu', 'negative'], ['chicken', 'neutral'], ['rice beans', 'neutral'], ['whiting', 'neutral'], ['crab sticks', 'neutral'], ['french fries', 'neutral'], ['value', 'positive'], ['the money', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We got the cold appetizer sampler and the dish was FULL of food, all for $12."], "output": "[['dish', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["From making the reservation (not required) to the before dinner drink (cava), to the table (romantic), to the the ambiance (candles, spanish antiques, etc) to the food of course (original, incredibly deep and rich in flavor) to our departure and saying goodnight to the waiter."], "output": "[['reservation', 'neutral'], ['ambiance', 'neutral'], ['candles', 'neutral'], ['antiques', 'neutral'], ['food', 'positive'], ['flavor', 'positive'], ['waiter', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Try the Duck Confit Hash (topped with two eggs) or the Beer Battered Fish Chips on the Brunch menu."], "output": "[['Duck Confit Hash', 'positive'], ['Beer Battered Fish Chips', 'positive'], ['Brunch menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They don't take reservations, though, so you have to get there by 8:00 to get a good table."], "output": "[['reservations', 'neutral'], ['table', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The man working the door (red hair)-very funny and warming."], "output": "[['man', 'positive'], ['door', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitress did try to get the manager to at least give us the Sangria on the house but the manager refused."], "output": "[['waitress', 'negative'], ['Sangria', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Well, what can I say about a restaurant with a takeaway menu completely devoid of sugar, butter, or deep-fried anything?"], "output": "[['sugar', 'negative'], ['butter', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["One example: They literally took bread from my baby, after we ordered a brick oven pizza, not food (the waiter's words)."], "output": "[['pizza', 'negative'], ['waiter', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In the most beautiful ground floor brownstone setting."], "output": "[['ground', 'positive'], ['setting', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["*There is a pre-theatre dinner menu for early diners that is of great value."], "output": "[['pre-theatre dinner menu', 'positive'], ['diners', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When our turn came to get in, we were told that the place was full due to the Labor Day weekend and we could not get inside unless we bought a 200$ bottle of vodka."], "output": "[['place', 'negative'], ['vodka', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Not the most adventurous nor exquisite food, but generous portions (at least, on the 3-course prix fixe) that were faultlessly executed, complemented by a varied wine list ranging from that special bottle for a celebratory splurge to excellent choices under $50."], "output": "[['food', 'negative'], ['portions', 'positive'], ['wine list', 'positive'], ['bottle', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["What I can say is that it was definitely some very good quality pizza, no matter what area of the world/style of pizza you are used to."], "output": "[['quality pizza', 'positive'], ['pizza', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["However, the service was so excellent, we added $10 to the tip!"], "output": "[['service', 'positive'], ['tip', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Portions are fairly generous and the staff brings out multiple little bites and treats throughout dinner."], "output": "[['Portions', 'positive'], ['staff', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The loud belly dancer with her scarf dragging across my food and table, almost knocked over my water glass."], "output": "[['belly', 'negative'], ['food', 'neutral'], ['glass', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["they used to have grilled panini for under $9 at lunch which was great considering that its a sitdown restaurant with service, but i didnt see those options when i came here this week."], "output": "[['grilled panini', 'positive'], ['lunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We decided to share order of filet mignon for the table because there was just not enough food."], "output": "[['filet mignon', 'neutral'], ['the table', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Chicken Tikka is so moist, plump, seasoned so well and simply divine (you don't need any extra sauces to get this well marinated chicken down."], "output": "[['Chicken Tikka', 'positive'], ['sauces', 'neutral'], ['marinated chicken', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Or better yet, if on a budget and want to do something romantic, stop at the bar for a drink and enjoy the sunset."], "output": "[['bar', 'neutral'], ['sunset', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was delicious but we were rushed through dinner because they were closing soon (since we were seated an hour later than we should have)."], "output": "[['food', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Comfort food is the restaurant's strength: Braised short ribs are promising, the Nicoise salad (with seared tuna) is fresh and tasty and the mashed potatoes are, true to form, delectable."], "output": "[['Comfort food', 'positive'], ['Braised short ribs', 'positive'], ['Nicoise salad', 'positive'], ['seared tuna', 'neutral'], ['mashed potatoes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although we were seated quickly, ambiance was cozy, service was decent the overall menu selection and overall food taste and presentation was less to be desired!"], "output": "[['ambiance', 'positive'], ['service', 'positive'], ['food taste', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["worst margaritas in town,if you are going to order a battle of (white wine)they served hot."], "output": "[['white wine', 'neutral'], ['served hot', 'neutral'], ['margaritas', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["So, get drinks elsewhere, have a nice dinner here, and stop by the package store on the way home where you can get a bottle of Bombay Sapphire for the cost of 2 drinks here."], "output": "[['dinner', 'positive'], ['bottle', 'neutral'], ['cost', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Decent eggs (just about everything on the menu is coated in this amazing hollandaise)."], "output": "[['eggs', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It was my birthday and although they came out with of a bottle of bub, I felt embarrassed about the lack of service."], "output": "[['bottle', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food There's a Mediterranean bent to the menu--hummus, babaganoush and stuffed grape leaves are offered, as well as Moroccan chicken and spicy Merguez lamb sausage."], "output": "[['Food', 'neutral'], ['Mediterranean', 'neutral'], ['menu', 'neutral'], ['babaganoush', 'neutral'], ['stuffed grape', 'neutral'], ['Moroccan chicken', 'neutral'], ['Merguez lamb sausage', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Dining choices range from three-course, ingredient-themed tasting menus or a regular, seasonal a la carte menu."], "output": "[['Dining choices range', 'neutral'], ['menus', 'positive'], ['la carte menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Pastas include shellfish-stocked linguine with tomato sauce, and an excellent homemade cheese ravioli--all are available in half portions."], "output": "[['Pastas', 'neutral'], ['linguine with tomato sauce', 'positive'], ['homemade cheese ravioli', 'positive'], ['portions', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Specialty drinks--alcoholic and non--arrive in skull mugs or mini-canteens, nifty take-home souvenirs."], "output": "[['Specialty drinks', 'neutral'], ['souvenirs', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["No specials and no crab limited the menu choices, and the toast for my (very average) foie gras arrived 5 minutes after the rest of the food, and was cold and burnt."], "output": "[['specials', 'negative'], ['crab', 'negative'], ['menu choices', 'neutral'], ['foie gras', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We decided to ask for our check for the wine we had and the waiter became completely annoyed at us!"], "output": "[['wine', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In all cases, service is slow but it's not the waiters fault."], "output": "[['service', 'negative'], ['waiters fault', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After the waiter finally took our order and gave us our food he never came back."], "output": "[['waiter', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The wait (despite reservation) was 35 minutes (in an over-crowded bar) no apologies whatsoever."], "output": "[['wait', 'neutral'], ['reservation', 'neutral'], ['bar', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had a reservation and 2 of us showed up on time and notified the hostess that we were there but the other 2 were running a few minutes late."], "output": "[['reservation', 'neutral'], ['hostess', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Get some drinks and listen to the free live music."], "output": "[['drinks', 'neutral'], ['music', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This place is decent if you want to hang out with friends (who don't mind paying up) in a low-key atmosphere with good food, but don't mind putting up with sub-par level of service."], "output": "[['atmosphere', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went there with family and even though we had reservations, we were seated 30 minutes late, the food took 45 minutes to arrive and when I got the wrong order, I had a hard time trying to find the server."], "output": "[['reservations', 'neutral'], ['food', 'neutral'], ['server', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["our waiter spilled an entire glass of water on my brother and didn't so much as acknowledge it, let alone apologize."], "output": "[['waiter', 'negative'], ['glass of water', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["we walked in to the resturant, squeezed by our (to be) waiter (who ignored us and didnt step to the side), and straight up to the host (he was busy talking to the bar tender)."], "output": "[['waiter', 'negative'], ['host', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Unlike the reviewer before me, what made me KEEP going back was the great reception I received from the bouncers and I needed several cocktails to endure the waitstaff."], "output": "[['cocktails', 'neutral'], ['waitstaff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you're going with a date to a lounge on that street, stop there for a drink and a quick appetizer first."], "output": "[['lounge', 'neutral'], ['drink', 'neutral'], ['appetizer', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The sexy waiter suggested the Pineapple Basil ( I Know is sounds yucky, but MMMM) Martini."], "output": "[['waiter', 'positive'], ['Pineapple Basil', 'neutral'], ['Martini', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was good but it will not make up for the negligent, rude, condescending and hostile service with the full support of their management we received."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I guess if you order the chef's tasting menu, which is a seven course meal with an optional wine matching for $125pp then your tummy will be well satisfied."], "output": "[['chef', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When we requested a table our bar tab was quickly transferred and the LOVELY hostess sat us at a table of our choice - we chose the corner."], "output": "[['hostess', 'positive'], ['corner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is good, and we won't let one bad apple spoil the batch."], "output": "[['food', 'positive'], ['apple', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Went on a Saturday with out of town tickets and the food was great but the service was awful, even surely."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["we shared many dishes but none really stood out except the spinach, wow!!"], "output": "[['dishes', 'neutral'], ['spinach', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Few styles of cooking place such an importance on texture--baby eels in a sizzling slick of oil, for example, is nudged just a shade away from pasta by the crackle of tiny bones under your teeth."], "output": "[['texture', 'positive'], ['oil', 'neutral'], ['pasta', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Encouraged, I went back for dinner and was again impressed: crisp, spicy asparagus spears (tad too spicy?"], "output": "[['dinner', 'neutral'], ['asparagus spears', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While you're standing around for a good half hour waiting for two plain burgers, you're being bumped into by people waiting to be seated because of the narrow passageway leading to the dining area."], "output": "[['hour waiting', 'negative'], ['burgers', 'neutral'], ['area', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Sushi pieces are smaller if u r a 'buffet' customer and choices are rather limited and there's really nothing special on the menu."], "output": "[['Sushi', 'negative'], ['choices', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waitress was pleasant but slow, and the food is simply not good enough to be treated like a nuisance."], "output": "[['waitress', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The head waiter made some lame excuse about how the chef had asked the hostess to revise the menu but it had not been changed."], "output": "[['waiter', 'negative'], ['hostess', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Later in the evening after our meal we finally found the real owner behind the bar of the restaurant and explained to him the situation which he had been made aware of by the waitress."], "output": "[['meal', 'neutral'], ['owner', 'neutral'], ['bar', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The only concern i have is with the slighly all-business waitstaff who order and throw the food down, rushing you out."], "output": "[['waitstaff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The price wouldnt be so bad if it wasnt for the poor service, average food, and uninspired menu selections (choice of tiramisu and strawberries with whipped cream for dessert?!"], "output": "[['price', 'negative'], ['service', 'negative'], ['menu selections', 'negative'], ['tiramisu', 'neutral'], ['cream', 'neutral'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you're not looking for a pretentious atmosphere and a restaurant that serves the best steak you've ever eaten."], "output": "[['atmosphere', 'positive'], ['steak', 'positive'], ['restaurant', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food *was* pretty good, though, (though certainly not worth the prices) so it's worth checking out if you have an expense account to work with."], "output": "[['food', 'positive'], ['prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Entrees range from strongly seasoned nori-wrapped rare tuna with wasabi-soy vegetables to simple wood-grilled halibut with light caper vinaigrette."], "output": "[['tuna with wasabi-soy vegetables', 'positive'], ['light caper vinaigrette', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After all, fresh fish, vegetables and fruits in season, olive oil, lemon and oregano are ingredients readily available on the Mediterranean."], "output": "[['fish', 'positive'], ['vegetables', 'positive'], ['fruits', 'positive'], ['olive oil', 'neutral'], ['lemon', 'neutral'], ['oregano', 'neutral'], ['ingredients', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Made with extra egg yolks, the custard has more flavor than traditional scoops; it's also got less than half the fat of premium store-bought pints."], "output": "[['egg yolks', 'positive'], ['flavor', 'positive'], ['traditional scoops', 'neutral'], ['fat', 'positive'], ['premium', 'positive'], ['pints', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter was great and we even got drinks and some food courtesy of the cheff- maybe because it wasn't so busy when we went."], "output": "[['waiter', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["*Food:Just about anything on the menu, however the sandwhiches are most popular and recommended."], "output": "[['menu', 'neutral'], ['sandwhiches', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["And when I received my $9 glass of wine, I had to ask the waitress if she planned on putting more in -- there was hardly any liquid in the glass!"], "output": "[['glass of wine', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Any sandwich or appetizer on the menu is delicious."], "output": "[['sandwich', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The hamburger showed up long before the mussels, and the waiter suggested I start eating because he didnt want my food to get cold."], "output": "[['mussels', 'neutral'], ['waiter', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Try the tea service (just $14 includes a pot of tea, tea sandwiches, warm scone, dessert, and other goodies), and come by yourself or with a friend."], "output": "[['tea service', 'positive'], ['pot of tea', 'neutral'], ['tea sandwiches', 'neutral'], ['scone', 'positive'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Outside the realm of steak, things aren't so certain: The pork chops can be a bit tough, lobster tails aren't the greatest and the special salad isn't."], "output": "[['realm', 'neutral'], ['steak', 'neutral'], ['pork chops', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I've had the ribeye, the salmon, and a burger/fries at the bar, and they were all exceptional."], "output": "[['salmon', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Was a bit disappointed by the sashimi (the sauce a bit greasy) and dumpling (all you taste is the pepper) appetizers but the entrees (chicken and sea bass) were really fresh and tasty."], "output": "[['the sauce', 'negative'], ['dumpling', 'negative'], ['entrees (chicken and sea bass)', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["anyway, nice place for brunch for selection under $20 meals desserts were great (3 flavors for creme brulee!!"], "output": "[['place', 'positive'], ['brunch', 'neutral'], ['selection', 'neutral'], ['meals desserts', 'positive'], ['flavors', 'neutral'], ['creme brulee', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["for our entree without a waiter in sight."], "output": "[['entree', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I tried the price fix and te waiter looked offended when I requested the price fix menu."], "output": "[['waiter', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When we sat down, the waiter barely looked in our direction and abruptly shoved our menus on the table."], "output": "[['waiter', 'negative'], ['menus', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My friend ordered the scallops which were served in a light red sauce that was complemented very nicely with atichoke palms."], "output": "[['served', 'neutral'], ['light red sauce', 'neutral'], ['palms', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was horrible, and full of small bones, the dessert was advertised as homemade ice cream and pastries--but we only received 2 small scoops of commercial ice cream--no pastries."], "output": "[['dessert', 'neutral'], ['ice cream and pastries', 'positive'], ['commercial ice cream', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My nice waitress even came running out of the restaurant to hand me a tiny box I had forgotten on the table."], "output": "[['waitress', 'positive'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Bland food, arroganrt waiters."], "output": "[['food', 'positive'], ['waiters', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The cajun food is great but there is something for everyone on the menu and I have yet to be disappointed."], "output": "[['cajun food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere of the place is nice as well as the location, but I found food mediocre and too expensive for the quality offered."], "output": "[['atmosphere', 'positive'], ['place', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food The French-Belgian menu is small, and everything on it is satisfyingly savory, such as a simple pot of mussels in a choice of sauces (beer and bacon, creamy mushroom, or white wine-and-garlic broth); beef stewed with beer and prunes; and a juicy croque monsieur."], "output": "[['Food', 'negative'], ['pot', 'positive'], ['mussels', 'neutral'], ['choice of sauces', 'neutral'], ['white wine-and-garlic broth', 'neutral'], ['beef stewed with beer', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Not only is it the nicest atmosphere with an antique bar and allabaster globes sconces, marble fireplace."], "output": "[['atmosphere', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We reserved the downstair lounge for private parties and the price was fairly reasonable."], "output": "[['downstair lounge', 'neutral'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["after such a strong showing, dessert was a letdown per our waiters recommendation, we ordered the raspberry softie the coconut-stuffed apricots the softie tasted like a mixture between cough syrup a starburst, whereas the apricots were extremely sour."], "output": "[['dessert', 'negative'], ['waiters', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["great food, but not low fat."], "output": "[['food', 'positive'], ['fat', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When asked what the waitress recommended she just named a few things off the menu without saying why."], "output": "[['waitress', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The spicy tuna is great, as is the seasonal spider roll, (soft shell crab)."], "output": "[['spicy tuna', 'positive'], ['spider roll', 'positive'], ['soft shell crab', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitstaff briskly plunks down dishes that take alarmingly little time to make, which, in addition to dumplings, include sizzling platters of meat and lo mein noodles."], "output": "[['dishes', 'neutral'], ['meat', 'positive'], ['mein noodles', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The place is small and intimate and you may feel a little crowded, but the service is excellent and it's great for friends out, a romantic date, or a special occassion."], "output": "[['place', 'negative'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Sometimes I wish there were a bar to sit at and have a glass of wine, but on the other hand the lack of one allows the place a pleasant sit down sort of feel."], "output": "[['bar', 'neutral'], ['glass of wine', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I can't imagine how small the fish portion on the $10 lunch menu must be if I got the large one."], "output": "[['fish portion', 'negative'], ['lunch menu', 'neutral'], ['one', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I just think the prices are high for the type of food the kitchen turns out as well as the portion sizes."], "output": "[['prices', 'negative'], ['food', 'neutral'], ['portion sizes', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This is a very small 4 tables or so restaurant with a very modest enviornment, so if you're with business partners for lunch or dinner, Plataforma Restaurant or Brazil Grill are the better choices, but if you got a lot of time with some buddies of yours, then this one may be for you."], "output": "[['lunch', 'neutral'], ['dinner', 'neutral'], ['Grill', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["You can go to all these gormet places and eat expensive pizza this is the best cheese, sauce, bread its a done deal."], "output": "[['pizza', 'negative'], ['cheese', 'positive'], ['sauce', 'positive'], ['bread', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitress asked us if we'd be eating dinner."], "output": "[['waitress', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The owner lied to me when i asked where our food was 1 hour after we placed the order - he said oh your friend said you were not ready for it."], "output": "[['owner', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service is Ok, but they must have drank the coolade, as they believe that they are serving good food!"], "output": "[['service', 'positive'], ['serving', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["No compensatory nibbles or drinks were supplied -- even after we indicated to the waiter that it was 'the right thing to do'"], "output": "[['nibbles', 'negative'], ['drinks', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My party got the dessert sampler which included 6 highlights from the dessert menu--each of which were worth the price of the three course meal ($90 per person with margaritas, tax, and tip)."], "output": "[['dessert sampler', 'neutral'], ['dessert menu', 'neutral'], ['the three course meal', 'positive'], ['margaritas', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The bartender said that they didn't have one, but did say, We have mixed drinks."], "output": "[['bartender', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Great roofdeck, nice group of 30 somethings, but no music, kind of quiet."], "output": "[['roofdeck', 'positive'], ['music', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the place is small but everything else is 'big' in terms of quality variety and smiles of the wait service."], "output": "[['place', 'negative'], ['quality variety', 'positive'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The coffee by the name of the place is delicious and although the space is a bit tight, it's a great place to chat, chill or simply enjoy a great cup of joe."], "output": "[['coffee', 'positive'], ['space', 'negative'], ['cup', 'positive'], ['joe', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I requested a Riesling and the waiter recommended staying with the Sencere which didn't come by the glass according to the menu but he provided it to us any ways."], "output": "[['waiter', 'negative'], ['glass', 'neutral'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Pad thai and a variety of noodle soups, such as pho bac and Bangkok Curry, round out the menu and arrive in heaping portions."], "output": "[['menu', 'neutral'], ['portions', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The mussles had be be a portion of maybe 8-9 mussles only and the gnocci were basically all garlic- garlic is just meant to be a condiment- way tooo much garlic."], "output": "[['portion', 'neutral'], ['gnocci', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When the waitress brought the check after an hour, she finally noticed that I had been sitting without food and offered to get it for me."], "output": "[['waitress', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I don't understand the other negative reviews of the service because we had amazing waiter."], "output": "[['service', 'neutral'], ['waiter', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Al Di La serves up an impressive selection of options ranging from meditarranean fish to rabbit to to duck to pasta."], "output": "[['options', 'positive'], ['fish', 'neutral'], ['pasta', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Many Thais top off spicy dishes with a fried egg, but in many places it's not on the menu and when requested, I will either get charged $1."], "output": "[['dishes', 'positive'], ['a fried egg', 'neutral'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food At dinner, a nicely gamey chopped liver mousse, watercress salad with blue cheese and walnuts, and meat loaf with mashed potatoes stand out among the menu's bistro fare."], "output": "[['dinner', 'neutral'], ['gamey chopped liver mousse', 'positive'], ['watercress salad with blue cheese', 'positive'], ['menu', 'neutral'], ['fare', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were given only one waiter for 20 people, and it honestly took over 1/2 an hour to get coffee (I actully went across the street to Dunkin Donuts!)"], "output": "[['waiter', 'negative'], ['coffee', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My dining experience with friends started off very badly - 40 minute wait WITH a reservation and having to repeatedly ask for bread and water - but ended on a better note."], "output": "[['dining', 'negative'], ['wait', 'neutral'], ['reservation', 'neutral'], ['water', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While the restaurant/space itself isn't so great (somewhat cramped cheesy interior, and the name implies its a burrito take-out place), the service and food outway its few cons."], "output": "[['interior', 'negative'], ['burrito take-out place', 'neutral'], ['service', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The uptight female manager came up to our table and rudely asked us to get up because they had a party waiting to eat."], "output": "[['manager', 'negative'], ['waiting', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This is definitely not a place to come for lunch because you can get the same food from a corner deli at half the price they charge here."], "output": "[['lunch', 'neutral'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Fortunately the hostess was nice enough to take our appetizers off the bill after we complained."], "output": "[['hostess', 'positive'], ['appetizers', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service is smart and though they can be overwhelmed with the crowds, does a good job."], "output": "[['service', 'positive'], ['crowds', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Appetizers took their sweet time in coming, and literally about an hour later we had our main dishes which were very small considering the price."], "output": "[['Appetizers', 'neutral'], ['time', 'positive'], ['main dishes', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food had a somewhat elevated price tag but but fair considering the Nobu origin - The cocktails highly recommended including the spide and lobster roll - we were well plated and did not encounter any arragance from the staff - maybe the other student reviewers are used to cafeteria service."], "output": "[['price', 'negative'], ['cocktails', 'positive'], ['spide', 'positive'], ['lobster roll', 'positive'], ['staff', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I would not suggest dining here unless you get a different server."], "output": "[['dining', 'negative'], ['server', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For lunch, try the white meat chicken salad."], "output": "[['lunch', 'neutral'], ['white meat chicken salad', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They don't offer recommendations, take a long time with drink orders, don't check back after serving the entree, and plan on waiting a long time for the check."], "output": "[['serving', 'neutral'], ['entree', 'neutral'], ['waiting', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["One waiter came by and literally threw the $36 salad on the table."], "output": "[['waiter', 'negative'], ['salad', 'neutral'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had to call him over 3 times during the meal because he gave us the wrong food, did not bring water after we asked twice, gave me the wrong drink, and did not check on us once."], "output": "[['meal', 'neutral'], ['food', 'negative'], ['drink', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The owner kindly gave us appetizers on the house to make our now, long wait, more pleasant, but of course they took forever to arrive and were insufficient."], "output": "[['owner', 'positive'], ['appetizers', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I adore Zen Palate - and both the formal upstairs dining room and the crowded, counter-style cafe downstair, have their pros and cons."], "output": "[['Zen', 'positive'], ['formal upstairs dining room', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After spending over $500 on a business dinner, a manager knelt down at our table and asked us to quote, wrap it up and move to the bar."], "output": "[['dinner', 'neutral'], ['manager', 'negative'], ['table', 'neutral'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["To SM's credit, our waiter was eventually replaced and the matre d' offered us free dessert, but we're not going back there ever again."], "output": "[['waiter', 'neutral'], ['dessert', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The entrance is a bit unwelcoming, after you pass throught the glass doors you enter a cedar rich hallway and the woods at the entrance and downstairs are rich, but to my horror the main dining room is wallpapered in faux wood veneer making it look like a bad episode of trading spaces."], "output": "[['glass doors', 'neutral'], ['woods', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It's a shame you can't even sample the food or sit in what is a very nice space."], "output": "[['food', 'neutral'], ['space', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["also, when i was waiting to be seated the bartender gave great service and mixed a mean cocktail for me."], "output": "[['bartender', 'neutral'], ['service', 'positive'], ['cocktail', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It gets crazy busy like any other bar on the weekends, so don't go there on a busy night if your looking for a quiete dinner party or fine dining service."], "output": "[['bar', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A friend was dieing for chorizo but it was only in the tapas menu which we couldn't have."], "output": "[['chorizo', 'positive'], ['tapas menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This is the local spot where we can always count on for a great brunch, a California Burger, the best fries or their carrot dressing for salads."], "output": "[['carrot dressing', 'neutral'], ['salads', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This place is good but food and service is presented for the masses, not much personalized service considering the price tag and that it is a  full-evening-out type of dinner place."], "output": "[['food', 'negative'], ['dinner place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While it can get pricey, 25$ for a lobster 3sides and a refillable drink, its tons of fun, and the food tastes great!"], "output": "[['lobster', 'neutral'], ['refillable drink', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter said they mixed it up because there were three similar things on the menu."], "output": "[['waiter', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Dinner's nothing to scream about (although there are a few winners on the menu), but solid margaritas and appetizers are well-suited for a summer evening."], "output": "[['menu', 'neutral'], ['margaritas and appetizers', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Mysteriously, the reserved tables all stayed empty throughout our meal and were still empty when we left an hour later."], "output": "[['reserved tables', 'negative'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["On the other hand, I never felt rushed to vacate the place at the end of my meal."], "output": "[['place', 'negative'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food Brasserie favorites are prepared by the book: Onion soup gratinee bubbles with a thick layer of Gruyere cheese, and grilled shell steak is served medium-rare, with a side of crisp shoestring potatoes."], "output": "[['Food', 'positive'], ['Onion soup gratinee', 'neutral'], ['Gruyere cheese', 'neutral'], ['served', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I asked one of the more elderly managers what we were eating and he joked that he didn't really know so he referred someone else to us who basically repeated what was written in the menu."], "output": "[['managers', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["ASK for spice adjustments or for special orders, if you think you'll need them, BUT most dishes are GREAT as the staff prepares them."], "output": "[['dishes', 'positive'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["was out of water for 1/2 the meal, salad was never delivered, waitress never came by to see how our party was doing."], "output": "[['meal', 'neutral'], ['salad', 'negative'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Had a few appetizers; smoked duck was served cold but good flavor, tofu was good/fresh too, nothing to rave about though."], "output": "[['appetizers', 'neutral'], ['flavor', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had to ask the busboy if bread came with our meal, which it did and we received after waiting about 30 minutes."], "output": "[['busboy', 'neutral'], ['meal', 'neutral'], ['waiting', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food The free chips-and-salsa may suggest casual Tex-Mex cooking, but this menu is a couple notches above."], "output": "[['Food', 'neutral'], ['menu', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu holds no letdowns: Desserts, like a cone of stiff kulfi with licorice, ot cinnamon souffle, extend dinner's spice into the sweet realm."], "output": "[['menu', 'positive'], ['Desserts', 'neutral'], ['souffle', 'neutral'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The place was a bit noisy, but sitting on the edge of the restaurant helped, and although the portions were small, w/ an appetizer it was the perfect amount of food."], "output": "[['portions', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Id say a little better than most Thai Ive eaten, and the menu had an astounding selection, which isnt bad for such a reasonable price."], "output": "[['menu', 'neutral'], ['selection', 'positive'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Nonetheless, it's an excellent pie -- and don't let the long lines scare you off -- they keep them moving."], "output": "[['pie', 'positive'], ['lines', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This place is the tourist fav of chinese food in the city, the service was fast, but the taste of the food is average, too much starch used in dishes, and the flavors of different dishes are very similar, can't really tell the difference."], "output": "[['chinese food', 'neutral'], ['the food', 'negative'], ['flavors of different dishes', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The owner himself one time came to our table to clear our dishes when our waiter didn't show (a rare occurance, but it was late at night)."], "output": "[['owner', 'positive'], ['dishes', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["they continue to expand their garden space, w/out expanding their kitchen and cannot provide even adequate service."], "output": "[['garden space', 'positive'], ['kitchen', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were seated fastly enough, and ordering was painless, but I got the wrong appetizer, we both received the same item instead."], "output": "[['ordering', 'neutral'], ['appetizer', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Choices are standard and plentiful: omelettes and egg dishes, pancakes, bagels, muffins, croissants, mini-doughnuts, cookies, etc."], "output": "[['Choices', 'positive'], ['egg dishes', 'neutral'], ['pancakes', 'neutral'], ['muffins', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Waiters had to reach over people to deliver food."], "output": "[['Waiters', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service was horrible- the 'manager' took my our order - did not write it down- and two of us were given the wrong apps and or entrees."], "output": "[['service', 'negative'], ['entrees', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Even if their service was not top notch at all times, at least the wait staff was very accommodating and respectful."], "output": "[['service', 'negative'], ['wait staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service was very rushed and as we were finishing our drinks and paying our bill, the owner asked us to leave so he could seat other people at our table."], "output": "[['service', 'negative'], ['drinks', 'neutral'], ['owner', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["however the dessert porportions somehow ballooned to regular conventional sizes."], "output": "[['dessert', 'neutral'], ['sizes', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Summary good service, bad food!"], "output": "[['service', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It was spaced out (we had the 80pp), toro appetizer was so smooth, we had quail, numerous sushi, soup, pumpin puree and more."], "output": "[['toro appetizer', 'positive'], ['quail', 'neutral'], ['sushi', 'positive'], ['soup', 'neutral'], ['pumpin puree', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Not to mention that the busboy spilled 2 glasses of water on my back and the Manager was NOWHERE TO BE SEEN."], "output": "[['busboy', 'negative'], ['glasses of water', 'neutral'], ['Manager', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I made reservations one week in advance and although I had to change it at the last minute, the hostess was very accommodating and we got seated promptly upstairs overlooking the Buddha."], "output": "[['reservations', 'neutral'], ['hostess', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["And once the bill was paid, the bartender kept on giving us drinks."], "output": "[['bill', 'neutral'], ['bartender', 'positive'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food came out really quick and the service overall was not bad."], "output": "[['food', 'positive'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Breakfast, Lunch and Dinner are all great, but they are hit or miss with some of their pasta dishes."], "output": "[['Breakfast', 'positive'], ['pasta dishes', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene The bar's upbeat Latin music, colorful stools and cocktail napkins, and a fruity drink menu are the first confirmations that Agozar lives up to its translation: A good time."], "output": "[['Scene', 'neutral'], ['bar', 'neutral'], ['upbeat Latin music', 'neutral'], ['stools', 'positive'], ['cocktail napkins', 'positive'], ['fruity drink menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Though there are a handful of Japanese a la carte offerings on the menu, the prix fixe is most popular by far."], "output": "[['menu', 'neutral'], ['prix fixe', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For dinner I had a very balanced spinach fettucine dish served piping hot with salmon, dill, in a creamy pink sauce."], "output": "[['dinner', 'neutral'], ['spinach fettucine dish served piping hot with salmon, dill', 'positive'], ['pink sauce', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We often come with a baby and the staff is so sweet and kind to her, it is a joy to be there."], "output": "[['baby', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Then, we discovered that not ordering guacamole for your table is tantamount to asking the wait staff to roll their eyes at you and then ignore you during your entire meal (I had to eventually go to the front of the restaurant to ask for our check)."], "output": "[['guacamole', 'neutral'], ['wait staff', 'negative'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The calamari salad was huge (but delicious)--it could be a meal unto itself."], "output": "[['calamari salad', 'positive'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The only drawback is that the tiny cafe can only hold so many people with even less tables available, so if you are lucky enough to score a table, stay put with a date and some wine, because no place nearby can serve so much romance with such quality eats."], "output": "[['tables', 'negative'], ['eats', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A hard-drinking, upscale crowd, holding conversations over loud Latin jazz music, packs the small, open dining room and attached bar."], "output": "[['Latin jazz music', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I wasn't impressed by dessert - I ordered truffles w/ bisquits."], "output": "[['dessert', 'negative'], ['w/ bisquits', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I love it at lunch time, less expensive, excellent food, awesome people-watching (Hi, Regis who is right next to our table) and really nice and airy in the summertime when they open the windows."], "output": "[['lunch', 'neutral'], ['food', 'positive'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A hint of wasabi enlivens the shrimp; while the vegetarian, stuffed with seasonal greens, gets overwhelmed by its healthful-tasting herb dipping sauce."], "output": "[['hint of wasabi enlivens the shrimp', 'neutral'], ['vegetarian', 'neutral'], ['herb dipping sauce', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["had the $80 chefs tasting menu - was excellent -and we were stuffed - basically is a bit of all of their special dishes - one at a time - with sushi soup coming last."], "output": "[['chefs', 'positive'], ['special dishes', 'neutral'], ['sushi soup', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When I asked to speak to a manager, I was sent to voicemail, and I still haven't received a callback."], "output": "[['manager', 'negative'], ['callback', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["By dessert, I gave up and sat there hopelessly watching as my rice pudding was snatched away half eaten, only to be replaced immediately with a hefty bill."], "output": "[['dessert', 'neutral'], ['rice pudding', 'neutral'], ['bill', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Don't look for sushi on the menu although there's tons of sake and it's served properly."], "output": "[['sushi', 'neutral'], ['menu', 'neutral'], ['served', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Didn't get a call so I thought all was ok-they didn't have a reservation and wouldn't seat us for over an hour even though no one else was waiting and I saw several empty tables."], "output": "[['reservation', 'neutral'], ['tables', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["On top of that, the portions were hearty enough that we barely had any appetite left for dessert."], "output": "[['portions', 'positive'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When I pointed this out to the waiter he told me that all of the lox is like that."], "output": "[['waiter', 'negative'], ['lox', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["But in my opinion, a great experience doesn't just pertain to food, and an evening of dining is certainly given a bad taste when the service is not up to par."], "output": "[['dining', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There was a ten minute wait with a reservation, but the bar kept us entertained."], "output": "[['wait', 'neutral'], ['reservation', 'neutral'], ['bar', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were about the leave when a nice waitress explained to us that she'd personally seat us when she witnessed the hostess' actions."], "output": "[['waitress', 'positive'], ['hostess', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food wasn't impressive either- I was expecting huge portions, but my lobster ravioli was only 4 medium sized pieces, and I've tasted better at other restaurants."], "output": "[['food', 'negative'], ['portions', 'positive'], ['lobster ravioli', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Even when the chef is not in the house, the food and service are right on target."], "output": "[['chef', 'neutral'], ['food', 'positive'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Be prepared to wait for your table at peak hours, even if you have a reservation."], "output": "[['table', 'negative'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I used to think Lombardi's served the best pizza in the city, but then I happened in on Grimaldi's en route to the Brooklyn Ice Cream Factory one day."], "output": "[['pizza', 'positive'], ['Cream', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We ordered Brushetta, a 6 on a scale of 10, I like cold tomatoes on toasted bread, they had warm tomatoes."], "output": "[['Brushetta', 'neutral'], ['cold tomatoes on toasted bread', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is ok, but not worth the prices."], "output": "[['food', 'positive'], ['prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you've got the money and don't mind being packed in like sardines - then cozy on up to the Sushi Bar (much better than a table) and let Gari work his Omikase magic."], "output": "[['sardines', 'neutral'], ['table', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had the GREATEST MEAL THAT I'VE EVER HAD at Babbo (Aside from my Grandmothers)  The food is not quite traditional Italian but then again not exactly Nouvo-cuisine."], "output": "[['MEAL', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food For the most part, it's solid, sometimes impressive Chinese: One can easily find better pork buns and Peking duck in Chinatown, but then you'd have to settle for dining with regular folks."], "output": "[['Food', 'positive'], ['dining', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Not only is the sushi mostly stellar, you'd have to be a real bonehead to not take advantage of their cooked items."], "output": "[['sushi', 'neutral'], ['items', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["At one point, we tried to get our waitresses attention and she ignored us and than we asked for more biscuits and never got them."], "output": "[['waitresses', 'negative'], ['biscuits', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Yes, the wait is long and ridiculous as times, especially as you watch others gobble down their food."], "output": "[['wait', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The staff is warm and friendly, and the bartender makes an awesome drink with something called pisco."], "output": "[['staff', 'positive'], ['bartender', 'neutral'], ['drink', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Save room for extra sides, even though two come with each main course: The collard greens, gooey mac and cheese and ham-hocked lima beans all stoke the soul like the sound of a pedal-steel guitar."], "output": "[['sides', 'positive'], ['collard greens', 'neutral'], ['ham-hocked lima beans', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It had not been made fresh at the bar, but kept in the freezer till we ordered, they also forgot our soup, kept us waiting for the frozen sushi for close to an hour."], "output": "[['bar', 'neutral'], ['soup', 'negative'], ['waiting', 'negative'], ['frozen sushi', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There are some reviews complaining about the menu but I had the same dish the first three times that I was there - and any specials that I have had have been excellent."], "output": "[['menu', 'neutral'], ['specials', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Everything on the menu is worth trying at least once, from the calamari/zucchini appetizer, to the homemade cavatelli, to the rib eye steak (like butter!)"], "output": "[['menu', 'positive'], ['rib eye steak', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It's too loud and the cheesiest music is played throughout the meal."], "output": "[['cheesiest music', 'negative'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere was embracing and enticing and the costs of the meal, $45 to $55 in value."], "output": "[['atmosphere', 'positive'], ['costs', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When we followed the waiter to get back the card, the Manager explained that their machine did work, but someone else's bill was charged on our card (total charge=$140)."], "output": "[['waiter', 'neutral'], ['Manager', 'neutral'], ['machine', 'positive'], ['bill', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have yet to visit for dinner, but had a lovely brunch there recently - the french toast is to DIE for."], "output": "[['dinner', 'neutral'], ['brunch', 'positive'], ['french toast', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food In addition to its potent, expertly made coffee drinks--beans come from upstate coffee roaster Irving Farm--71 stocks a full array of cakes, tarts, sandwiches and salads."], "output": "[['Food', 'positive'], ['coffee drinks', 'neutral'], ['array of cakes', 'neutral'], ['salads', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The $75 tasting menu features seafood which is both unusual and powerfully fresh, but the chef's appetizers which preceed it like sesame flavored tile fish with raw vegetable salad and japanese spiced flan with seafood were unbalanced and far too delicate on the palate (although the tuna tartare with avocado is a standout)."], "output": "[['menu', 'positive'], [\"chef's appetizers\", 'neutral'], ['sesame flavored tile fish with raw vegetable salad', 'negative'], ['japanese spiced flan with seafood', 'negative'], ['tuna tartare with avocado', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have to say that the food at Bread TriBeCa was a major letdown."], "output": "[['food', 'negative'], ['Bread', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There isn't a huge selection of food, but there's something on the menu for everyone to really enjoy."], "output": "[['food', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The wait staff was all hanging at the bar, lounging around."], "output": "[['wait staff', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the manager was nice profecional and service was average but the food was not italian, a diner is better, try po'"], "output": "[['manager', 'positive'], ['service', 'neutral'], ['food', 'negative'], ['diner', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It took us 20 minutes to get a check, despite many attempts at meaningful eye contact with the wait staff."], "output": "[['check', 'neutral'], ['wait staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Bread bar couldn't get anything right except water refills (good job to the water guy)."], "output": "[['bar', 'negative'], ['refills', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Everyone says that their round slice is no good, but the Sicilian is so good that I have never tried the round."], "output": "[['slice', 'negative'], ['Sicilian', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When we mentioned that we had theatre tickets, the waiter made certain that our dishes were served promptly and courteously."], "output": "[['waiter', 'positive'], ['dishes', 'neutral'], ['served', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When you feel like eating again an hour later (portions are small) at least you won't feel as regretful about ordering take-out."], "output": "[['portions', 'negative'], ['take-out', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The staff were friendly, but the food just wasn't that great."], "output": "[['staff', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For brunch, go for the fluffy raisin challah French toast or Tex-Mex scrambled eggs with fresh tortillas and a side of crisp pork sausage."], "output": "[['brunch', 'neutral'], ['raisin challah French toast', 'positive'], ['Tex-Mex scrambled eggs', 'positive'], ['crisp pork sausage', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The pieces were small but the fish was good quality and there wasn't a lot of rice to mess with."], "output": "[['fish', 'neutral'], ['quality', 'positive'], ['rice', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The server spilled beer on the table when he poured it; he dropped ice cubes for another one of our guests and water everywhere else."], "output": "[['server', 'negative'], ['beer', 'neutral'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["To start with - the maitre'd forgot our reservation and then when it came time to sit us down - he told us we only had an hour."], "output": "[['maitre', 'negative'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This review is based on breakfast/brunch: I called on Saturday for a table the next day (knowing it was unlikely that I'd get one) and the reservations person told me that there were no tables available."], "output": "[['reservations', 'neutral'], ['tables', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The staff forgot my girlfriend's food altogether as she waited for half an hour."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The silvery beige decor reflects the refined air of the store as a whole."], "output": "[['beige decor', 'positive'], ['air', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our plates were taken before we finished eating and our waitress sent the hostess to tell us we had to leave to make room for the next table and that we had to pay before we left."], "output": "[['plates', 'neutral'], ['waitress', 'negative'], ['hostess', 'negative'], ['next table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The restaurant is loud, the tables are wooden and the service is OK."], "output": "[['tables', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Overall, it is a nice place and if you don't mind possible attitude and the not-so-cheap prices, it is a great place to meet for coffee or drinks (they have a nice selection of that too!"], "output": "[['prices', 'negative'], ['coffee', 'positive'], ['drinks', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["had to ask the host for the check because the waitress was sitting at another table taking their order."], "output": "[['host', 'neutral'], ['check', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["NOTE: Plan ahead, make a reservation and arrive early - parking is tight in the area - valet service is available if all else fails!"], "output": "[['reservation', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Everything from the salmon dip at the bar (while waiting for our table) to the dessert was perfect."], "output": "[['salmon dip', 'positive'], ['bar', 'neutral'], ['dessert', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The front desk is disorganized (couldn't find my reservation made a week in advance); service is below-par; food is just so so; the most expected dessert turned out to be disappointed."], "output": "[['front desk', 'negative'], ['reservation', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Unfortunately, as we were finishing up, the manager hovered around us and asked us to go to the bar to finish our drinks because there were other people waiting."], "output": "[['manager', 'negative'], ['bar', 'neutral'], ['drinks', 'neutral'], ['waiting', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food Recalling an era of calorie-defying decadence--hard liquor, red meat, cigars and mammoth portions--gluttony is the operative word here."], "output": "[['Food', 'negative'], ['meat', 'neutral'], ['portions', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Ceviche was a standout, but everything was above average from the fried plantain and refried beans to the homemade guac and yellow rice."], "output": "[['Ceviche', 'positive'], ['beans', 'neutral'], ['homemade guac', 'neutral'], ['yellow rice', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The servers were extremely professional, especially considering the entire room needed to be served at the same time."], "output": "[['servers', 'positive'], ['served', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food, admittedly, was tasty (we came prepared for high prices and small portions) but I could not believe that with entrees, appetizers, and wine that the servers would rush us through each course."], "output": "[['food', 'positive'], ['entrees', 'neutral'], ['appetizers', 'neutral'], ['wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The ambience is simple, yet elegant and be sure to finish your meal with their famous shlog."], "output": "[['ambience', 'positive'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["71 Irving's coffee is not only delicious but also consistently delicious."], "output": "[['Irving', 'neutral'], ['coffee', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The pommes frites are top-notch, and there's an impressive array of Belgian beers to pair with your meal."], "output": "[['pommes frites', 'positive'], ['Belgian beers', 'positive'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter was singing while taking our order- the food arrived 30 minutes later and the food was good, but the mules Frites were cold, the steak had to be returned twice-the spinach looked like it was grass from Union Square park with hunks of garlic in it-totally Unacceptable."], "output": "[['waiter', 'neutral'], ['mules Frites', 'negative'], ['spinach', 'negative'], ['garlic', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Half way through the meal we did not have refills on our waters, even though our waiter passed the table many times and he never stopped to check on us or to ask if we were pleased with the entrees."], "output": "[['waiter', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["but when tables began to clear up, it seemed polite to seat us comfortably in the dining area instead of having us twist our backs to talk, perched on bulky high chairs at the bar with no place to put our handbags (which the waiter happened to drop and expose contents later on)."], "output": "[['tables', 'neutral'], ['chairs', 'neutral'], ['bar', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Most laughable moment of night was when waiter offered me a free drink to make up for th 50 minute appetizer wait."], "output": "[['waiter', 'positive'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["cool new cocktails, amazing apps, we were seated on Chefs Table for dinner ;) All ten of us were extremely comfortable, where the Chef came personally and we had special dishes that were pre-decided by my cousin for his party."], "output": "[['new cocktails', 'positive'], ['Chefs Table', 'neutral'], ['dinner', 'neutral'], ['dishes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After waiting forty minutes for our brunch, learned that the waitress had -- oops!"], "output": "[['brunch', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["i have been waiting for 15 mn ( no food menu , no cocktail menu , no one even say hi to me )."], "output": "[['waiting', 'neutral'], ['food menu', 'negative'], ['cocktail menu', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the tables are in the back and the ambience was less to be desired."], "output": "[['tables', 'neutral'], ['ambience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The cooks in the front are very friendly and helpful."], "output": "[['cooks', 'positive'], ['front', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["waitress brought different food."], "output": "[['waitress', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There was interesting summer dessert, a rubarb-crisp with basil ice cream."], "output": "[['dessert', 'positive'], ['rubarb-crisp with basil ice cream', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There is no menu and the waiter never told us how much lunch was, I thought it couldn't be more than $35."], "output": "[['menu', 'neutral'], ['waiter', 'negative'], ['lunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["At first I was shocked by the price, but the excellent and friendly service from our waiter Jack was great and the duck salad was the best ever."], "output": "[['price', 'negative'], ['service', 'positive'], ['waiter', 'positive'], ['duck salad', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere was a+, until a friend and I were rudely interrrupted and rushed out by the attendant at the door when the check was only returned to us just 5 mins."], "output": "[['attendant', 'negative'], ['check', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Service was inexcusably, excruciatingly slow- it took more than 30 min to get the first round of drinks, by which point our party was ready to walk out."], "output": "[['Service', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We told the manager it was not worth a few appetizers to be treated that way and left."], "output": "[['manager', 'neutral'], ['appetizers', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We got up from the bar and got pushy with the hostess and finally were seated at an excellent table."], "output": "[['bar', 'neutral'], ['hostess', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There are a few chefs who aren't very enthusiastic and not very theatrical, but the end product is always great food."], "output": "[['chefs', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["also you dont mind waiting because theres such a buzz around the bar it makes you feel like you are out for drinks."], "output": "[['waiting', 'positive'], ['bar', 'neutral'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food at Mercer Kitchen is great, flavorful and nicely portioned."], "output": "[['food', 'positive'], ['Kitchen', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Beautiful rooms filled with beautiful people, but expensive for what it is ($68 prix fixe), limited menu, tiny portions, reeeeeeeally slow service, undercooked potatoes with the cod, less than fascinating desserts."], "output": "[['prix fixe', 'neutral'], ['portions', 'negative'], ['service', 'negative'], ['cod', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The dramatic space complements the food and will wow out-of-towners."], "output": "[['dramatic space', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Bartender, should not be taking dinner orders on napkins."], "output": "[['Bartender', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere was so fun that we decided to have another cocktail at the bar and enjoy the scene."], "output": "[['atmosphere', 'positive'], ['cocktail', 'neutral'], ['bar', 'neutral'], ['scene', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Besides their unique wood grilled kalbi or bulgoki (bbq) I'm not too fond of their traditional Korean dishes."], "output": "[['wood grilled kalbi', 'positive'], ['bulgoki (bbq)', 'positive'], ['Korean dishes', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["check it out but i cant narrow down what to order cause Ive always had v good food from pastas to fish!"], "output": "[['food', 'positive'], ['pastas', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If I were to spend a decent amount of cash on dinner, I'd go someplace with EXCELLENT, not just really good food."], "output": "[['dinner', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our dinner was enhanced by a 1999 Pinot Grigio, recmmended by the waitress."], "output": "[['dinner', 'neutral'], ['waitress', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I tried that on a Friday, told the guy otside the door that I did not have a reservation and he said, You may as well just leave now."], "output": "[['guy', 'negative'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In a room decorated with beautiful Ottoman antiques and artwork you can pick exceptional mezzes (appetizers) from a selection presented by a super-friendly staff or order lip-smacking dishes (especially if you like lamb) from the menu."], "output": "[['staff', 'positive'], ['lip-smacking dishes', 'neutral'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Catch a Yankee, Mets game, have a burger and great conversation with the bar keep."], "output": "[['burger', 'neutral'], ['bar keep', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The extensive menu spans the familiar, with dishes like a tataki of superior-quality beef with an arousing ginger sauce; the rare, with freshly made tofu, its ultra-creamy texture wowing more than its flavor."], "output": "[['menu', 'positive'], ['beef', 'positive'], ['texture', 'positive'], ['dishes', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["From the intricately decorated plates to the elaborate sushi dishes, it is everything a Japanese dinner should be."], "output": "[['elaborate sushi dishes', 'neutral'], ['Japanese dinner', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Expect a crowd while waiting, but they seat quickly."], "output": "[['crowd', 'negative'], ['waiting', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Start off with an expertly mixed cocktail or glass of wine at the beautiful bar."], "output": "[['mixed cocktail', 'neutral'], ['bar', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I was lured in by the fact that they have soy options for almost everything that includes dairy on the menu, as well as tofu subs for eggs; It is hard to find mexican tinged food with an optional vegetarian slant."], "output": "[['menu', 'neutral'], ['slant', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After the rude waitress took our order we were sipping our drinks when the manager comes over and says we have to leave as the tables are reserved for dinner patrons."], "output": "[['waitress', 'negative'], ['drinks', 'neutral'], ['manager', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Server's were extremely nice, yet were socializing too much with friends that were having drinks at the bar and it was difficult to get their attention."], "output": "[['Server', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Also, if you order a dinner, plan to have leftovers for the next day because the portions are HUGE, the salad that comes with a meal is large enough to be a meal itself."], "output": "[['dinner', 'neutral'], ['portions', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Fast and Fresh is also a bodega, and they have the usual offerings: cold drinks in the fridge (Corona and other beers available), bagels, sammiches and salads to order."], "output": "[['drinks', 'positive'], ['sammiches', 'neutral'], ['salads', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although the homefried potatoes were not worth the plate space, next time I'll ask to substitute a nice salad."], "output": "[['plate space', 'negative'], ['salad', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["By the end of the meal, we were shaking hands with/hugging our waiter as we stumbled/rolled out the door."], "output": "[['meal', 'neutral'], ['waiter', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I requested the waiter to seat us at a different table, and he was like 'its the same everywhere', and walked off."], "output": "[['waiter', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They had a great wine selection to choose from, the single mixed drinks were a little pricey."], "output": "[['wine selection', 'positive'], ['single mixed drinks', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For example, the flavor in each dish didn't really stand out and the spanish rice seemed more like uncle ben's with peas and corn mixed in."], "output": "[['flavor', 'negative'], ['dish', 'neutral'], ['spanish rice', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Other than the too fruity drinks at the bar which wasn't my cup of tea, everything else was excellent."], "output": "[['bar', 'neutral'], ['tea', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food Scott Ehrlich's cerebral New American food demands both close attention and a certain amount of faith; even when dishes aren't entirely successful, they manage to be compelling."], "output": "[['New American food', 'neutral'], ['dishes', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["interesting back patio - curious what it would be like for lunch."], "output": "[['back patio', 'positive'], ['lunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were a party of six and I had tried almost everything that was on the table, and had I been rich I would have hired the chef to cook only for me!"], "output": "[['table', 'neutral'], ['chef', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the atmosphere is trendy, i think it's better to come here for a drink rather than dinner."], "output": "[['atmosphere', 'positive'], ['drink', 'neutral'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Great place for either appetizers and drinks at the bar, a romantic dinner or late night partying."], "output": "[['drinks', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu can give you price shock but the food, service and drinks are worth every stinking penny."], "output": "[['menu', 'neutral'], ['price', 'neutral'], ['food', 'positive'], ['service', 'positive'], ['drinks', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went there on my 2nd day in New York ever for a quick lunch and ended up staying and chatting with the owners wife and a waiter, Javi for two hours."], "output": "[['lunch', 'positive'], ['owners', 'neutral'], ['waiter', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The main floor space is lovely, but cavernous (which means *VERY* noisy), so our server was especially patient with us since we couldn't hear each other or her half the time."], "output": "[['main floor space', 'positive'], ['server', 'positive'], ['time', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["NEED Reservations in order to get past the host by the secret door and the maitre d host downstairs but No trace of snooby attitude here."], "output": "[['Reservations', 'neutral'], ['maitre', 'positive'], ['host downstairs', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Unlike most whole in the wall Pizza places, you can taste the real Olive Oil in their pizza's."], "output": "[['real Olive Oil', 'positive'], [\"pizza's\", 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Cheeses get short shrift by waitstaff, who all seem hurried."], "output": "[['Cheese', 'neutral'], ['waitstaff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food as always was fantastic, and the pricing was moderate although I was not happy about the 18% gratuity being added for parties over 6, especially after the horrible service we recieved."], "output": "[['food', 'positive'], ['pricing', 'positive'], ['gratuity', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The best tasting pizza by far, a long long wait for service but well worth it."], "output": "[['pizza', 'positive'], ['wait', 'negative'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene With its yellow slat walls, nautical art and well-worn oak bar, this onetime fishermen's lair is now a snug little neighbor to both South Street Seaport and the glass sequoias of nearby Wall Street."], "output": "[['Scene', 'neutral'], ['bar', 'positive'], ['glass', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The orange slices signalling the end of the dinner was brought to our table even though we were still eating the main entrees."], "output": "[['orange slices', 'negative'], ['dinner', 'neutral'], ['entrees', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I came to have dinner with two of my girlfriends on saturday and had an awsome time."], "output": "[['dinner', 'neutral'], ['time', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Aperitif was the Casablanca; it was served carelessly with ice chunks large enough to sink the Titanic."], "output": "[['served', 'negative'], ['ice chunks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The pretty waitstaff is always pleasant, but service is inconsistent at best."], "output": "[['waitstaff', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They were seating people without reservations who were either friends of the employees or were slipping the hostess $20 to get seated without a reservation."], "output": "[['reservations', 'neutral'], ['employees', 'negative'], ['hostess', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Knapp Street Pizza also has a variety of pizzas including: eggplant, ziti, chicken parmigiana and so on."], "output": "[['pizzas', 'positive'], ['eggplant', 'neutral'], ['ziti', 'neutral'], ['chicken parmigiana', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After dinner the manager grabbed my boyfriend, asked him: Where are you from."], "output": "[['dinner', 'neutral'], ['manager', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Each entre came with a side of rice and bread (most places you have order the bread separately), dal (lentils) and fresh vegetable."], "output": "[['dal', 'neutral'], ['vegetable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A simple dish like Fattouch or Tabbouleh are turned into the most delicious salad youll ever have."], "output": "[['dish', 'positive'], ['Fattouch', 'neutral'], ['salad', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were first greeted by a very friendly hostess who asked if we had reservations - even though we didn't they were VERY accommodating - we sat at the bar and spoke to the VERY nice bartender who recommended a GREAT wine and gave us some brucetta to munch on while we waited."], "output": "[['reservations', 'neutral'], ['bartender', 'positive'], ['wine', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Full of characters from the neighborhood, it's a fun place to meet up with friends or have a drink at the bar."], "output": "[['drink', 'neutral'], ['bar', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["You must think that the quality is poor for them to sell it for such a low price."], "output": "[['quality', 'negative'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["50 a better meal on the go than pizza."], "output": "[['meal', 'positive'], ['pizza', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had oysters for my appetizer and the Turbot with a delicate creamy lemon sauce with a hint of dill for dinner."], "output": "[['oysters', 'neutral'], ['appetizer', 'neutral'], ['Turbot', 'neutral'], ['creamy lemon sauce', 'positive'], ['hint of dill', 'neutral'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I checked this place out during the blizzard, and was thrilled to discover the $12 early bird price fixe (until 6:30 PM) -- appetizer, entree, dessert, and soda."], "output": "[['price fixe', 'positive'], ['appetizer', 'neutral'], ['dessert', 'neutral'], ['soda', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food The restaurant boasts an impressive raw bar and samplings from the bait menu a big draw."], "output": "[['Food', 'neutral'], ['bar', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Much has been made of Island's lack of french fries--space and cost are cited on the menu--but an order of thick crispy salt and vinegar chips almost satisfies the craving."], "output": "[['french fries', 'negative'], ['space', 'neutral'], ['menu', 'neutral'], ['salt and vinegar chips', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Well i asked the server to describe a certain wine for me,he seemed like he knew what he was talking about,till i tasted it,it was totally the opposite of what he described."], "output": "[['server', 'negative'], ['wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Growling at us when we asked for water is one thing, but to just lie and make NO effort to satisfy, or apologize at these moderately high prices ($12."], "output": "[['water', 'neutral'], ['prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food is decent but portions so small that after 5 appetizers, 2 sides and three entrees, the three of us left still hungry!"], "output": "[['portions', 'negative'], ['appetizers', 'neutral'], ['sides', 'neutral'], ['entrees', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The scene was sassy and cool, but i would never eat dinner here again."], "output": "[['scene', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["and they have this great deal: 6 oysters on the half shell and your choice of beer, or wine for only $7!"], "output": "[['oysters', 'neutral'], ['choice', 'positive'], ['wine', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter simply comped off our appetizer and then stayed away for the rest of the night--we waited an additional twenty minutes after we were done eating for the check!"], "output": "[['waiter', 'negative'], ['check', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you are looking for service and all the frills $$$ - Il Mulino is the best for both - if you are looking for a fabulous dinner in/out - this restaurant is it!"], "output": "[['service', 'neutral'], ['dinner in/out', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is spicy like it should be not swimming in oil like it is at song down the street."], "output": "[['food', 'positive'], ['oil', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I'm sorry, but the prices at Boi are outrageous for this type of cuisine."], "output": "[['prices', 'negative'], ['cuisine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It was worth the wait , an hour, without a reservation, for an out of this world meal."], "output": "[['wait', 'positive'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is decent, but for what the bill comes to, it's just not worth it."], "output": "[['food', 'positive'], ['bill', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter was apparently angry to have to be serving, because it took him 15 minutes to even bring water, let alone take a drink order (it was early on in the day and the restaurant was not even 50% full, so he was NOT busy)."], "output": "[['waiter', 'negative'], ['serving', 'neutral'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Last visit, ignored by our waiter, we finally got beers and ordered food."], "output": "[['waiter', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The entire restaurant staff was disappointing to begin with (any waiters over 17 with some knowledge of the menu or wine?"], "output": "[['staff', 'negative'], ['waiters', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Unless you like getting bumped by waiters and people walking by, do not sit at a middle table."], "output": "[['waiters', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Justin our waiter, explained to us that the menu changes daily, more of a reason to return."], "output": "[['waiter', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere and clientele often evoke the feeling of being at a friend's dinner party, where people linger over wine, and chat over small plates of food."], "output": "[['clientele', 'positive'], ['dinner', 'neutral'], ['wine', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["And who else has this great wine list to go with pizza?"], "output": "[['wine list', 'positive'], ['pizza', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After being given a bad table at Becco and leaving there, we walked around and decided on Da Rosina because the price was right and the menu looked good."], "output": "[['table', 'negative'], ['price', 'positive'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Obviously bz place, greeting was less than welcoming, service was adequate from less than friendly waiters, steak for 2 was anything but spectacular served with sauce that's better suited for seafood than meat."], "output": "[['service', 'positive'], ['waiters', 'negative'], ['meat', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Dinner was very rushed - the waiter was bringing out the main course even before we had finished the appetizer."], "output": "[['Dinner', 'negative'], ['waiter', 'negative'], ['appetizer', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is average, however the service is way below average (our waiter was a stuttering fool when it came to the specials and left our drinks empty for the majority of the night) The atmostphere is cheesy as well as the crowd."], "output": "[['food', 'neutral'], ['service', 'negative'], ['waiter', 'negative'], ['drinks', 'neutral'], ['atmostphere', 'negative'], ['crowd', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The seating arrangment isn't the most practical because people get in the way of each other a lot, but the food makes it worth it."], "output": "[['seating arrangment', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Perfectly cooked, el dente pasta, AMZING baked clams, cheap but great wine, friendly service, comfy and non-pretentious setting all for unseen prices for this kind of food."], "output": "[['pasta', 'positive'], ['wine', 'positive'], ['service', 'positive'], ['setting', 'positive'], ['prices', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The small single room--wood panelling, large mirrors, white tablecloths, dim lighting--has few frills."], "output": "[['single room', 'negative'], ['mirrors', 'positive'], ['tablecloths', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Affordable starters comprise most of the menu: Cheese plates with sweet-sour chutneys, spicy lamb-stuffed fried olives and plump mussels baked under saffron-herb breadcrumbs are addictive, but signature tigelle panini fixings shouldn't be missed."], "output": "[['menu', 'neutral'], ['Cheese plates with sweet-sour chutneys', 'neutral'], ['lamb-stuffed fried olives', 'positive'], ['tigelle panini', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had the item that they forgot to put on the menu; some very tasty fish over jasmine rice with shrimp."], "output": "[['menu', 'neutral'], ['fish', 'positive'], ['rice with shrimp', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiters seemed annoyed we all ordered the restaurant week menu and were going to cut into their tips."], "output": "[['waiters', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Before leaving the server gave us takeout menus."], "output": "[['server', 'positive'], ['menus', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Two small, unimpressive lobster tails set atop a brew of tomato based stewed root vegetables."], "output": "[['lobster tails', 'negative'], ['stewed root vegetables', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For an entree I should have been more adventurous, but every menu item that aroused my interest had some form of pork in it (ham, bacon, prosciutto, you name it), most of the time superfluously, I went for the Portabello sandwich."], "output": "[['entree', 'positive'], ['prosciutto', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The kicker was when there were three items on our check that were priced higher than stated on the menu and by the server."], "output": "[['priced', 'negative'], ['menu', 'neutral'], ['server', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The servers didn't know what tables the meals were going to, it was a complete comedy show."], "output": "[['servers', 'negative'], ['tables', 'neutral'], ['meals', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Though the service is speedy be prepared to wait at least 20 minutes for the soup dumplings."], "output": "[['service', 'positive'], ['soup dumplings', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Obviously we did not get right service and nobody said soory for that and other restaurant guests who came after us got quicker dish than us."], "output": "[['service', 'negative'], ['dish', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was good but our waiters were pushy,rude and dumb."], "output": "[['food', 'positive'], ['waiters', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["At any rate, the waiter totally forgot about us and we had to hail him down a couple of times just to get the specials and to order."], "output": "[['waiter', 'negative'], ['specials', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We went again and sat at the bar this time, I had 5 pints of guinness and not one buy-back, I ordered a basket of onion rings and there were about 5 in the basket, the rest was filled with crumbs, the chili was not even edible."], "output": "[['bar', 'neutral'], ['onion rings', 'neutral'], ['chili', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It has the most authentic Mexican found I have found in the Metro area and the margaritas are outstanding."], "output": "[['Mexican', 'positive'], ['area', 'neutral'], ['margaritas', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["However, everything we ate was salted to an extreme, and the steak, so regrettably, was saturated with butter."], "output": "[['steak', 'negative'], ['butter', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food, congeniality, and service have all deteriorated overf the past few years and so the wait is not worth it."], "output": "[['food', 'positive'], ['wait', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Suprising was the cheese selections that were sort of dessert as well."], "output": "[['cheese selections', 'positive'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My doubts were cleared immediately, the host was friendly and yes they suggest the pitcher of sangria before you look at the menu but you should take it anyway!"], "output": "[['host', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When you crave comfort food, make a reservation and head to Piccolo Angolo, they never dissappoint."], "output": "[['food', 'positive'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Waiter took our drink order and then we didn't see him for 15 minutes."], "output": "[['Waiter', 'negative'], ['drink order', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For dessert the waiter reccomended his favorite which was a Torreja."], "output": "[['dessert', 'neutral'], ['waiter', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Caravan can be a little slow sometimes, but more than makes up for it in the quality of the food and the care of wait staff."], "output": "[['food', 'positive'], ['care', 'neutral'], ['wait staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Short of being invited to a Filipino home for dinner, Elvie's is the closest you'll get to tasting Filipino delights."], "output": "[['dinner', 'neutral'], ['delights', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although the place had an actual makeover not long ago, the food or chef needs to be changed."], "output": "[['place', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It's so out there that it works--black-clad raver waiters and all--and even the most normal of groups love getting together for dinner and popular brunching on the palm-lined backyard patio spread."], "output": "[['waiters', 'positive'], ['dinner', 'neutral'], ['backyard patio spread', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Mind you, we had not finished drinking our Sangria (which absolutely sucked) nor eating our tapas (which took forever to arrive)."], "output": "[['Sangria', 'negative'], ['tapas', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The kitchen is open and surrounded by bar seating (the only kind of seating), and they have a nice set-up where the waitress stays behind the bar and the chefs deliver your food after you have watched them prepare it."], "output": "[['kitchen', 'positive'], ['bar seating', 'neutral'], ['waitress', 'positive'], ['chefs', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The limited number of toppings prevented the sogginess described by other reviewers and allowed the intense flavors from the fresh ingredients; sauce, mozarella, basil and black olives to really shine through, without being watered down from too many extra toppings."], "output": "[['ingredients', 'positive'], ['mozarella', 'neutral'], ['black olives', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The lobster bisque was good, but the price of adding lobster meat was astronomical."], "output": "[['lobster bisque', 'positive'], ['price of adding lobster meat', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["One night we landed at the bar for a late night dinner, and the hanger steak and frites w/ marjoram aioli was the BEST."], "output": "[['bar', 'neutral'], ['hanger steak', 'positive'], ['frites w/ marjoram', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Tip: go for lunch early, 12:00 say, when the place and street is quiet and enjoy the romantic and charming setting and delicious food."], "output": "[['lunch', 'neutral'], ['setting', 'positive'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In Short Custard Beach is located in the lower-level dining concourse of Grand Central Terminal, which features seating, many dining choices and a crowd of tourists and commuters."], "output": "[['dining concourse', 'positive'], ['seating', 'neutral'], ['dining choices', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu has been changed to a mostly unhealthy one, adding bacon even to the fish dishes (sometimes with no notice), so if youre looking for vegetarian or even just healthy seafood dishes, you wont find much."], "output": "[['menu', 'negative'], ['bacon', 'neutral'], ['fish dishes', 'neutral'], ['seafood dishes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I for one do not plan to go back, there are many other places in Manhattan that have just as good food if not better, at the same prices with much better service."], "output": "[['food', 'positive'], ['prices', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Not always consistent with cooking the steak (we wanted really rare and it was a bit more well done than that) but still fantastic with a great cut and dependable sides."], "output": "[['steak', 'negative'], ['sides', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Every time I go I order the eggs benedict which comes with home fries and an alcoholic beverage."], "output": "[['eggs benedict', 'positive'], ['beverage', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although the service was top notch, all of the food was disappointing: burnt octopus, bland ravioli, odd tasting mint love letters."], "output": "[['service', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The only downside was our waitress -- she forgot to order one of our side dishes, was not attentive, and then gave us our check before we finished our bottle of wine."], "output": "[['waitress', 'negative'], ['side dishes', 'neutral'], ['wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We didn't have reservations, and showing up at 8:45 we were told it would be about an hour wait."], "output": "[['reservations', 'neutral'], ['wait', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food ranges from okay to delicious and the service varies from great to poor."], "output": "[['food', 'positive'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For breakfast there are a wide variety of whole grain pancakes; pumpkin is my favorite, blueberry second!"], "output": "[['breakfast', 'neutral'], ['grain pancakes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The first time we went there had been a party of 10 that was just seated and the rest of the tables were all full, so we decided to take the drinks to go."], "output": "[['tables', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["But then there's the sluggish and absentminded service: twice someone tried to serve us something for another table and it took a long time to get our check."], "output": "[['service', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Karl the Bar Manager makes yummy special drinks for each season be sure to check out what's on his drink menu when you stop in."], "output": "[['Bar Manager', 'neutral'], ['special drinks', 'positive'], ['drink menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For the main course, he ordered the Hong Kong XO shrimp, nothing more than shrimp with brown sauce and I ordered the yellowfin tuna, which was tasteless."], "output": "[['main course', 'neutral'], ['shrimp with brown sauce', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Cozy atmosphere, good food and service, good place to meet friends for dinner and a drink."], "output": "[['atmosphere', 'positive'], ['food', 'positive'], ['service', 'positive'], ['dinner', 'neutral'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For the price and quality of the food we got, I would not dine here again."], "output": "[['price', 'negative'], ['quality', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The pro's: Good ambience,service The Con's: For the 4 to 5 star price (200 dollars for 2 people which included 2 drinks each, an appetizer, main course, and a hsared dessert), the food and presentation was just average."], "output": "[['ambience', 'positive'], ['service', 'positive'], ['price', 'neutral'], ['drinks', 'neutral'], ['hsared dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the staff there was really freindly the owner even sat down at one point to chat with us, it was hard to chose from the menu it all sounded good, so my wife and i shared plates to try a little of each dish , we ordered."], "output": "[['owner', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We waited in the bar area and had an excellent time waiting for dinner with the bartender and staff."], "output": "[['bar area', 'neutral'], ['dinner', 'neutral'], ['staff', 'positive'], ['time', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Each appetizer was a success: lobster bisque, fried clams, scallops."], "output": "[['appetizer', 'positive'], ['lobster bisque', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was good but for the prices, it was definitely not worth it."], "output": "[['food', 'positive'], ['prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We ordered the recommended dessert ahead of time as they suggested but when it came time for it, the waiter had forgotten it."], "output": "[['dessert', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The steak, duck and soft shell crab are musts for dinner and almost every side dish was great."], "output": "[['steak', 'positive'], ['duck', 'positive'], ['soft shell crab', 'positive'], ['dinner', 'neutral'], ['dish', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It has a large salad bar, many side dishes, soups, fruits, bread, crab legs and sushi."], "output": "[['salad bar', 'positive'], ['side dishes', 'positive'], ['soups', 'neutral'], ['fruits', 'neutral'], ['bread', 'neutral'], ['sushi', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food Pizzas are Neapolitan-style--thin, made with San Marzano tomatoes in a 700-degree wood-burning oven, and loaded with Mediterranean goodies."], "output": "[['Food Pizzas', 'positive'], ['Mediterranean goodies', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Really great thin crust pizza - hot and fresh and fast, though you'll probably have to wait for a table."], "output": "[['crust pizza', 'positive'], ['table', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["At the end of the meal, I politely asked the waitress whether she would comp something, and she said yes."], "output": "[['meal', 'neutral'], ['waitress', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It was Au Bar meets 'Absolutely Fabulous' meets a Versace Outlet Sale."], "output": "[['Bar', 'neutral'], ['Sale', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When we ordered our Margaritas, the waiter said $10, so we gave him a 20 and waited, and when he didn't give us our change, we asked and he said - Happy Hour's over, they're $10 each."], "output": "[['Margaritas', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It is now nothing but an overpriced establishment that is shamelessly riding on the coat tails of its past."], "output": "[['establishment', 'negative'], ['coat tails', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["But the food here is excellant and there are just too many appetizers (in the traditional custom of Korean restaurants) to sample."], "output": "[['food', 'positive'], ['appetizers', 'positive'], ['custom', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["one of us still had wine, so the others tried to order dessert drinks, but the owner told us no because there were people waiting and the waiter said if he served us more he would be fired."], "output": "[['wine', 'neutral'], ['dessert drinks', 'neutral'], ['owner', 'negative'], ['waiting', 'neutral'], ['waiter', 'negative'], ['served', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Went for restaurant week and surprisingly on the menu were entree options of Mahi, Mahi, Kobe Beef ribs, Salmon and some other things in very reasonable portions."], "output": "[['menu', 'neutral'], ['entree options of Mahi', 'neutral'], ['Kobe Beef ribs', 'neutral'], ['portions', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have tried everything available on the AYCE menu, it has all been quite good (although I am not one to be especially particular with food, sushi in particular."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["as of late though(maybe change of ownership)the food quality dropped with the menu change and the service got worse."], "output": "[['food quality', 'negative'], ['menu', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Spring roll did not taste very fresh, soup ok but only had 2 shrimps."], "output": "[['Spring roll', 'negative'], ['soup', 'positive'], ['shrimps', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Overall, reasonable food for price for Pre-fixe dinner (got salad, entree and dessert for 20 dollars a person)."], "output": "[['food', 'positive'], ['price', 'positive'], ['Pre-fixe dinner', 'neutral'], ['salad', 'neutral'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The brief list of desserts includes a rich chocolate marquise and a lemony banana-cream pie."], "output": "[['list', 'positive'], ['desserts', 'neutral'], ['pie', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I was accompanied by foodies, yet the waiter treated the few questions people had about the menu as if he was dealing with diners who had never eaten at a decent restaurant."], "output": "[['waiter', 'negative'], ['menu', 'neutral'], ['diners', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We sat way before 2 other tables ahead of us that rec'd their appetizers before us; the waiter neglected to apologize."], "output": "[['appetizers', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["fish was fresh enough, but the quality was only so-so (the salmon was especially sinewy)."], "output": "[['fish', 'positive'], ['quality', 'negative'], ['salmon', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Thankfully, a succinct menu leaves little to ponder--and, despite the high churn, burgers always arrive as specified."], "output": "[['menu', 'neutral'], ['burgers', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The place is small, or at lease it felt that way b/c tables were right on top of each other."], "output": "[['place', 'negative'], ['tables', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food Mi Nidito's menu offers a considerable array of Mexican standards, with a separate page for seafood, such as King crab enchiladas, and another for vegetarian dishes such as almond-sauteed vegetables."], "output": "[['menu', 'neutral'], ['array', 'positive'], ['seafood', 'neutral'], ['vegetables', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waitress had a French accent and her caring and knowledgeable attitude she discplayed with each table led us to beleive she was the owner."], "output": "[['waitress', 'positive'], ['owner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service was average - the waiter did not check in on our meals and did not even refill the water, but was a bit pushy on desert (we both ordered schnapps)."], "output": "[['service', 'negative'], ['waiter', 'negative'], ['water', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While certain staples are excellent (the burger, some of the pastas), the food is not really the point."], "output": "[['staples', 'positive'], ['burger', 'positive'], ['pastas', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were a large party, over 6 people, and after our initial drinks, which included a couple bottles of wine, and order were taken we did not see a waiter or a busboy again for over an hour!!"], "output": "[['initial drinks', 'neutral'], ['waiter', 'negative'], ['busboy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter was courteous and knew the menu well, though he was a little pushy with the bottles of wine."], "output": "[['waiter', 'positive'], ['menu', 'positive'], ['bottles of wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After 45 mins of waiting in an sans air conditioned bar, we grew tired of paying for over-priced drinks."], "output": "[['bar', 'neutral'], ['drinks', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The best dish is not listed on their menu - it is a special - the flat pasta with truffle mushroom sauce."], "output": "[['dish', 'positive'], ['menu', 'neutral'], ['flat pasta with truffle mushroom sauce', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Never heard anything about a minimum required food order of $30 or had any bad experiences with the staff."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Long wait for our meal (approx 30 minutes), unusual slow service, waitresses (especially the preety one with black hair) louder thn clients, do not care much for customers."], "output": "[['meal', 'neutral'], ['service', 'negative'], ['waitresses', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The only cuisines that will provide comparable quality in the vicinity are Greek (if you know where to look) and Pizza."], "output": "[['vicinity', 'neutral'], ['Pizza', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I defy anyone to tell me where else you can cut the steak with your fork, it practically melts in your mouth- and the sides are amazing."], "output": "[['steak', 'neutral'], ['fork', 'neutral'], ['sides', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["my personal favorite is the meat pie (which uses meat sauce instead of regular marinara sauce)."], "output": "[['meat pie', 'positive'], ['meat sauce', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The only failing was the persian tea, that I'm used to being sweetened with honey."], "output": "[['persian tea', 'negative'], ['honey', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I don't claim that the place as the most authentic, but when you're talking about Southeast Asian street food, which really represents a melting pot of cultures and have slight variation in style for many similarly-named dishes depending where yuo're specifically from, who's to claim what's authentic?"], "output": "[['place', 'positive'], ['food', 'neutral'], ['pot', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My friends and I went to dinner last weekend and had a great time."], "output": "[['dinner', 'neutral'], ['time', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Avoid this restaurant on a busy night at all costs -- they have yet to learn how to make the appropriate number of reservations; the front of the house and the managers are amateurs."], "output": "[['reservations', 'neutral'], ['managers', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When spending upwards of $200 for dinner for two, I expect better service."], "output": "[['dinner', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["MeetLESS gives you a dance club w/o the dance floor a restaurant w/ horrendous service and limited menu selections (the ONLY steak is a top sirloin?!!!)"], "output": "[['club', 'neutral'], ['service', 'positive'], ['menu', 'neutral'], ['steak', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Appetizers, such as sweet grilled scallops with butter, and mouthwatering grilled yellowtail collar, are mostly excellent, though some, like mushrooms stuffed with bland poached fish, fall flat."], "output": "[['mushrooms', 'neutral'], ['poached fish', 'negative'], ['flat', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["You can't go wrong with this spicy sausage, better than the chicken or beef which would be much better if it were seared rather than limply fried on the skillet."], "output": "[['chicken', 'positive'], ['fried', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food The Portuguese knack for exploration couldn't be more apparent on the expansive menu, which moves beyond classics like bacalhau to encompass a world of former colonies along with the motherland."], "output": "[['menu', 'positive'], ['motherland', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I would recommend the Risotto with pear and spinach, the lasagna, and the salads."], "output": "[['Risotto', 'positive'], ['spinach', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Delicious appetizers and entrees, our server recommended a wonderful bottle of wine, and we couldn't resist dessert."], "output": "[['appetizers', 'positive'], ['entrees', 'positive'], ['server', 'neutral'], ['bottle of wine', 'positive'], ['dessert', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My only complaint is that the place is over crowded on weekends, but that's the price you pay for having such great food."], "output": "[['price', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The entree menu is not diverse, but the items on it are all very good."], "output": "[['entree menu', 'negative'], ['items', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["So I go into the bar, and I ask the (extremely hot) waitress, what's the soup of the day?"], "output": "[['bar', 'neutral'], ['waitress', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Each week, Zutto's sushi chef never ceases to amaze me with new concoctions."], "output": "[['sushi chef', 'negative'], ['concoctions', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For dessert, there's sublime cheesecake."], "output": "[['dessert', 'neutral'], ['cheesecake', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The place was busy, but the comfortable banquets and friendly service made me not mind waiting a little extra while for my food to come out."], "output": "[['place', 'positive'], ['banquets', 'positive'], ['service', 'positive'], ['waiting', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It might be a good place to have a drink, but not for food."], "output": "[['drink', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We went there on New Year's Day around 7 pm without a reservation and were able to get a table right away thanks to the very accomodating hostess."], "output": "[['reservation', 'neutral'], ['hostess', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Kid faves include grilled cheese and, quite possibly, the biggest peanut butter and jelly sandwich in New York City."], "output": "[['grilled cheese', 'neutral'], ['peanut butter and jelly sandwich', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Since then, he cannot get enough of their salmon roll, and spicy tuna roll."], "output": "[['salmon roll', 'neutral'], ['tuna roll', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the waitress was probably new, because she had no idea what wine they had, or if they had a certain type by the glass or bottle, and kept going back to the bar to find out."], "output": "[['waitress', 'negative'], ['wine', 'neutral'], ['glass', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I would love the owner to consider hosting a 'tango bar' once - twice a week."], "output": "[['owner', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For the price I paid for a cup of Bustelo coffee w/ milk I could buy 2 vacumed packs for 3 bucks."], "output": "[['price', 'negative'], ['cup', 'neutral'], ['Bustelo coffee', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Everything from the little tastes prepared by the kitchen to the main course to dessert was outstanding and the beauty of the restaurant makes it that much nicer."], "output": "[['main course', 'neutral'], ['dessert', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waitress was so helpful with the wine list."], "output": "[['waitress', 'positive'], ['wine list', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu, fortunately, matches the other locations, covering the basics of Ethiopian cooking, and includes sambosas, kifto (chopped beef often served raw), tibs (lamb sauteed with rosemary), and, of course, injera, the spongy bread that doubles as a utensil."], "output": "[['menu', 'neutral'], ['sambosas', 'neutral'], ['bread', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Staff wouldn't take no for an answer on pitchers of sangria."], "output": "[['Staff', 'negative'], ['sangria', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They brought fresh naan to the table as well as a kind of crepe filled with potatoes that was cooked on a griddle set up by the window."], "output": "[['naan', 'positive'], ['crepe filled with potatoes', 'neutral'], ['window', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I honestly do not understand how anyone can not love this place, unless they don't like real pizza."], "output": "[['place', 'positive'], ['pizza', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Make a reservation, and if possible grab a seat outside, even on cool days the heat torches work great."], "output": "[['reservation', 'neutral'], ['seat', 'neutral'], ['heat', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The space is small and reservations are definitly needed."], "output": "[['space', 'negative'], ['reservations', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It is a small restaurant so without reservations, there can be a long wait."], "output": "[['reservations', 'neutral'], ['wait', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Even if you hate beets, try the beet ravioli- you will not be disappointed!"], "output": "[['beets', 'negative'], ['beet ravioli', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For roughly $10-12 one can get themselves a healthy burger decked with toppings, fries, and a drink, a meal that makes the neighboring fast food places look inferior."], "output": "[['burger', 'positive'], ['drink', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Po has the best food in NY, if you don't mind a wait."], "output": "[['food', 'positive'], ['wait', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I'm not a drinker, and I find that the waiters usually blow us off and ignore us once we don't spend a lot of money ordering wine, and the water takes a while to get re-filled, but the food is good enough that we return."], "output": "[['wine', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["No condiments on table or offered, service average, smokey upon arrival as the kitchen is fully exposed and the space very tight."], "output": "[['condiments', 'neutral'], ['kitchen', 'negative'], ['space', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After finishing your meal, you can drop by their natural food market next door for organic all natural grocery."], "output": "[['meal', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiters didn't clean it up until they brought our dessert."], "output": "[['waiters', 'negative'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In Short This restaurant, an offshoot of the celebrity-besieged East Hampton eatery of the same name, is enlivened by a copper-topped bar, an on-display wood-burning oven and a royal blue oceanic mural running along its walls."], "output": "[['bar', 'neutral'], ['blue oceanic', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Went with three people last saturday night - half way through our entrees we tried to order a second bottle of wine - both the hostess and waitress told us no, cause, ehh, the place is very crowded this night guys."], "output": "[['entrees', 'neutral'], ['bottle of wine', 'neutral'], ['hostess', 'negative'], ['waitress', 'negative'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you eat here, just keep in mind that the specials are much higher than the regular menu when ordering."], "output": "[['specials', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The regular entrees and desserts here are excellent, with truly unusual sides and garnishes that make for brilliant flavor combinations with the central meat or fish."], "output": "[['entrees', 'positive'], ['desserts', 'positive'], ['sides', 'positive'], ['flavor', 'positive'], ['central meat', 'neutral'], ['fish', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["True, the service is hardly on par with the finer restaurants in NYC, but I go for the energy and the tasty tapas-like seafood treats that are perfect with beer or sake."], "output": "[['service', 'negative'], ['tapas-like seafood treats', 'positive'], ['beer', 'positive'], ['sake', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There is no service at this bar, which means no drinks or food -- ultimately leading to a very frustrating night out, and you end up kicking yourself for not leaving an hour earlier."], "output": "[['service', 'negative'], ['bar', 'neutral'], ['drinks', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Hostess finally brought it, saying if we wanted dessert, we could move to another table."], "output": "[['Hostess', 'negative'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The bill was surprisingly inexpensive considering we each had appetizers, an entree, dessert and drinks (alcoholic and non) we also had 3 rounds of shots for the entire table."], "output": "[['appetizers', 'neutral'], ['dessert', 'neutral'], ['alcoholic', 'neutral'], ['bill', 'positive'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["You get plenty of food for the price, enough leftovers for lunch and they actually serve garlic chicken with lots of chicken and chinese vegetables."], "output": "[['food', 'positive'], ['price', 'neutral'], ['lunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We waited forever for our orders, our drinks came out AFTER our food, we never got refills on water, we had to ask like three times for extra dressing, and our waiter was rude."], "output": "[['drinks', 'neutral'], ['water', 'neutral'], ['dressing', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I am not sure if this was just an off night or what, our waiter forgot wine, brought us desert menus before dinner came, then brought us the wrong dinner."], "output": "[['waiter', 'negative'], ['wine', 'neutral'], ['desert menus', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["From the opera playing in the background, to Emilio, the owner wishing everyone a good meal, this should be the highest rated Italian restaurant in the city."], "output": "[['background', 'neutral'], ['owner', 'positive'], ['meal', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["who seemed honestly offended that we asked why our table was 45 minutes late; a cold cafeteria room that was clearly designed to intimidate; and haute chinese food that was over-salted to make up for the lack of flavor."], "output": "[['table', 'neutral'], ['cafeteria room', 'negative'], ['chinese food', 'positive'], ['flavor', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After our initial order, the waitress wasn't very attentive (we had to wait 15 minutes at a time to get her attention to refill drinks, order desert, etc)."], "output": "[['waitress', 'negative'], ['drinks', 'neutral'], ['desert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Main courses include a list of housemade pastas, a daily risotto special (if you're lucky, you'll arrive on wild mushroom day), plus a handful of fish and meat dishes."], "output": "[['daily risotto special', 'neutral'], ['wild mushroom day', 'positive'], ['meat dishes', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["our waitress (who was ok) disappeared in the middle of our dinner, leaving us to an obnoxious amateur (must answer the phones or something) who could not answer our questions and treated us extremely rudely."], "output": "[['waitress', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["First of all, I think our service person was miffed that we couldn't order much for apps or drinks since we had already started at the bar."], "output": "[['service', 'negative'], ['drinks', 'neutral'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I mean Pho Viet Huong is at a good location, but face it, the broth is cloudy and oily -they're supposed to constantly dump the top layer off of the Pho broth, service is ran with attitude who cares about you, I have plenty of other customers to make money off of."], "output": "[['Pho broth', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu sticks to standard Italian dishes--linguine with clam sauce, chicken parmigiana, and fettuccine Alfredo--but the reasonable prices add to the charm."], "output": "[['menu', 'neutral'], ['chicken parmigiana', 'neutral'], ['fettuccine Alfredo', 'neutral'], ['prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Before I went to Nobu for a Restaurant Week lunch, I was told not to order the sushi -- not because it wasn't excellent, but because 1) it's harder for a relatively untrained palate to appreciate the difference between good and excellen sushi than to savor a really well-prepared seafood entree and 2) the servings of sushi are small."], "output": "[['lunch', 'neutral'], ['seafood entree', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Self-important people, please stay at home and cook and dump as much parmesan on as you like."], "output": "[['people', 'negative'], ['parmesan', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Or belly up to the beef belly soup, made with wide chow fun noodles and a thick, beefy broth."], "output": "[['beef belly soup', 'neutral'], ['chow fun noodles', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The simple menu focuses on standard pies and chicken-centric specialty pizzas--the Hawaiian BBQ, BBQ chicken, and bacon and chicken club--each topped with fresh ingredients like baby portobello mushrooms and roma tomatoes."], "output": "[['menu', 'neutral'], ['specialty pizzas', 'neutral'], ['Hawaiian BBQ, BBQ chicken', 'neutral'], ['bacon and chicken club', 'neutral'], ['ingredients like baby portobello mushrooms', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The garden is beautiful and romantic place to share dinner with that special someone or just with friends."], "output": "[['garden', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food Palm dry ages its steaks--as opposed to vacuum packing--and the result is evident."], "output": "[['Food', 'negative'], ['steaks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Got a seat quick, and had some weird fill-out order form for a hard to understand menu."], "output": "[['seat', 'positive'], ['menu', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The interior is understated making it special enough to take a date but easy enough to stop in anytime for dinner or snack."], "output": "[['interior', 'positive'], ['dinner', 'neutral'], ['snack', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We get treated very well and before we sit down to our steaks and fried green tomatoes that we love there - we have a few beers at the bar."], "output": "[['steaks', 'positive'], ['fried green tomatoes', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They had a prix fixe menu with the most amazing cooked quail appetizer, then lobster bisque, followed by a divine choice of entree, and then the chocolate mousse dessert."], "output": "[['prix fixe menu', 'neutral'], ['cooked quail appetizer', 'positive'], ['lobster bisque', 'positive'], ['entree', 'positive'], ['chocolate mousse dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We saw problems with our waitress immediately when she frowned when we opted for tap water instead of bottled."], "output": "[['waitress', 'negative'], ['tap water', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene Honeycomb-colored walls, random wall art, a peek into the kitchen from paper-topped tables--all combine for a casual, thrown-together ambience."], "output": "[['Scene', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["02 one can have salad, great steak, and cheesecake or chocolate mousse, plus friendly service."], "output": "[['salad', 'neutral'], ['steak', 'positive'], ['cheesecake or chocolate mousse', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When my family and I visited, we were hearded in and out of the restaurant like cattle; not once did our waiter ask how are meal was, and the waitress mixed up our steaks."], "output": "[['meal', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Any of their desserts are the perfect finish to a picnic lunch in the park or a Romantic Dinner at home."], "output": "[['desserts', 'positive'], ['lunch', 'neutral'], ['Dinner', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service was terrible- our waiter was unable to make any recommendations, mumbled the special and failed to check back during the course of our meal."], "output": "[['service', 'negative'], ['waiter', 'negative'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I, on the other hand, thought my fish cake, chicken and veggie hot soba entree was average, and there were less noodles in the soup than I expected."], "output": "[['fish cake', 'neutral'], ['veggie hot soba entree', 'negative'], ['soup', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene Cooing couples find some formality and open air up in the front room, while the subterranean back area offers hunkered-down seating for loungier dining."], "output": "[['Scene', 'neutral'], ['air', 'positive'], ['area', 'neutral'], ['dining', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["SO I ASKED, TO SPEAK TO THE MANAGER, AND ONE OF THE OWNER WHO MANAGES THE PLACE CAME TO MY TABLE, TOLD ME THAT THE CEVICHE WAS FRESH."], "output": "[['MANAGER', 'neutral'], ['OWNER', 'neutral'], ['CEVICHE', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When we got there, the wait was just as everyone here has described, Domenico's process was just as described, but the pizza?"], "output": "[['wait', 'neutral'], ['pizza', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The place got really crowded around 8ish when I went right before Christmas so reservations might be necessary."], "output": "[['place', 'negative'], ['reservations', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food This Cajun-Italian menu is lengthier than its Manhattan counterparts--here, adventuresome diners can still design their own pies, but they can also feast on oversized plates of peel-and-eat old bay shrimp and cajun spaghetti with meatballs enlivened with andouille sausage."], "output": "[['Cajun-Italian menu', 'positive'], ['diners', 'positive'], ['plates', 'positive'], ['cajun spaghetti with meatballs enlivened', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Great tasting meat, intimate if slightly noisy ambience and the service is slightly less attentive than it could be but is done with charm."], "output": "[['meat', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For an entree, I tried the Ravioli, cooked to perfection and stuffed with eggplant, ricotta, and chicken and served in an suculent sage butter sauce."], "output": "[['entree', 'neutral'], ['Ravioli', 'positive'], ['ricotta', 'neutral'], ['chicken', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We are 30 plus year olds, very gainfully employed, were not being loud or obnoxious, there were other diners around us as well as a bunch of people at the bar and nobody seemed to have a problem with us except for this manager."], "output": "[['bar', 'neutral'], ['manager', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["You'll have to wait for a long time if you're not in with the management or Fernando, but it's worth it, have some campari and cinzano at the bar!"], "output": "[['management', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The sauce is filled with spices, including fresh garlic and basil."], "output": "[['sauce', 'neutral'], ['spices', 'positive'], ['garlic and basil', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter got aggravated when we explained how we wanted our entrees prepared."], "output": "[['waiter', 'negative'], ['entrees', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["What I thought was a rip off was, when we were ordering, the waiter told us there was a minimum of food we can purchase."], "output": "[['waiter', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Service only so-so -- I saw a lot of wait staff standing around, and at the busiest moment, I watched waiter stroll through the dining room with two plates as if he had all the time in the world."], "output": "[['wait staff', 'negative'], ['dining room', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My Moon spent all their money on an architect/interior designer and forgot about the chef."], "output": "[['money', 'neutral'], ['chef', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Now, I expressed my surprise and then the bartender and manager chimed in with a simpleton's remark sir, with restaurants at this time, reservations start coming in."], "output": "[['manager', 'negative'], ['reservations', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Their mixed drinks weren't so good, but they have nice selection of wines."], "output": "[['mixed drinks', 'negative'], ['selection of wines', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["sam adams on tap, french fries served out of a brown paper bag and a burger cooked perfectly."], "output": "[['tap', 'neutral'], ['french fries served', 'neutral'], ['burger', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was good but took long and the drinks she recommended to us were too strong."], "output": "[['food', 'positive'], ['drinks', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["be prepared for a long wait at dinner."], "output": "[['wait', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My friend and I went out for a cigarette, and when we returned, our table had been given to another party- even though our drinks and unpaid bill were still on the table."], "output": "[['drinks', 'neutral'], ['bill', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["finally they wanted to take our app order before taking our wine order, seemed like the waiter couldnt handle it all at once."], "output": "[['wine', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food, service, and atmosphere are all pretty good, but a little pricy, coming to about 40$ a person if you order 1 drink and 1 appetizer each."], "output": "[['food', 'positive'], ['service', 'positive'], ['atmosphere', 'positive'], ['drink', 'neutral'], ['appetizer each', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["But the best offerings are the a la carte grilled items, such as the chicken with scallion skewers and asparagus with bacon rolls."], "output": "[['la carte grilled items', 'positive'], ['chicken with scallion skewers', 'neutral'], ['asparagus with bacon rolls', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The portions for the entrees did make up for it."], "output": "[['portions', 'positive'], ['entrees', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the prices are right and i strongly recommend this place for any time of day: early breakfast or late night snack."], "output": "[['prices', 'positive'], ['breakfast', 'neutral'], ['snack', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Well, once again I was unable to finish the paella and ended up taking it home ( I filled up on delicious fried brie and duck)- Meow Meow."], "output": "[['paella', 'neutral'], ['fried', 'positive'], ['duck', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Dishes feature intriguing names, and interesting combinations of fresh ingredients."], "output": "[['Dishes', 'neutral'], ['ingredients', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For spending over $100 per person for dinner, i would think that the waiter would put my plate of food down for me instead of handing me my dish."], "output": "[['dinner', 'neutral'], ['waiter', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The good service started from the moment we walked in the front door."], "output": "[['service', 'positive'], ['door', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We get our beers and then are told from a confuzed waitress that she realized that she can't give us the happy hour drink prices if we are not sitting at the bar."], "output": "[['beers', 'neutral'], ['waitress', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter was pleasant and I thought how bad could someone screw up basic Italian food?"], "output": "[['waiter', 'positive'], ['Italian food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They spoon the FAT GREASE over your steak when they bring it to the table."], "output": "[['FAT GREASE', 'negative'], ['steak', 'neutral'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food was good (get a crepe or steak!)"], "output": "[['Food', 'positive'], ['crepe', 'neutral'], ['steak', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When I had my dinner, the appetizers were flawless (try the carciofi and the polpettini), the entree was succulent (and fun having the branzino fileted at the table), and the tiramisu."], "output": "[['dinner', 'neutral'], ['carciofi', 'positive'], ['entree', 'positive'], ['branzino fileted', 'positive'], ['tiramisu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Hostess continued to ask us if everything was okay, and then did nothing when we gave her specific actions (how about some water or coffee served in paper cups)."], "output": "[['Hostess', 'negative'], ['coffee served', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["As expected, the wine list is as thoughtful as the menu the staff has earned my trust with their bullet-proof recommendations I have yet to be disappointed from their exhaustive list."], "output": "[['wine list', 'positive'], ['menu', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I'm a chef (30 years), and I can honestly say that I've finally found Italian food worth eating at a reasonable price."], "output": "[['chef', 'neutral'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Forget about the staff and go for the food and pleasant, if a bit cramped Lancaster, Pennsylvania like decor for comfort."], "output": "[['staff', 'negative'], ['food', 'positive'], ['decor', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The combination of fresh tomato sauce, fresh mozz cheese, basil and the dough they make with imported flour, makes this is one of the better pizza's in NY."], "output": "[['basil', 'neutral'], ['dough', 'neutral'], ['flour', 'neutral'], ['pizza', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had high hopes for this high-ranked wonder, only to be let down by inattentive service doubled by LONG food and drink wait times."], "output": "[['food', 'neutral'], ['wait times', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Some of the food is the Italian American red-sauce variety - fine if you're stuck in the past, but, there are also a number of very good, far more authentic Italian items at most reasonable prices."], "output": "[['food', 'neutral'], ['variety', 'neutral'], ['prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After we finished our salad our waitress told us that they had run out of roast lamb and pastitichio."], "output": "[['salad', 'neutral'], ['waitress', 'negative'], ['roast lamb', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The steak au poivre certainly lives up to its lofty reputation, but it shuoldn't overshadow many of the other delicacies on the menu, such as the crab cakes and the frisee salad."], "output": "[['steak au poivre', 'positive'], ['menu', 'neutral'], ['crab cakes', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Japanese folk music blaring on the quaint speakers are a trip and they have some interesting things on the menu like bull pen|s and turkey testicles."], "output": "[['Japanese folk music', 'neutral'], ['speakers', 'positive'], ['menu', 'neutral'], ['turkey testicles', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu includes the usual Chinese restaurant staples, but also includes a fairly diverse selection of other dishes not typically found in your average noodle house."], "output": "[['menu', 'neutral'], ['dishes', 'positive'], ['house', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Greek Glasswine is still on menu along side good value bottle selections fromaround the world."], "output": "[['menu', 'neutral'], ['value bottle selections', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The manager came personally to apologize and to my surprise, he brought me the drink, a big chocolate chip cookie, and a bag of chips!!!"], "output": "[['manager', 'positive'], ['drink', 'neutral'], ['big chocolate chip cookie', 'neutral'], ['bag of chips', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["of course i haven't mentioned the fact that we walked in on time for our reservation only to wait in the empty bar for over half an hour, being seated when we reminded the hostess that we were still waiting."], "output": "[['reservation', 'neutral'], ['bar', 'neutral'], ['hostess', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Went the next day for lunch - menu too pricey for lunch and the waiter was the WORST !!"], "output": "[['day', 'neutral'], ['menu', 'negative'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The only problem we had was with an incompetent waitress and floor manager which slowed down our food and seating."], "output": "[['waitress', 'negative'], ['floor manager', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["One oversight: the gf wanted tea to go along with the plate of yummies they gave me, but the server forgot to bring it since we took our time to finish the wine."], "output": "[['plate', 'neutral'], ['server', 'negative'], ['wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Patroon burger--Angus beef topped with a roasted tomato--is simple, yet able to stand on its own against any fully loaded competitor."], "output": "[['Patroon burger', 'neutral'], ['a roasted tomato', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Good location, but tourist-y and poor quality food."], "output": "[['location', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I realize that this place has a huge menu and, therefore, will have some not-so-good things, but it's the rudeness of the service that gets to me."], "output": "[['menu', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The chefs and staff are welcoming and happy to make substitutions or tune the spice up or down to your requests."], "output": "[['chefs', 'positive'], ['staff', 'positive'], ['spice', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Service was at best distracted, at worst disdainful, even though we came early with a reservation and are not food novices."], "output": "[['Service', 'negative'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["as written below, the drinks were watered down, and they didn't have the ginger martini available nor all of the wine list."], "output": "[['drinks', 'neutral'], ['wine list', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["great food, even better price, they also have a dj spinning great music, definitely a must try."], "output": "[['food', 'positive'], ['price', 'positive'], ['dj', 'neutral'], ['music', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["No matter what you order, you're almost certain to get so much food you'll be leaving with a doggie bag."], "output": "[['food', 'positive'], ['bag', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Good wines under $100 are included in the predominantly French list, but take some ferreting out to find."], "output": "[['wines', 'positive'], ['French list', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Since we already have our drinks there is no choice, so we are forced to pay full price."], "output": "[['drinks', 'neutral'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I think the person who says it has a wierd taste must have had very bad luck because I think this is the most authentic thai I've had in NYC (and I'm comparing it to food in Thailand)."], "output": "[['taste', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If the staff actually got it together and showed some customer service this place would be good."], "output": "[['staff', 'negative'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was not good at all, starting with the green salad, and the entrees (garlic chicken, chicken extreme) were chicken doused in oily sauce."], "output": "[['green salad', 'neutral'], ['sauce', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Waitress forgot drinks, and watched us begin our dinner without even water, strange."], "output": "[['Waitress', 'negative'], ['drinks', 'neutral'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After paying for our meal, we left some feedback with the manager (a chap named J."], "output": "[['meal', 'neutral'], ['manager', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Order the porterhouse and they put it between you and you kind of eat family style at a wooden table."], "output": "[['eat', 'neutral'], ['style', 'positive'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In any case, the food was quite yummy and on monday nights, they have a prix fixe $25 dinner which is definitely a deal."], "output": "[['food', 'positive'], ['prix', 'neutral'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Someone should tell these people that high prices on the menu does not make your restaurant better."], "output": "[['prices', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A full bar and a dozen different margaritas attract a happy hour crowd, and a tortilla machine is often surrounded by children watching the dough-to-tortilla transformation."], "output": "[['margaritas', 'positive'], ['transformation', 'neutral'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When we were finally seated about half an hour after my reservation, the waitress took her time taking our order."], "output": "[['reservation', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you're dining solo, you will feel completely at ease in the cozy environs; in fact, you're likely to see at least one other solo diner hunched over a book, sipping a glass of Chianti."], "output": "[['dining', 'neutral'], ['environs', 'positive'], ['diner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["(and don't miss the olive oil when dining in - not sure what they put in it, but it is de-licious!"], "output": "[['olive oil', 'negative'], ['dining', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I ordered dessert and it was they gave me the wrong flavor of ice cream."], "output": "[['dessert', 'neutral'], ['flavor', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Nice decor and an extensive menu lured me in, but the horrible service and rude staff drove me out."], "output": "[['menu', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Meaning, I ordered Lobster Tails as an entree (The Tails were delicious) and along with my Tails came Spinach with beans and fried potatoes that were close to potato steak fries."], "output": "[['Lobster Tails', 'positive'], ['entree', 'neutral'], ['Spinach with beans and fried potatoes', 'neutral'], ['potato steak fries', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I was surprise with the Champagne toast from the concierge who booked our dinner."], "output": "[['Champagne toast', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My girlfriend asked the bartender what kind of wine they had and since she couldn't hear she leaned on the bar to get closer to him and he made a face and told her not to get near him."], "output": "[['bartender', 'negative'], ['wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The rice that we were served for dinner was dry and hard, obviously left over from lunch."], "output": "[['rice', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the food was excellent, although they didn't have any dishes with meat, and the soy replacements definitely were not a replacement for meat."], "output": "[['food', 'positive'], ['dishes', 'negative'], ['soy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["ten minutes after we ordered the waitress came to our table and told us we had ordered complicated entrees and we would be waiting for 45 minutes."], "output": "[['table', 'neutral'], ['entrees', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The margaritas were mediocre, but it did not make up for the muzak they played in the resturant nor the bad food and drink they served."], "output": "[['drink', 'negative'], ['served', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere was wonderful, however the service and food were not."], "output": "[['atmosphere', 'positive'], ['service', 'negative'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had a tasty Caesar salad for an appetizer and ordered the 10 oz Fillet Mignon medium rare."], "output": "[['Caesar salad', 'positive'], ['appetizer', 'neutral'], ['oz Fillet Mignon', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Bartenders look like model wannabes and threw out my friend's beer before he was finished (about 1/4 left)."], "output": "[['Bartenders', 'negative'], ['beer', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They did not have mayonnaise, forgot our toast, left out ingredients (ie cheese in an omelet), below hot temperatures and the bacon was so over cooked it crumbled on the plate when you touched it."], "output": "[['mayonnaise', 'negative'], ['toast', 'negative'], ['ingredients', 'negative'], ['cheese', 'neutral'], ['omelet', 'neutral'], ['bacon', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The place is packed, they don't take reservations and waited almost 2 hours."], "output": "[['place', 'negative'], ['reservations', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When it came time to get the check, they couldn't seem to determine which of the servers had it."], "output": "[['check', 'neutral'], ['servers', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I though it was impossible to get such appetizers as a seafood salad or a seafood soup for about $3, but the taste and portions won't let you have any doubts."], "output": "[['appetizers', 'neutral'], ['taste', 'negative'], ['portions', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["An Egg like custard appetizer, a platter of different kinds of rolls made from: Lobster, Eel, Sword Fish, Trout, Blue Fin Tuna, Horse Mackerel, and Salmon Roe."], "output": "[['platter', 'neutral'], ['rolls', 'positive'], ['Eel', 'neutral'], ['Trout', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Get a bottle of wine, and eat what your heart has been desiring because all the things you would love to be on one menu--are!"], "output": "[['bottle of wine', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Granted, it's loud and sometimes obnoxious and it's such a pain to get seats for, but the the food is great."], "output": "[['seats', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Unfortunately the food and the service don't live up to the spectacular setting."], "output": "[['food', 'negative'], ['setting', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The place has a sort of trendy pseudo-asian decor that seems perfectly casual or romantic."], "output": "[['place', 'neutral'], ['decor', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The staff was great - and all guests are seated by the owners."], "output": "[['staff', 'positive'], ['owners', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["With dessert, the pre-theater is a great deal/meal."], "output": "[['dessert', 'neutral'], ['pre-theater', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Smallish menu, but more than adequate, and not that heavy on sauces which is so typical of italian restaurants."], "output": "[['menu', 'negative'], ['sauces', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This place is so very nearly achieving, but in the mean time, my advice - eat early elsewhere, then take your seat, order a bottle of wine and enjoy the performance and the ambience."], "output": "[['bottle of wine', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene You'll have to knock to enter this hidden dining room, a luxe windowless space featuring four wall-sized murals depicting famous landmarks throughout the seasons, as well as a handful of finery-laden tables."], "output": "[['Scene', 'neutral'], ['dining room', 'neutral'], ['space', 'neutral'], ['tables', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When the manager came over, he accused my friend of offending the chef and continued to argue with her about the dish."], "output": "[['manager', 'negative'], ['chef', 'negative'], ['dish', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For around $50 per person for brunch, it was a great value and the food really was fantastic."], "output": "[['brunch', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After waiting more than 15 minutes for our order to be taken and then having the waitress not know how to make certain drinks, our party of 7 was obviously dissatisified."], "output": "[['waitress', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Ones experience is truly dampened by having to trundle up lifts and escalators, further on arrival at the restaurant we found the actual dining room to be slightly sterile and lacking in atmosphere."], "output": "[['actual dining room', 'negative'], ['atmosphere', 'negative'], ['experience', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The worst service I have ever had - entered the restaurant and waited at the door for 5 minutes before deciding to push our way past the extremely small bar to find a waitress."], "output": "[['service', 'negative'], ['bar', 'negative'], ['waitress', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitress/hostess seemed a bit sad when we told her we weren't ordering dessert (those arepas are deceptively filling!"], "output": "[['waitress/hostess', 'negative'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was ok, good bread."], "output": "[['food', 'neutral'], ['bread', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I am a martini guy - vodka, not gin - and their classic martini with blue cheese olives is pretty damn near definitive."], "output": "[['martini guy', 'neutral'], ['martini with blue cheese olives', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While I would agree with the initial review that Asia de Cuba isn't really Asian or Cuban in its decor, the food was a nice fusion."], "output": "[['decor', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In fact, you can't really say you've arrived in this town until you've scored a table here and made the pilgrimage to east Harlem for luscious pastas and chicken in vinegar and lemon."], "output": "[['table', 'neutral'], ['pastas', 'positive'], ['chicken in vinegar', 'neutral'], ['lemon', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitstaff was helpful but watch out, after you pay your hefty bill managment will ask you to leave if they think you've lingered too long."], "output": "[['waitstaff', 'positive'], ['bill', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Setting The exposed brick and tangerine walls, flickering candles and tiny bar cast a formal mood across this cozy Park Slope trattoria, but the high ceiling fans and two glass walls (left open in warm weather) add a casual breeziness."], "output": "[['Setting', 'neutral'], ['candles', 'neutral'], ['bar', 'positive'], ['ceiling', 'positive'], ['breeziness', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We made reservations for 6pm on Friday and it was not necessary BUT the place got packed really quick around 7-8pm."], "output": "[['reservations', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Other than its impossible reservation (no matter how many months you call in advance, the only available time slots for dinner on a Saturday are always 4:45 or 9:45), Peter Luger is worth the drive over to Brooklyn."], "output": "[['reservation', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The pooris were miniscule, about 2 bites each; they serve 4 of those as a dinner for $25!"], "output": "[['pooris', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Highly suggest you sit at the bar for added atmosphere and generally friendly people."], "output": "[['bar', 'neutral'], ['atmosphere', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["As a lover of everything humus and cucumber, there is no other restaurant in the city that compares to Mogador's appetizers."], "output": "[['humus', 'positive'], ['cucumber', 'positive'], ['appetizers', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A great coal fired crust provides a backyard BBQ taste."], "output": "[['crust', 'positive'], ['backyard BBQ taste', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although the food was great, the service was so bad that I can't see myself ever returning."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Tried to get a table during restaurant week but there was an over an hour wait."], "output": "[['table', 'neutral'], ['wait', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The fresh mozzerella appetizer had to be the runniest mozz I have ever had, and the accompanying tomato was so over-salted I could barely eat it."], "output": "[['mozzerella appetizer', 'positive'], ['accompanying tomato', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The cultured wait staff were accommodating and helped explain and pronounce the items off the menu."], "output": "[['cultured wait staff', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A cocky, arrogant and shockingly condescending manager (all of 22 years-old) then told us we should leave the restaurant if we wouldn't move to the bar."], "output": "[['manager', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When I saw it on the menu I didn't beleive it and was not expecting the real thing."], "output": "[['menu', 'neutral'], ['thing', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["You can undoubtedly get better food and service for the price at other places, but certainly not with those views!"], "output": "[['food', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When I complained regarding the poor tiramisu, the waitress made a flip comment regarding the fact that I shouldn't order an italian dessert in an irish restaurant."], "output": "[['tiramisu', 'negative'], ['waitress', 'negative'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We held a birthday dinner for my friend and were very impressed w/ both food and service."], "output": "[['dinner', 'neutral'], ['food', 'positive'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My favorite dishes all involved squash of some kind, which i would not expect to love."], "output": "[['dishes', 'positive'], ['squash', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The restaurant appears clean and the food was fine until my dining partner discovered pieces of chicken about half way through her vegetarian dish."], "output": "[['dining', 'neutral'], ['chicken', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitresses and the diners have to scream at one another to give an order."], "output": "[['waitresses', 'negative'], ['diners', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We a menu that rearely changes,e xcept for one or two specials, the quality and care they put in thier food in evident."], "output": "[['quality', 'positive'], ['care', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This Raku provided fresh and sumptuous sushi, sashimi, and deliciously prepared cooked entrees, which did much to alleviate my jitters about fishing (or dining, as it were) in unfamiliar waters."], "output": "[['sushi', 'positive'], ['sashimi', 'positive'], ['entrees', 'positive'], ['dining', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When we sat, our waiter came over immediately and recommended the snapper and the pho-- some of the tastiest I've had, and I went to Tu Lan 3x a week in San Francisco."], "output": "[['waiter', 'positive'], ['snapper', 'neutral'], ['pho', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Had an OK dinner that was made better by the attention the owners pay to the patrons."], "output": "[['dinner', 'neutral'], ['owners', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I must start by stating plainly that I love Jeollado, but it is loud, the service is bad, but the rolls are great and it is the best deal (CHEAP) in town."], "output": "[['service', 'negative'], ['rolls', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We sat near the sluggish, hot and very loud kitchen and the service area was not wiped down once during the entire time."], "output": "[['kitchen', 'negative'], ['time', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Unfortunately, the food is awful, the staff really doesnt care about you, and the frozen hot chocolate is just a chocolate milkshake (it wasnt all that great) I went before lunch on a Thursday and it took me 2 hours to get in."], "output": "[['food', 'negative'], ['staff', 'negative'], ['frozen hot chocolate', 'negative'], ['chocolate milkshake', 'negative'], ['lunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There might be a wait for brunch or even for dinner, but the quality of the food is always worth the wait."], "output": "[['brunch', 'neutral'], ['dinner', 'neutral'], ['quality of the food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service, which was horrendous - they charged us for two appetizers when we asked to split one (when we brought it up, he insisted that the appetizer really did only consist of 2 sliced tomatoes and 1 slice of cheese)."], "output": "[['service', 'negative'], ['appetizers', 'neutral'], ['slice of cheese', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It was a crowded Wednesday night but we were seated near the kitchen right away, talked to all of the staff who were friendly and made the evening special for my date and I."], "output": "[['staff', 'positive'], ['special', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The $9 glass of wine which the waitress called good was like grape juice with alcohol and no sugar."], "output": "[['glass of wine', 'neutral'], ['waitress', 'negative'], ['grape juice', 'neutral'], ['alcohol', 'neutral'], ['sugar', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitresses are at your table filling your water or oil before your last sip or dip."], "output": "[['waitresses', 'positive'], ['water', 'neutral'], ['oil', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I managed to get the last reservation at 11:15pm during the week, and, upon entering the restaurant, my boyfriend and I were seated next to each other, hardly a romantic atmosphere!"], "output": "[['reservation', 'neutral'], ['atmosphere', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The upside of the smallish portions is that a good sake can do a better job working over one's date, and you don't leave the table w/ a food coma."], "output": "[['portions', 'negative'], ['table', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Personally, I like my food fresh, so you just have to tell the waiter that you would like to order by ear."], "output": "[['food', 'positive'], ['waiter', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I and 3 friends went there last night for dinner and loved the food, which I have to say was uniformly outstanding and some of the best I've had for under a zillion dollars in a long time."], "output": "[['dinner', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Then we were seated at a large booth and it took the waiter 20 minutes to come back and take our order but I sort of expected that with a new restaurant."], "output": "[['booth', 'positive'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The mint love letters and spaghettini primi we ordered as entrees were perfection."], "output": "[['letters', 'positive'], ['primi', 'positive'], ['entrees', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the waiter was extremely helpful, basically we gave him carte blanche to order small plates for us that he thought we'd like."], "output": "[['carte', 'neutral'], ['plates', 'neutral'], ['waiter', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["No doubt, the lobster bisque will knock your socks off, but you'd be cheating yourself if you didn't try some of the other options, specifically the sausage gumbo and the veal ghoulash really lit my fire."], "output": "[['lobster bisque', 'positive'], ['sausage gumbo', 'negative'], ['veal', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Their service needs some work, but it is safe to say that you will enjoy the food."], "output": "[['service', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have worked in the restaurant industry for 5 years, and so am understanding of things out of my server's control, and I have never experienced such poor service!"], "output": "[['server', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had one of the worst service experiences in memory having the prix fix brunch there--waving arms, calling, asking two or three times for everything from coffee to the check."], "output": "[['service', 'negative'], ['brunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I love deviled eggs, a BBQ staple - but I'll be damned if serving two eggs (four VERY small halves) qualifies as an appetizer."], "output": "[['BBQ', 'positive'], ['appetizer', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food is decent but portions are so tiny and the whole meal is served on huge plate which makes it look even more ridiculous."], "output": "[['Food', 'positive'], ['portions', 'negative'], ['meal', 'negative'], ['served', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene The entrance leads into a dim, narrow bar decorated with sake bottles, exposed brick and a beautiful arched wooden ceiling."], "output": "[['Scene', 'neutral'], ['bar', 'negative'], ['sake', 'neutral'], ['ceiling', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Nothing on the menu jumped out at me, but when we tasted the chicken and the pork tenderloin."], "output": "[['menu', 'negative'], ['pork tenderloin', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter fast to get our drinks, aptz, and orders."], "output": "[['waiter', 'positive'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["And don't forget to try the Korean rice wine to go with your dinner (Sansachun is one of my favorite)."], "output": "[['Korean rice wine', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have tried to make reservations, but both times, the hostess didn't have my name."], "output": "[['reservations', 'neutral'], ['hostess', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had to ask for the bill twice, and our water was refilled only when we asked for it."], "output": "[['bill', 'neutral'], ['water', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The salmon carpaccio was just bland lox over a bed of unseasoned spinich, the NY strip steak was not a good cut of meat, the fish special, snapper, was tough and flavorless, and the key lime pie for dessert tasted like it was from a supermarket."], "output": "[['salmon carpaccio', 'negative'], ['lox', 'negative'], ['steak', 'neutral'], ['meat', 'negative'], ['fish special', 'negative'], ['key lime pie', 'negative'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Appetizers were OK, steak was not as good as what I would have prepared at home on the grill."], "output": "[['Appetizers', 'positive'], ['steak', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I've been a few times for dinner and dessert and the food is always old-tasting and bland."], "output": "[['dinner', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["words can't even describe how delicious that dessert was post a bottle of wine and pesto ravioli."], "output": "[['dessert', 'positive'], ['pesto ravioli', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Forget what it was called, but it had some kind of onion puree on top that ROCKED and the steak was a grass-fed organic type and very tender."], "output": "[['onion puree', 'neutral'], ['steak', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For example, the last time I was there the bartender seemed visibly irritated that I would ask him for a drink instead of the waitress."], "output": "[['bartender', 'negative'], ['drink', 'neutral'], ['waitress', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We waited half an hour just to get menus, and watched another table of 10 people leave because they had been ignored by the (single) waiter."], "output": "[['menus', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The staff were all partying with each other at the bar, so even though we were the only ones there for food, it took 15 minutes to get menus."], "output": "[['staff', 'negative'], ['bar', 'neutral'], ['menus', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It is the only all Austrian wine list in the country and the waitress gladly broke it down for me, so I could find just the right wine for my meal."], "output": "[['wine list', 'neutral'], ['waitress', 'positive'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["but no reservations makes for a very long wait, usually of an hour."], "output": "[['reservations', 'neutral'], ['wait', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I was shocked by the amount of butter used in the pork and lamb dishes -- the smell of butter was literally wafting off the plate!"], "output": "[['smell of butter', 'negative'], ['plate', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["dining with my mother this past Saturday must have signaled to the wait staff that I wasn't cool enough to merit their attention."], "output": "[['dining', 'neutral'], ['wait staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The wait for brunch is kinda long (what can you say?"], "output": "[['wait', 'negative'], ['brunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The seafood sausage is ok, but the rest of the appetizers outshine them."], "output": "[['seafood sausage', 'neutral'], ['appetizers', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter handed us menus consisting of about 7 entrees, and after telling us the specials, informed us that there was no chicken."], "output": "[['waiter', 'neutral'], ['entrees', 'neutral'], ['specials', 'neutral'], ['chicken', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food Pies come in three sizes, from a petite five inches (perfect for the solo diner) up to 10."], "output": "[['Food Pies', 'neutral'], ['diner', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["best chicken in queens."], "output": "[['chicken', 'positive'], ['queens', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The ambience is extremely romantic, even if you get seated upstairs."], "output": "[['ambience', 'positive'], ['upstairs', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Just be sensible, if the wait is 45 minutes or longer--just have sushi there some other time, and eat something else that night."], "output": "[['wait', 'negative'], ['sushi', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I don't know why people complain about the service - our waiter brought our drinks and food out promptly."], "output": "[['waiter', 'positive'], ['drinks', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My dining companion had a steak with so much fat on it that he had to send back it."], "output": "[['dining', 'neutral'], ['steak', 'neutral'], ['fat', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the 3rd however, the waiter forgot to put in our order for food and we ended up waiting an hour for them (b/c they were really busy)."], "output": "[['waiter', 'negative'], ['food', 'neutral'], ['waiting', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have been a waiter for many years and I can tell you that if bad service is given you at least apologize to the costumer."], "output": "[['waiter', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Waited an hour for the food to come out, couldnt even find the waitress."], "output": "[['food', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When one of our party brazenly asked to substitue a flavor of gelato for one of the desserts on the menu, the waiter snobbishly told us that, Mario and the chef don't like to do that."], "output": "[['desserts', 'neutral'], ['menu', 'neutral'], ['waiter', 'negative'], ['chef', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The decor is nothing great to speak of, but who cares - the food is top notch."], "output": "[['decor', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food The seafood-dominant fusion menu features standout starters, like super-fresh raw bar oysters, crispy citrus-pepperoncini calamari and flaky lobster-mushroom tart with fiery chorizo and caramelized onions."], "output": "[['seafood-dominant fusion menu', 'neutral'], ['lobster-mushroom tart with fiery chorizo', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Even though we complained several times, they brought us the bill before dessert and the manager came to our table to mention he was closing the place for the night."], "output": "[['bill', 'neutral'], ['dessert', 'neutral'], ['manager', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I forget the name of the dish but anyone going here must get the shrimp cooked in molases and rum."], "output": "[['dish', 'neutral'], ['shrimp', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My wife and I invited our friends to a late dinner and were having drinks afterwards when the manager instructed the waitress not to serve us any more drinks as it was bottle service."], "output": "[['dinner', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Wait staff started swarming around us as if we just ordered cokes throughout lunch."], "output": "[['Wait staff', 'negative'], ['lunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I read the high reviews for Lombardi's and John's, and disliked the pizza I got at both places, so Grimaldi's was my last try at finding the perfect pie in NYC."], "output": "[['pizza', 'negative'], ['pie', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When I questioned the purpose of waiting on this line, I was asked to leave the bar."], "output": "[['waiting', 'neutral'], ['bar', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This is definately a place to go for drinks and then get dinner somewhere else!"], "output": "[['drinks', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our server, Ben, was perhaps the best waiter I've ever had--he walked us through the menu to design our meal, and suggested what textures, tastes, and wines would complement each other."], "output": "[['waiter', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In the hour we waited for our food we had to remind our mentally challenged waitress 3times to bring our chipssalsa."], "output": "[['food', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The kitchen is fast, but you sometime may have trouble getting a seat, since this place is very small."], "output": "[['kitchen', 'positive'], ['seat', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I met a client here and wasn't expecting much but after the lunch was over, I was pleasantly surprised with the quality of the meal and the price point."], "output": "[['lunch', 'neutral'], ['quality', 'positive'], ['meal', 'positive'], ['price point', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Good date place too, if the date isn't prissy about food (I'll marry the woman who splits the grilled sardines with me)."], "output": "[['food', 'negative'], ['grilled sardines', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu is short and sweet: hamburgers, cheeseburgers and double cheeseburgers, with all-beef patties steam-grilled on a pile of onions and served on square white buns with pickles."], "output": "[['menu', 'positive'], ['patties steam-grilled', 'neutral'], ['onions', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We also tried grilled chicken (not bad), fried whiting (fried too long, very greasy), taramasolata (too salty), chicken rice soup (oily mess), and an OK Greek salad."], "output": "[['grilled chicken', 'positive'], ['fried whiting', 'negative'], ['chicken rice soup', 'negative'], ['Greek salad', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["True, the menu doesn't offer a wide range of choices and portions are not la all-you-can-eat, buffet style (but is that a negative thing after all?"], "output": "[['menu', 'neutral'], ['portions', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went recently for brunch and will never go back - my glass of wine was vinegary and obviously old, my food gummy and disgusting, and the service totally ditzy."], "output": "[['brunch', 'neutral'], ['glass of wine', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food was served very promptly, but our wait for drinks was surprisingly long."], "output": "[['served', 'positive'], ['wait', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I politely told our waitress about this and she was not only apologetic, but the manager came over a minute later and apologized and bought myself and my guest another round of drinks."], "output": "[['waitress', 'negative'], ['manager', 'positive'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Nothing wrong with the service, either, but don't we all want something more from a dining experience than just average for above-average prices?"], "output": "[['service', 'positive'], ['prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Service was atrocious: appetizers came out 3 minutes after we ordered, and 10 minutes before we finally tracked down the bottle of wine we had ordered, the waiter rushed us from start to finish, we had to repeatedly track down someone to pour us more wine since it wasn't at the table, etc, etc."], "output": "[['Service', 'negative'], ['appetizers', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["But the price tag was high, and the food was comparable to a Las Vegas buffet for flavor and quality."], "output": "[['price tag', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In Short At this Upper East Side bar and restaurant, it's both the dinner and drinks that reel in the well-heeled clientele."], "output": "[['drinks', 'neutral'], ['clientele', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food It's a people-pleasing menu, with spaghetti and meatballs, calamari, eggplant Parmesan and other red-sauce classics alongside several more upscale dishes."], "output": "[['Food', 'neutral'], ['menu', 'positive'], ['spaghetti and meatballs', 'neutral'], ['calamari', 'neutral'], ['eggplant Parmesan', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["About the wait - be prepared to - it isn't just anyplace offering top notch cuisine for about $25 all in."], "output": "[['wait', 'neutral'], ['cuisine', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had to ask for bread for the table (several times)."], "output": "[['bread', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["At $16 a burger and $26 for a lobster roll, the food is definitely expensive."], "output": "[['burger', 'neutral'], ['lobster roll', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The freshness of the ingredients down to the perfection of the crust, it is truly the best."], "output": "[['freshness', 'positive'], ['ingredients', 'neutral'], ['crust', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Delivery portions are bigger and 2 can easily share 1 entree."], "output": "[['Delivery portions', 'positive'], ['entree', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Roof: very nice space (although I know 5 other rooftop bars just as good), but the crowd was a bunch of posers and the owner was a tool."], "output": "[['space', 'positive'], ['bars', 'positive'], ['posers', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food The casual Middle Eastern menu looks familar, but the food--made to order in the open kitchen--is a notch above its peers."], "output": "[['Middle Eastern menu', 'positive'], ['open kitchen', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Good value for breakfast."], "output": "[['value', 'positive'], ['breakfast', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitress waited until I went to the bathroom to ask my friend to order more food."], "output": "[['waitress', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Great food -- but some of the worst service in the neighborhood."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We ordered two appetizers and two entrees and were absolutely stuffed, we couldn't even finish our meals."], "output": "[['appetizers', 'neutral'], ['entrees', 'neutral'], ['meals', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu is a bit different and all of the selections are pretty tasty."], "output": "[['menu', 'neutral'], ['selections', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I would recommend this place as a great introduction to someone who has never tried indian food as they give you tiny appetizer like portions of a myriad of items(that they keep bringing you more of), so if you aren't crazy about an item it's not a big deal b/c there are a ton of other dishes to try."], "output": "[['indian food', 'neutral'], ['appetizer', 'negative'], ['portions', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Reserve a cozy window seat for more privacy, or hop onto a stool at the bar to dine solo."], "output": "[['privacy', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The sandwiches, platters, and pitzas are top notch too, but I could make a meal just out of their pita bread and babaganoush."], "output": "[['platters', 'positive'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["waiters were very nice, they dont take reservations during the week end, we waited at the bar with some sangria, Very good experience, loud music but we were able to communicate easily, overall i recommand this place to groups and dates,   Will be back more often!"], "output": "[['waiters', 'positive'], ['bar', 'neutral'], ['sangria', 'neutral'], ['dates', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Accompaning fish or meat are some hefty side dishes such as white rice, black beans, yucca, radish, tomato, and green pepper salad, or plaintains cooked a variety of different ways."], "output": "[['dishes', 'positive'], ['white rice', 'neutral'], ['black beans', 'neutral'], ['tomato', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It was somewhere between our waiter not knowing what sushi came as part of the tasting platter and the copious amounts of wine that he spilt while trying to pour me a taste that I realized."], "output": "[['waiter', 'negative'], ['sushi', 'neutral'], ['wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My friend was a vegetarian and the staff went out of their way to provide her with a special entree."], "output": "[['staff', 'positive'], ['entree', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitress came three times: to take our order, to bring the order, and to bring the check."], "output": "[['waitress', 'negative'], ['check', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The second time we went the waiter didn't put in our pizza order!"], "output": "[['waiter', 'negative'], ['pizza', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The restaurant didn't mind me sitting on their doorstep to the extent that the bartender invited me in for a drink."], "output": "[['bartender', 'positive'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although the service can be a bit brusque at times, the food is always good, hearty and hot."], "output": "[['service', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Entrees are right around $10, with fried rice and noodles being a little cheaper."], "output": "[['Entrees', 'neutral'], ['noodles', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The server was condescending and was unable to provide assistance with menu selections."], "output": "[['server', 'negative'], ['menu selections', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The portions are like a buffett for breakfast."], "output": "[['portions', 'negative'], ['breakfast', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["17 for a small cup of tea."], "output": "[['cup', 'negative'], ['tea', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After a waiter spilled a soda on me, without cleaning it up, offering me a napkin, or apologizing, I tried to send back my awful friench fries."], "output": "[['waiter', 'negative'], ['soda', 'neutral'], ['fries', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["He let us be seated, but told the hostess to make sure we didn't get menus until it was our arrival time."], "output": "[['hostess', 'negative'], ['menus', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Hostess was extremely accommodating when we arrived an hour early for our reservation."], "output": "[['Hostess', 'positive'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Furthermore, while the fish is unquestionably fresh, rolls tend to be inexplicably bland."], "output": "[['fish', 'positive'], ['rolls', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Wide range of dim sum and food."], "output": "[['range', 'positive'], ['dim sum', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have gotten warmer and much friendlier welcome and outstanding service at the other Thai restaurants in the Greenpoint area."], "output": "[['welcome', 'positive'], ['service', 'positive'], ['area', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went anyway and was greeted by the rude owner who practicly ripped our outside drink from our hands (although we were trying to throw it out anyway."], "output": "[['owner', 'negative'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Since I listened closely, I know they were a party of 2 without any reservation The manager then offered to seat us but we left."], "output": "[['reservation', 'neutral'], ['manager', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In summary: a terribly obnoxious and impolite host, a long and cramped wait for a table (complete with a mediocre bartender and drinks), more bad host, a calamari appetizer that may have actually been a joke, an hour's wait for our entrees, and tough chop-away-at-it veal."], "output": "[['bartender', 'negative'], ['drinks', 'neutral'], ['calamari appetizer', 'negative'], ['entrees', 'neutral'], ['chop-away-at-it veal', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When we received the bill, we asked the manager to do something about the drinks, considering how poor the service was and her reply was, Well, you got them!"], "output": "[['bill', 'neutral'], ['manager', 'positive'], ['drinks', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Always a treat, the butter chicken, palak paneer, and goat curries are sensational, while the tandoori, samosas, and chana aloo are a bit dry."], "output": "[['palak paneer', 'positive'], ['tandoori', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For entrees the suckling pig is a ho-hum pile of pulled pork and the fish-of-the-day was merely good."], "output": "[['entrees', 'neutral'], ['suckling pig', 'positive'], ['pork', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Sure the service isn't the best but the food is tasty and the prices are great."], "output": "[['service', 'negative'], ['food', 'positive'], ['prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I tried almost everything on the menu, but my fav is the pumkin raviloi, too bad it's only seasonal."], "output": "[['menu', 'neutral'], ['pumkin raviloi', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the first was dinner opening week some time ago - not a good piece of sushi to be had, the robata was so so and nothing was remotely memorable."], "output": "[['dinner', 'neutral'], ['sushi', 'negative'], ['robata', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["we had to wait at the bar for a table, but the atmosphere is bustling and is well worth it."], "output": "[['bar', 'neutral'], ['atmosphere', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Took 20 minutes and three requests to the waitress to get a drink, and then my steak came opposite to how I ordered it--twice!"], "output": "[['waitress', 'negative'], ['drink', 'neutral'], ['steak', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["As if the 2 hour wait wasn't bad enough, the host/manager was so busy flirting with attractive female customers, he didn't seem to notice we had been sitting at the bar and we ended up missing his call."], "output": "[['host/manager', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We could have made a meal of the yummy dumplings from the dumpling menu."], "output": "[['meal', 'neutral'], ['dumplings', 'positive'], ['dumpling menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our meals were a moderate portion and they weren't too spicy."], "output": "[['meals', 'neutral'], ['portion', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["large portions so unless you are of large stature you should not get 2 appetizers."], "output": "[['portions', 'positive'], ['appetizers', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While being shown to our table by a hostess, we were welcomed by Lidia Bastianich herself and seated at a great table in the dining room -- not too secluded, but not noisy."], "output": "[['hostess', 'neutral'], ['seated', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["this is the style of cooking that takes normal dishes to new highs."], "output": "[['style of cooking', 'positive'], ['dishes', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Fantastic flavor, but certainly not worth the high price of the small glass."], "output": "[['flavor', 'positive'], ['price', 'negative'], ['glass', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["even if you have to wait for a spot at the bar to wait for your table, the music and design of the space create an ambiance that is simultaneously chic and comfortable - something extraordinarily difficult to find in this city."], "output": "[['spot', 'neutral'], ['bar', 'neutral'], ['space', 'positive'], ['ambiance', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The only thing that was a little annoying was that the hostess didnt want to let us finish our first drinks at the bar and kept rushing us to sit down."], "output": "[['hostess', 'negative'], ['drinks', 'neutral'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My only two complaints are that (1) our server was a real space cadet and kinda inattentive and (2) the sodas were really small; overall, though, I had a great time and really enjoyed my dinner!"], "output": "[['space', 'neutral'], ['dinner', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The fact that the resteraunt staff couldn't even keep a reservation straight, not to mention that after screwing up, they told us to go scratch and made us wait almost 2 hours."], "output": "[['resteraunt staff', 'negative'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The portions were overly generous for both the apps and entrees without sacrificing the quality."], "output": "[['portions', 'negative'], ['apps', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While dining, none of us were impressed with the food."], "output": "[['dining', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Ziti Bolognese is baked in a similar sauce, with ground meat mixed in and cheese melted on top--the menu offers many variations on this theme."], "output": "[['Ziti Bolognese', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our server lamely offered a free after-dinner drink to make up for it after he failed to even ask how the food was once it was served."], "output": "[['after-dinner drink', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Even if you're just a middling junior exec, staff service makes you feel like a board member."], "output": "[['exec', 'neutral'], ['staff service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Two complaints- their appetizer selection stinks, it would be nice to get some mozzarella sticks on the menu."], "output": "[['appetizer selection', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["my sister asked for iced tea twice and the waitress said they didn't have."], "output": "[['iced tea', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service could be better but the management (Mariano) is quite helpful if there are any problems."], "output": "[['service', 'neutral'], ['Mariano', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Evening started out nice w/ complimentary glass of champagne, but turned sour as mussels were extremely overcooked, steak came in kid size portion smothered with sauce and owner recommended a wine special off the standard wine menu that was double the price of the most expensive bottle but made no effort to describe the wine as extremely special or significantly more expensive that what they typically serve."], "output": "[['glass of champagne', 'positive'], ['mussels', 'negative'], ['steak', 'negative'], ['portion smothered with sauce', 'negative'], ['owner recommended', 'negative'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We enjoyed the Raw Bar Special which was choice of 6 raw oysters or clams and a drink (house wine: red or white, or a beer) for only $8."], "output": "[['Raw Bar Special', 'positive'], ['raw oysters', 'neutral'], ['clams', 'neutral'], ['drink', 'neutral'], ['white', 'neutral'], ['beer', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Twister shrimp - too salty and nothing spectacular; Mango sorbet - so flavorful and rich, it tasted like ice cream!"], "output": "[['Twister shrimp', 'negative'], ['Mango sorbet', 'positive'], ['ice cream', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you are expecting big portions, go find a Cheesecake Factory."], "output": "[['portions', 'positive'], ['Cheesecake Factory', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We explained that we had left a standard 15% on food, and a slightly smaller percentage on alcohol (At least 10%)."], "output": "[['food', 'neutral'], ['percentage', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["better for dining with friends/significant others."], "output": "[['dining', 'positive'], ['others', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Subtle decor, above average wine list and a menu with a difference."], "output": "[['decor', 'positive'], ['wine list', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter (the one with the Spanish accent) was a bit pre-occupied with other things- hardly coming around to the table and nowhere to be seen most of the time."], "output": "[['waiter', 'negative'], ['time', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene Less trendy than Plan Eat Thailand, less crowded than Veracruz and infinitely more charming is Bean, a Mexican spot on Bedford Avenue's college-town-like stretch."], "output": "[['Bean', 'positive'], ['Mexican spot', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Great wine list with an extra expensive selection for all you big spenders."], "output": "[['wine list', 'positive'], ['selection', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["And toppings are not the best way to go here, and if you do, choose wisely -- it is a very thin crust that can't support much more than the fine sauce and sublime cheese it already has."], "output": "[['toppings', 'negative'], ['cheese', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The salsa always tastes like V8 with onion pieces."], "output": "[['salsa', 'positive'], ['onion pieces', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This is one of two Ping's in Queens, the other one on Queens Blvd in Elmhurst serves great seafood dishes fished straight off clean tanks."], "output": "[['Ping', 'neutral'], ['seafood dishes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I always trek to Bar 89 and get one of their huge sandwiches that comes with fries."], "output": "[['Bar', 'neutral'], ['sandwiches', 'positive'], ['fries', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Expect to be cramped and you may have to wait a little for your food, but the service is really friendly and helpful."], "output": "[['food', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitress told me that their dessert chef was trained in Sicily."], "output": "[['waitress', 'negative'], ['dessert chef', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Each course was accompanied by a new wine."], "output": "[['course', 'neutral'], ['wine', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although, a limited menu, we had no trouble picking out our delicious meal."], "output": "[['menu', 'negative'], ['meal', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The festive crew serves from a gigantic menu of American classics: chili, burgers, cobb salads, baked potatoes, wings, philly cheesesteaks, club sandwiches, you name it."], "output": "[['festive crew', 'neutral'], ['menu', 'positive'], ['chili', 'neutral'], ['burgers', 'neutral'], ['baked potatoes', 'neutral'], ['wings', 'neutral'], ['club sandwiches', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It was there that we ordered dinner by starting out with the foie gras mousse which was a wonderful a reccomendation by the waiter."], "output": "[['dinner', 'neutral'], ['foie gras mousse', 'positive'], ['waiter', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had a late 9:30 pm reservation; when we arrived and went to be seated, there was some type of discrepancy since the hostess was missing in action."], "output": "[['reservation', 'neutral'], ['hostess', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Service was bad enough that we decided to head out after the first round of drinks."], "output": "[['Service', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Mojitos were good and prices werent bad but sides should be included in price as portions are tiny."], "output": "[['Mojitos', 'positive'], ['prices', 'negative'], ['portions', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When asked to compare between two dishes, the server said whatever you like."], "output": "[['dishes', 'neutral'], ['server', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The bar tender didn't know where the tea was, waiters started making the drinks if the bar tender wasn't around."], "output": "[['tea', 'neutral'], ['waiters', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["i had a horrible experience with a waiter while trying to have breakfast friday morning."], "output": "[['waiter', 'negative'], ['breakfast', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have been surrounded with Indian food my entire life, and my lunch time experience at Devi was absolute bliss."], "output": "[['Indian food', 'neutral'], ['lunch', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["tender grilled calamari, shrimp with spinach in puff pastry, delicious fried brie."], "output": "[['tender grilled calamari', 'neutral'], ['shrimp with spinach in puff pastry', 'neutral'], ['fried brie', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I always get cantonese wonton noodle soup here, but the chicken is also almost always good."], "output": "[['wonton noodle soup', 'neutral'], ['chicken', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Get the bacon (best ever, hands down) and shrimp cocktail to start and steak for how many ever to finish."], "output": "[['bacon', 'positive'], ['shrimp cocktail', 'neutral'], ['steak', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiters can shoot off a 5 minute long list of specials, and they know the menu very well."], "output": "[['waiters', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Another hostess came by and told us that since we were now 5 we were a different table and couldnt' stay."], "output": "[['hostess', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They cook the cheese so that it turns a nice brown color and it is absolutely the best pizza I've ever had in New York."], "output": "[['cheese', 'neutral'], ['pizza', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The staff is constantly disappearing from the restaurant, making it impossible to get drink refills or to get the check."], "output": "[['staff', 'negative'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Reservations for parties under 5 people isn't allowed but their yummy cocktails and handsome waiters help soothe the pain."], "output": "[['Reservations', 'neutral'], ['waiters', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene With three outposts around town, Sarabeth's Kitchen has become a well-known and reliable spot for casual dining at breakfast, lunch or dinner."], "output": "[['Scene', 'neutral'], ['Kitchen', 'neutral'], ['spot', 'positive'], ['dining', 'neutral'], ['breakfast', 'neutral'], ['lunch', 'neutral'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had fried chicken of which KFC runs circles around, and the fries were a knock off of poor burger king spuds."], "output": "[['fries', 'neutral'], ['burger', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu of upscale American fare is somewhat intimidating as there are almost too many choices, but our wonderful waiter Eric came to the rescue suggesting and describing specials as if he had just polished off dinner himself."], "output": "[['menu', 'neutral'], ['waiter', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you go, try the marinara/arrabiatta sauce, the mozzarella en Carozza is mmmmmmmm."], "output": "[['marinara/arrabiatta sauce', 'positive'], ['mozzarella en', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were not offered the dessert menu and that waiter was so rude!~ I was very offended after a good meal."], "output": "[['dessert menu', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The manager sent us a complimentary glass of wine for the steak not being cooked like he wanted."], "output": "[['manager', 'negative'], ['glass of wine', 'neutral'], ['steak', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Don't let the ambiance of this place fool you, the food is far better than many pricey establishments."], "output": "[['ambiance', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The entrees tasted like microwaveable meals, the appetizers were ordinary, the sauces seemed like they came from a bottle, and the dessert was worse than packaged food."], "output": "[['entrees', 'negative'], ['meals', 'neutral'], ['appetizers', 'negative'], ['sauces', 'negative'], ['dessert', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After asking the waiter for a few minutes to look over the menu, we had to call out several times over 15 minutes to get him to come back to our table."], "output": "[['waiter', 'negative'], ['menu', 'neutral'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If the waitress had been remotely available or had come by to enquire about our food, I certainly would have sent it back, but since I was being taken out for a birthday dinner I did not want to make a fuss."], "output": "[['waitress', 'negative'], ['food', 'neutral'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food tasted good (for the most part), but it is customary to ask people how they would like their steak done (all 5 of ours were RAW."], "output": "[['Food', 'positive'], ['steak', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The pot pie, pork chop and chicken were cleaned off the plates so well they didn't need washing."], "output": "[['pot pie', 'neutral'], ['pork chop', 'neutral'], ['chicken', 'neutral'], ['plates', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["our dinner was marred by painfully slow service."], "output": "[['dinner', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Drinks are overpriced; wine list is good."], "output": "[['Drinks', 'negative'], ['wine list', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I was interrupted by the waiter to say that when we are done with dinner he'd bring one."], "output": "[['waiter', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The other side of the menu offers chicken, veal, and seafood standards, including perfect saltimbocca and a huge, succulent veal chop."], "output": "[['menu', 'neutral'], ['chicken', 'neutral'], ['seafood', 'neutral'], ['saltimbocca', 'positive'], ['veal chop', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There was only one server on duty and we waited a while for menus."], "output": "[['server', 'positive'], ['menus', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was so not Shanghai, but apparently those in the crowded dining room and waiting for tables wouldn't know the difference."], "output": "[['food', 'negative'], ['tables', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Great place to meet friends or co workers for drinks, dinner or both."], "output": "[['workers', 'neutral'], ['drinks', 'neutral'], ['dinner', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After waiting to get a table for over a half hour even though we had reservations, we went up to the host."], "output": "[['waiting', 'negative'], ['reservations', 'neutral'], ['host', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While the food was good (certainly no Il Mulino) the service was horrendous."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Went to dinner with friends, food was good, but the waitress was snippy, gave several exasperated sighs, kept pushing us to order more wine - on a sunday night - and now I realize that she added an eztra 20% to my debit charge."], "output": "[['dinner', 'neutral'], ['food', 'positive'], ['wine', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The two cons were the lack of information on the menus (they had just sushi roll names, with no description of their contents, printed in a bland format), and music selection, which didn't fit the ambiance."], "output": "[['menus', 'neutral'], ['music selection', 'neutral'], ['ambiance', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I go in for lunch whenever I can and have the thinnest sliced pastrami, along with fresh cut home-made potato chips."], "output": "[['lunch', 'neutral'], ['potato chips', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The kids really enjoyed their food and the value on the kids menu is good."], "output": "[['food', 'positive'], ['value', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Great decor, expensive drinks but worth the price, but the music is bland and the crowd is very cheezy."], "output": "[['decor', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Could have gone to Pastis for a salad three times the size for the same price."], "output": "[['salad', 'neutral'], ['size', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Friendly service, and outdoor seating in the warm months, eases the crush."], "output": "[['service', 'positive'], ['seating', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We asked for the check and had to wait 20mins for the waitress to come back and take our card."], "output": "[['check', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Besides, they used to be much more accommodating when I used to request a jalebi paratha instad of a plain naan as part of the brunch price."], "output": "[['naan', 'negative'], ['brunch price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Crowds do come on weekends, so be sure to make reservations."], "output": "[['Crowds', 'negative'], ['reservations', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When I really need good pizza I fly in From Arizona for a few pies, go to friends house , freeze them and fly home."], "output": "[['pizza', 'positive'], ['pies', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Conversation went like this: waiter: presented the steak and said 'Meduim well'"], "output": "[['waiter', 'negative'], ['steak', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["From the complimentary chef app of a delicate butternut squash ravioli in a delicious truffle sauce to an amazing buttery and tender langostine entree to a dessert that I can't remember because of the fabulous Cakebread Cabernet we were drinking -- the whole evening was amazing."], "output": "[['chef app', 'positive'], ['dessert', 'neutral'], ['Cakebread Cabernet', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["However, the food, once you get over the price, was very good."], "output": "[['food', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["she never once checked on us after serving our drinks, we asked another waitress about our sandwiches, she attempted to check on them but didn't really get an answer."], "output": "[['drinks', 'neutral'], ['waitress', 'negative'], ['sandwiches', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We sat there with the check and ordered dessert and more drinks."], "output": "[['check', 'neutral'], ['dessert', 'neutral'], ['drinks', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you want to avoid the long lines, arrive at 5:00 PM and have an early dinner."], "output": "[['lines', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": [": after ordering a bottle of wine (which was originally, inexplicably mistaken for 2 glasses of it), the (2) waitresses in charge of the outdoor space claimed that the bottle was right there in the only cooler used to service about 10 tables."], "output": "[['bottle of wine', 'neutral'], ['glasses', 'neutral'], ['waitresses', 'negative'], ['outdoor space', 'neutral'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were coldly greeted by a hostess and wait staff who, in spite of our reservation, did not want to seat any of us, including the elderly, until our entire party had arrived."], "output": "[['hostess', 'negative'], ['wait staff', 'negative'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["and although the service is a little slow, the lax atmosphere allows you to drink and eat away the afternoon or evening and not even care."], "output": "[['service', 'negative'], ['atmosphere', 'positive'], ['afternoon', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I was expecting an average meal and was really pleased to get an awesome dinner - and it was pretty cheap too."], "output": "[['meal', 'neutral'], ['dinner', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service and surroundings couldn't have been better, but the food was very disapointing at best."], "output": "[['surroundings', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We heard two different servers telling tables about these specials, and when we asked to hear them, they wouldn't tell us them."], "output": "[['servers', 'negative'], ['specials', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Up front, a large bay window provides a basement view of the neighborhood; at the rear, the tiny open kitchen serves up a limited variety of dishes: fish and chips, Thai chicken and hamburgers with caramelized onions all co-exist without any concerns about culinary common ground."], "output": "[['dishes', 'negative'], ['fish', 'neutral'], ['hamburgers with caramelized onions', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food  Kolonaki serves up everything from a European tuna sandwich (made with tuna, lemon juice, capers, parsley, onions, carrots, olive oil and basil) to scrumptious specialty desserts."], "output": "[['Food', 'positive'], ['tuna, lemon juice', 'neutral'], ['capers', 'neutral'], ['parsley', 'neutral'], ['onions', 'neutral'], ['specialty desserts', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went for the wine tasting dinner."], "output": "[['wine', 'neutral'], ['dinner', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The decor is a little plain and the seating is a touch too close but its worth it for the food."], "output": "[['decor', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food took over an hour despite at least two chasers, we had to track the server down to get extra drinks, the manager seemed to try and deliberately mislead us about the reason behind the delay and in the end the food was poor."], "output": "[['server', 'negative'], ['drinks', 'neutral'], ['manager', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Bartender made a bad drink for me and I sent it back and was charged for it."], "output": "[['Bartender', 'neutral'], ['drink', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["as appetizers, we ordered the zucchini flowers (rich savory) escargot-topped mushroom caps (mediocre)."], "output": "[['appetizers', 'neutral'], ['zucchini flowers', 'positive'], ['escargot-topped mushroom', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When I look at the menu I was surprised at the relatively high price compared with other korean restaurants."], "output": "[['menu', 'neutral'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["though the portions were smaller than average, the flavor and sauces that accompany them (truffle honey, cherries and peaches in mustard sauce) were all really good."], "output": "[['portions', 'negative'], ['sauces', 'positive'], ['truffle honey', 'neutral'], ['mustard sauce', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["their Stella on tap was almost flat, i saw the bartender whisking our beers to give them any sort of head."], "output": "[['tap', 'neutral'], ['bartender', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The restaurant is small so ask for seating in the front upstairs (the back, where we were sitting was incredibly hot) or on the first floor."], "output": "[['seating', 'neutral'], ['back', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter could not have been more patient with us as we (okay, my wife) made her decision on appetizers."], "output": "[['waiter', 'positive'], ['appetizers', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Went with my father without a reservation, and the maitre d' was very nice and sat us within 15 minutes of our arrival - we had been told that the wait would be an hour (this may be unusual)."], "output": "[['reservation', 'neutral'], ['maitre', 'positive'], ['wait', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["All of us enjoyed our meal, and for the price (~$185, w/ taxtip, 2 bottles of wine, 1 appetizer each, plus entrees) it was pretty impressive."], "output": "[['meal', 'positive'], ['price', 'positive'], ['bottles of wine', 'neutral'], ['entrees', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were a large group and would highly recommend all the drinks and foodThe manager on duty was understanding that our friends were very late and held our reservation."], "output": "[['drinks', 'positive'], ['manager', 'positive'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The hostess finally seated us at a table for two when there were three of us in an empty restaurant."], "output": "[['hostess', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Once dinner ended the party really started going inside they were playing great music."], "output": "[['dinner', 'neutral'], ['music', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food There's more here than top-quality sushi and sashimi, like sugar-coated foie gras with cashews and balsamic ginger sauce."], "output": "[['Food', 'neutral'], ['sashimi', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Seated in the upstairs part of the restaurant my party and I were subjected to rude, abrupt service and unmercifully long waits for our food."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The sign outside said, 26 beers on tap, however the bartender was unable to pull a pint from any of them."], "output": "[['beers', 'neutral'], ['tap', 'neutral'], ['bartender', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While we enjoyed the appetizers (kobe beef quesadillas and a mix of fries) the burgers themselves were not nearly as good."], "output": "[['appetizers', 'positive'], ['kobe beef', 'positive'], ['mix of fries', 'positive'], ['burgers themselves', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Now admittedly I went at lunch, when presumably the kitchen and waitstaff are less taxed than at dinner, but everything was fine."], "output": "[['kitchen', 'neutral'], ['waitstaff', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Instead, the chef made me a special creation off the menu, and wow."], "output": "[['chef', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Management or one of the many busboys should have been monitoring the tables more closely to ensure consistency - we had to ask for olive oil for the flatbread, when it was on nearly every other table as well as salt and pepper."], "output": "[['Management', 'negative'], ['salt', 'neutral'], ['pepper', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I can only say that the soup dumplings are almost as good as Joe's Shanghai and some dishes I had (like Eight Spice appetizer) were tasty while others (Shanghai style Shumai) were less so."], "output": "[['soup dumplings', 'positive'], ['dishes', 'positive'], ['Eight Spice appetizer', 'positive'], ['style', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["During the summer the outdoor area is a great place to sit and eat you pizza."], "output": "[['outdoor area', 'positive'], ['pizza', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the staff is great, but the food is just ok."], "output": "[['staff', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["An order of roast chicken is nicely crisped and moist, although the potato cubes alongside are limp."], "output": "[['roast chicken', 'positive'], ['potato cubes', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["from the hostess to the bartender to the waiter (who told us that we had to leave because the tables needed to be turned around more quickly even though it was a friends engagement dinner)."], "output": "[['bartender', 'negative'], ['waiter', 'negative'], ['tables', 'neutral'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A friend asked for cheese on her pasta and the waitstaff, including the manager, REFUSED to give it to her."], "output": "[['cheese', 'neutral'], ['pasta', 'neutral'], ['manager', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After waiting over a month for weekend reservations, I would of rather gone to IL Baggato."], "output": "[['waiting', 'negative'], ['reservations', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Paul's frozen seafood and the other cuts of meat were disappointing, with the only acceptable appetizers being the corn chowder and the gravlax."], "output": "[['seafood', 'negative'], ['meat', 'negative'], ['appetizers', 'positive'], ['corn chowder', 'neutral'], ['gravlax', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My g/f and I walked in one night, the owner greeted us at the door and took our coats, sat us in the back room (non-smoking at the time)."], "output": "[['owner', 'positive'], ['back room', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene A dark refurbished dining car hosts plenty of hipsters in carefully selected thrift-store clothing."], "output": "[['Scene', 'neutral'], ['dining car', 'positive'], ['clothing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the tasty food keeps luring me back, but after placing an order with who i assume must be the same rude sunday manager i keep hearing about, i'm not sure i will again."], "output": "[['food', 'positive'], ['manager', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["(try the Queso Fundido and fire) Upstairs there is a dining room which is decorated with brightly colored mexican theme."], "output": "[['Queso', 'neutral'], ['dining room', 'neutral'], ['theme', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We got seated right away, We got a nice starter from the kitchen, unfortunately the waiter that brought it could not explain what it was, it was delicious though."], "output": "[['starter', 'positive'], ['kitchen', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We did not get asked how I meal was nor did we get to our refill on waters until pretty much after the steak was finished."], "output": "[['meal', 'neutral'], ['steak', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you're looking for nonstop attention, a 20 page wine list and a waiter who puts your napkin on your lap, this is not the place to go."], "output": "[['wine list', 'neutral'], ['waiter', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I recently attended a celebratory dinner here and I just want to warn everyone that the service is the worst I have ever experienced!"], "output": "[['celebratory dinner', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had sage-and-prosciutto-wrapped veal tenderloin; my companion had duck with delightful cranberry relish; both served with carefully complementing, delicious sides."], "output": "[['duck', 'neutral'], ['cranberry relish', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I must say I enjoyed their soup dumplings more than Joe's,but the other dishes were disappointing."], "output": "[['soup dumplings', 'positive'], ['dishes', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There is NO waiting area - waiters, diners,and staff all converge in a tight space."], "output": "[['waiters', 'neutral'], ['diners', 'neutral'], ['staff', 'neutral'], ['space', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["First had a cheese platter at the bar and then enjoyed a nice dinner with friends."], "output": "[['cheese platter', 'neutral'], ['bar', 'neutral'], ['dinner', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is always good, and you get a lot for your money (the entrees, which are about $7-$8, come with the main selection plus two small sides, such as some veggies and two spring rolls)."], "output": "[['food', 'positive'], ['sides', 'neutral'], ['veggies', 'neutral'], ['spring rolls', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["As for the sides, the grits were more like soupy cheese sauce; the greens were okay."], "output": "[['sides', 'neutral'], ['grits', 'neutral'], ['soupy cheese sauce', 'neutral'], ['greens', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There was a fire crackling in the dining room, the bar was a finished copper, the stools were leather, and the lighting wasn't dim nor bright, but just."], "output": "[['dining room', 'neutral'], ['bar', 'negative'], ['stools', 'negative'], ['lighting', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After we waited nearly 25 minutes for our food (the place wasnt crowded), our waiter forgot some of our order and brought out a salad when we asked for everything to come out all at once."], "output": "[['food', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Within 3 minutes after we sat the waiter was hovering over us to get our food order."], "output": "[['waiter', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["To be honest, it cost $95 for two adults and a kid (including only two beers for the adults), and the only things worth eating were the raw oysters, information about which the staff was not too sure."], "output": "[['beers', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service was good, if a little slow, and the place was very crowded (which can be comforting, but on a date it may be hard with the constant noise)."], "output": "[['service', 'positive'], ['noise', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Intrigued by the ambience of the restaurant, some friends and I decided to have dinner at Paladar on Saturday night."], "output": "[['ambience', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For an appetizer try the chicken raviolis, and for dinner try the beef briolle."], "output": "[['appetizer', 'neutral'], ['chicken', 'positive'], ['dinner', 'neutral'], ['beef briolle', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The space is small and they don't take reservations, but go next door to the bar while you wait and have some very yummy sakatini's that are made with fresh fruit."], "output": "[['space', 'negative'], ['bar', 'neutral'], ['fruit', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["7A is open 24/7 and is great for lunch, brunch or a late night visit after partying all night."], "output": "[['7A', 'neutral'], ['lunch', 'positive'], ['brunch', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": [") While the location and ambiance sure are nice, I found the price a bit expensive considering the quality of the food was nothing spectacular."], "output": "[['location', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This restaurant has taken the trend of serving tiny portions on oversized plates to a new level."], "output": "[['serving', 'neutral'], ['plates', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The bar has a large selection of beers on tap,bottles or cans."], "output": "[['bar', 'neutral'], ['selection', 'positive'], ['beers', 'neutral'], ['tap', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had dinner with 5 friends at Blue Smoke last night and was totally impressed with the way the food has developed."], "output": "[['dinner', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Came here with a date and immediately liked the room and nice bar scene even though we had a bit of a wait despite a reservation."], "output": "[['bar scene', 'positive'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They are served with a free appetizer and the portions are perfect for lunch."], "output": "[['appetizer', 'positive'], ['lunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitress conveniently added in her tip into our bill, charged $10 for each margarita."], "output": "[['waitress', 'negative'], ['margarita', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waitress left halfway through dinner, without explanation, and was replaced by another waiter."], "output": "[['waitress', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was good but nothing to write home about - the rack of lamb was a bit too fatty."], "output": "[['food', 'positive'], ['rack of lamb', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A very pretty setting to have a meal, but unfortunately the service and food don't match the atmosphere."], "output": "[['service', 'negative'], ['food', 'negative'], ['atmosphere', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Waiter was a strange bird and when told we wanted to enjoy our dining experience and not be rushed through dinner, he assured us it takes 30 minutes to get entrees once food was ordered."], "output": "[['Waiter', 'negative'], ['dining', 'positive'], ['dinner', 'neutral'], ['entrees', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When the bill came, both appetizers were charged even though we had one bite of the first and it should not have served competely overcooked."], "output": "[['bill', 'neutral'], ['appetizers', 'neutral'], ['served', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Sit at the bar, order a glass of wine, and grab an appetizer: they'll also bring you olives, parmesan cheese, a huge loaf of delicious bread and 3 dipping sauces."], "output": "[['bar', 'neutral'], ['glass of wine', 'neutral'], ['appetizer', 'neutral'], ['bread', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The only thing better than the pizza (if possible), are the meatball and the eggplant parm heros."], "output": "[['pizza', 'neutral'], ['meatball', 'positive'], ['eggplant parm heros', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although it lacks the patina of places like Peter Luger's and Sparks, it still has a steakhouse's telltale wood paneling, chalkboard specials and decorative wine bottles."], "output": "[['Peter', 'neutral'], ['specials', 'neutral'], ['wine bottles', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu is an exact replica of its sister location in New Mexico - right down to the Frito Pie (don't knock it till you've tried) and a killer array of margaritas."], "output": "[['menu', 'neutral'], ['Frito Pie', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The osso buco is to die for and my favorite appetizer was the artichoke served on bed of frisee with a warm poached egg topped with parmesan cheese."], "output": "[['appetizer', 'positive'], ['artichoke served', 'neutral'], ['warm poached egg topped with parmesan cheese', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If coming to Tea and Anthipathy (yea u heard me) during conventional dining hours, expect a good long wait on the curb till tables open up."], "output": "[['dining', 'neutral'], ['wait', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For entree selections we had the chicken cacciatore, head on shrimp (in a honey glaze) spectacular, mozzarella en carozza (a little bit on the fishy side due to the anchovies) and the sliced italian meats, sapprosota to die for."], "output": "[['entree', 'neutral'], ['shrimp', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["But what would have been a pleasant experience was spoiled by the attitude and actions of the wait staff and the management."], "output": "[['attitude', 'neutral'], ['wait staff', 'positive'], ['management', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Why would anyone ever go here when the same food (and menu) is double the price of Baba and Jaya in Chinatown."], "output": "[['food', 'neutral'], ['menu', 'neutral'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Taci then moved to NYU, to a space as warm as an igloo, with an equally cold atmosphere, an attempt at a more upscale menu, and with all the charm of a pizza joint."], "output": "[['space', 'positive'], ['atmosphere', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I got a full 1/2 chicken, 4 ribs and a decent sized pile of brisket and pulled pork with a corn muffin filled with actual corn."], "output": "[['ribs', 'neutral'], ['brisket', 'positive'], ['pork', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you would like to charge us 5 dollars for service that would be fine, though comming from a restaurant where we buy a dessert for a bithday I thinks it's a bit cheap."], "output": "[['service', 'positive'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food Despite a menu that seems larger than the restaurant, great care goes into the preparation of every dish."], "output": "[['Food', 'positive'], ['menu', 'neutral'], ['dish', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["However the manager, who refused to come to our table to discuss it, said we were wrong (through the poor waitress) and would not replace our bottle."], "output": "[['manager', 'negative'], ['table', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our server seemed to be new because he continually had to go back to the kitchen to check on menu items."], "output": "[['server', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Thought we were going to have a winner from the pleasant person on the other side of the phone when I called for our reservation."], "output": "[['person', 'positive'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The matre de ignored what I said about my girlfriend having to look for a waiter to refill her glass (twice), I mentioned about my rice, he said, You should have spoken up."], "output": "[['waiter', 'negative'], ['rice', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After confronting the counter clerck he assured me the soups would stay warm as long as I wasn't walking 20 minutes to my destination."], "output": "[['counter', 'neutral'], ['soups', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I've eaten here a couple times and the food is always good (jerk chix wings, fried chicken, meat loaf, etc) but the service is terrible."], "output": "[['food', 'neutral'], ['fried chicken', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the service was horrible then and the food was decent."], "output": "[['service', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were put on the wait list, seated in 15 min after a quick drink at the bar and had an incredibly entertaining waiter and dined next to a few regulars who raved."], "output": "[['wait list', 'neutral'], ['bar', 'neutral'], ['waiter', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["As host of the party with a full guestlisted group, I still had to wait online for 20 minutes before anyone from the staff would even look in my direction."], "output": "[['host', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["went for dinner with two friends and all of us were raving about our meals--the best steak i've had in a long time, and the duck and salmon were also delicious."], "output": "[['dinner', 'neutral'], ['meals', 'positive'], ['steak', 'positive'], ['duck', 'positive'], ['salmon', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Casual and kid-friendly, the red-and-gold colored restaurants offer quick drive-thru or dine-in service with a menu of burgers, sandwiches and more."], "output": "[['service', 'positive'], ['burgers', 'neutral'], ['sandwiches', 'neutral'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service was spotty as a couple of drink orders were forgotten and the waiter didn't really come to check on us."], "output": "[['service', 'negative'], ['drink', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["D, who can't decide on a single dish, the tapas menu allowed me to express my true culinary self."], "output": "[['dish', 'negative'], ['tapas menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The recipe uses shrimp with shell since they preserve the juice much better and it just made me remember my childhood at the beach in Acapulco."], "output": "[['recipe uses shrimp', 'neutral'], ['juice', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Build your own pie--add toppings to either Ultimate Deep Dish, Crunchy Thin Crust or Classic Hand Tossed styles--or select a Feast Pizza, like the MeatZZa Feast, topped with pepperoni, ham, beef and Italian sausage."], "output": "[['toppings', 'neutral'], ['Crust', 'positive'], ['Feast Pizza', 'neutral'], ['MeatZZa', 'neutral'], ['pepperoni', 'neutral'], ['ham', 'neutral'], ['beef', 'neutral'], ['Italian sausage', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Luckily, I made reservations for our group or else it would have been a long wait."], "output": "[['reservations', 'neutral'], ['wait', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Came recommended to us, but we found the food to be so-so, the service good, but we were told we could not order desert since the table we were at had a reservation waiting."], "output": "[['food', 'negative'], ['waiting', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We didn't order-the waiter just kept piling the food in front of us."], "output": "[['waiter', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Denny's serves a better Grand Slam breakfast--and at a quarter of the price (I paid $21 w/o tip for b-fast--I went back a second time, because the restaurant was highly touted and I thought the first bad experience was a fluke."], "output": "[['Grand Slam breakfast', 'positive'], ['price', 'neutral'], ['tip', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The server was dutiful yet insincere, the brunch drinks above average."], "output": "[['server', 'negative'], ['brunch drinks', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For dinner we decided to take our servers advice and order several items to share."], "output": "[['dinner', 'neutral'], ['servers', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Then the menu is all in Italian well I don't speak Italian so it took forever for the waitress to translate."], "output": "[['menu', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is decent, too commercialized Italian food, and very verylarge portions, which ca end up being very expensive if you are not up for sharing and ordering wisely."], "output": "[['Italian food', 'positive'], ['portions', 'positive'], ['wisely', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Not being familiar with Vietnamese cuisine, we found the menu descriptions very helpful."], "output": "[['Vietnamese cuisine', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["All of the dishes we had were very good, but the fries were a little on the salty side, which we actually didn't mind."], "output": "[['dishes', 'positive'], ['fries', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was phenomenal- brought me back to Tuscany with that olive oil."], "output": "[['food', 'positive'], ['olive oil', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Amazingly tasty cheese drenched in oil and soft yet crisp perfect dough, who could ask for more?"], "output": "[['cheese', 'positive'], ['oil', 'neutral'], ['dough', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Risotto's, Sushi Tuna, wasabi aioli, Steak Frite, and the Best weekend Brunch in Queens."], "output": "[['Sushi Tuna', 'neutral'], ['wasabi aioli', 'neutral'], ['Steak', 'neutral'], ['Brunch', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I ordered the flounder special - the fish was fresh but the dish lacked flavor."], "output": "[['fish', 'positive'], ['dish', 'negative'], ['flavor', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Their Korean menu was also equally impressive, A must try is the Kimchee cabbage pancakes as an appetiser ( the portions were as big as an entree!)"], "output": "[['pancakes', 'neutral'], ['portions', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter told us that he had checked with the kitchen because he noticed that we had not gotten our dinners and they said it would be out shortly, shouldn't someone have said something to us?"], "output": "[['waiter', 'negative'], ['dinners', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter was confused and forgot an additional soda when we asked for it."], "output": "[['waiter', 'negative'], ['soda', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were left to choose between boring salmon and chicken entres or a duck substitution."], "output": "[['chicken', 'negative'], ['duck substitution', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Just expect to wait a good twenty minutes before they take your order (even when the restaurant is half empty), you'll have to ask at least 5 waiters and a manager for coffee before they bring it to you and when they bring your orders out wrong, expect the manager to side with the chef and not you."], "output": "[['waiters', 'negative'], ['coffee', 'neutral'], ['chef', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It is a nice room with a cool bar and you should stop in for a drink and Tapas but dinner was very weak!!!!"], "output": "[['room', 'positive'], ['bar', 'positive'], ['drink', 'neutral'], ['dinner', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The calamari salad was great while the lamb ribs were fat, fattier and fattiest."], "output": "[['calamari salad', 'positive'], ['lamb ribs', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In my opinion, the bar is not very well laid out, its narrow design makes it hard to meet a group for drinks."], "output": "[['bar', 'neutral'], ['design', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter was completely unfamiliar with the menu and did not bother to tell us that they were out of several items (even though we arrived at 7 pm on a Saturday night!)"], "output": "[['waiter', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The music was a bit loud but the song selection was great, so we blew off desert and had another round of drinks at the bar."], "output": "[['selection', 'positive'], ['drinks', 'neutral'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitress let us taste three wines before deciding (we were only ordering glasses) and then we chose to eat at the bar (same menu) since it was so comfortable."], "output": "[['waitress', 'positive'], ['bar', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["You get three courses for $20 at lunch and the amount of food is more than enough for anyone to leave feeling fully satisfied."], "output": "[['courses', 'neutral'], ['lunch', 'neutral'], ['amount of food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A+ for the food but the wait staffs need to educate themselves better."], "output": "[['food', 'positive'], ['wait staffs', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We decided to get out of there and go to a safe place with bigger portions and normal food."], "output": "[['portions', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the wait staff looks like were doing us a favor giving us service and two loud guys at the bar made my evening with my wife quiet miserable."], "output": "[['wait staff', 'negative'], ['service', 'neutral'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The tables were too close together, the food wasn't impressive, and the service was often times completely missing - waiting 45 minutes between ending dinner and being asked about dessert is not what a restaurant of this caliber should be all about."], "output": "[['tables', 'negative'], ['food', 'negative'], ['service', 'negative'], ['dinner', 'neutral'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["unbeknownst to the three of us, the hostess made note of the fact that i was celebrating my b-day after a member of my dinner party made a very brief reference to it as we were seated."], "output": "[['hostess', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Enjoy the food, because it is remarkable, but don't be too willing to be gratuitis to a server that does not deserve it."], "output": "[['food', 'positive'], ['server', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Clams, shrimp, mussels, scungilli, and calamari served together in a spicy red sauce atop linguine are full of flavor; steak pizzaiola, a heroic portion of tender beef in a pool of garlicky marinara, comes with a side of spaghetti."], "output": "[['Clams', 'neutral'], ['shrimp', 'neutral'], ['mussels', 'neutral'], ['scungilli', 'neutral'], ['calamari served', 'neutral'], ['spicy red sauce atop linguine', 'neutral'], ['flavor', 'positive'], ['steak', 'neutral'], ['portion of tender beef', 'neutral'], ['spaghetti', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service sucked--we didn't get bread, our eggs were cold, and their brunch prix fix does not include an alcoholic drink."], "output": "[['bread', 'negative'], ['brunch prix', 'negative'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When a meal starts with bad bread, you know you're in for a long night."], "output": "[['meal', 'neutral'], ['bread', 'negative'], ['night', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Most dishes are smothered in melted cheese or merely mediocre; flan is flat and pedestrian, drenched in tasteless sugar syrup; and even its supposedly best feature - the margarita - is a hit-or-miss affair."], "output": "[['dishes', 'negative'], ['cheese', 'negative'], ['flan', 'negative'], ['sugar', 'negative'], ['margarita', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It appears to be a charming french outdoor bistro, and the food wasn't bad, but the waiters were clearly tired of dealing with tourists, and didn't handle us with care."], "output": "[['french outdoor bistro', 'positive'], ['waiters', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I felt the chef was using truffles too much just to cover up mediocre food."], "output": "[['chef', 'negative'], ['truffles', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["To finish, the cost of the dinner was over-priced."], "output": "[['cost', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In Short The few window-front tables fill quickly, but most customers prefer not to linger in the nondescript space, in favor of taking their Thai food to go, or phoning in for delivery."], "output": "[['window-front tables', 'neutral'], ['space', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["On the top of everything at the end of the dinner the waiter gave us the wrong check."], "output": "[['dinner', 'neutral'], ['waiter', 'negative'], ['check', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["However, you don't even really need the menu, because the daily specials are always tempting and delicious."], "output": "[['menu', 'neutral'], ['daily specials', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In other words, conserative types craving simpler things like grilled chicken or salmon probably would not appreciate Tabla's distinctive and unusual menu."], "output": "[['salmon', 'neutral'], ['menu', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The staff were very friendly, the prices were relatively average, not bad, and the food was great."], "output": "[['staff', 'positive'], ['prices', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It is expensice, but the portions are big and include a side, salad, nan and rice along with your main meal!"], "output": "[['portions', 'positive'], ['salad', 'neutral'], ['nan', 'neutral'], ['rice', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After dining there twice, all the waiters will remember you and what you ordered the last time you were there!"], "output": "[['dining', 'neutral'], ['waiters', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Comfort standbys--including bacon-wrapped meat loaf and barbecued ribs, and upscaled interpretations--like tuna club made with wasabi mayo, share space with brunch favorites (Belgian waffles, fluffy buttermilk pancakes and wrecked eggs, or tofu)."], "output": "[['Comfort', 'positive'], ['barbecued ribs', 'neutral'], ['interpretations', 'neutral'], ['wasabi mayo', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It might be the best sit down food I've had in the area, so if you are going to the upright citizen brigade, or the garden, it could be just the place for you."], "output": "[['food', 'positive'], ['garden', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene Unpolished but cozy, with red walls, arty sconces and deep, comfortable booths, Raga calls little attention to itself."], "output": "[['Scene', 'positive'], ['walls', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This is the place to come for coffee and dessert; they have an enormous and decadent selection of cakes, pies, and other things involving chocolate."], "output": "[['coffee', 'positive'], ['dessert', 'positive'], ['selection of cakes', 'positive'], ['pies', 'neutral'], ['chocolate', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service is a bit slow, but harkens back to my years growing up in Napoli, Italy where things are not rushed and when you sit down for dinner the table is yours all night."], "output": "[['service', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere is bland and non-descript and the service is fine."], "output": "[['atmosphere', 'negative'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene Tucked away on the second floor of a small, nondescript Madison Avenue building, Caviar Russe feels more like a private club than a restaurant."], "output": "[['Scene', 'negative'], ['Caviar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Service was good, the waiter was a little flip, but we can deal with that."], "output": "[['Service', 'positive'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Meals generally begin in a pub-food vein, with appetizers like featherweight, perfectly salted fried clams and brown sugar-lacquered ribs that are good enough to take on any barbecue joint in the city."], "output": "[['Meals', 'neutral'], ['appetizers', 'positive'], ['salted fried clams', 'positive'], ['brown sugar-lacquered ribs', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Waiter ignored us, never asked if we needed anything, never received a dessert menu or asked if we wanted coffee, or even the check."], "output": "[['Waiter', 'negative'], ['dessert menu', 'neutral'], ['coffee', 'neutral'], ['check', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["when someone from our table of 5 asked the waitress for refill on water, she comes back and fills only that person's glass, leaving the rest of the table with almost empty glasses."], "output": "[['waitress', 'negative'], ['water', 'neutral'], ['glasses', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The last three times I've called (in addition to asking me to wait for a long time before taking my order), they've given me grief about asking for delivery even though my address is clearly within the map printed on the menu, just because the delivery guy gets mad if he has to go out of his way."], "output": "[['menu', 'neutral'], ['delivery guy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food is mediocre, except for Mushroom Custard and Foie Gras in Fire Ice."], "output": "[['Food', 'negative'], ['Mushroom Custard', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The prices did not reflect the quality of the meal."], "output": "[['prices', 'negative'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Among the entrees, choose the stellar mole--deep, thick and chocolatey--blanketing tender chicken or poured over a chicken enchilada rather than the dry arroz con pollo."], "output": "[['entrees', 'neutral'], ['stellar mole', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When the food came, it was almost good, but the lack of AC, bad service, and overall apathetic staff, from the HOST, to the MANAGER to the WAITER, ruined the experience."], "output": "[['food', 'positive'], ['service', 'negative'], ['staff', 'negative'], ['HOST', 'negative'], ['MANAGER', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A few years ago I would have rated it much higher, but now - with other better choices such as Candle Cafe, Good Health Cafe and others, the dated menu, crowded atmosphere are spacey service is not the greatest choice."], "output": "[['menu', 'neutral'], ['atmosphere', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I think they just tried to get a little too creative with the menu and actually ended up losing flavor in some of the dishes."], "output": "[['menu', 'neutral'], ['flavor', 'negative'], ['dishes', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The place looks like the inside of a factory, with its steel drums, over-amped A/C and hard wooden benches, and the industrial decor seeps into overly streamlined menu and passionless food."], "output": "[['menu', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When I requested a specific beer on the menu, the waiter said they were all out of that one and kept pushing the only available beer, which I didn't want."], "output": "[['menu', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["About the food we had a little difilculty keeping the orders straight ,the menu has too many choices,but the server was very helpul and suggested de paella valenciana which was extremele delicious."], "output": "[['menu', 'neutral'], ['server', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Mixed drinks were Casino Quality we weren't sure if the sides on our tables were left from the previous diners, but when our steaks (Only one choice on the menu) arrived."], "output": "[['Mixed drinks', 'neutral'], ['sides on', 'neutral'], ['tables', 'neutral'], ['diners', 'negative'], ['steaks', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Kitchen is only separated from its patrons by glass is immaculate and the service is undeniable heartfelt."], "output": "[['Kitchen', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food came cold and a sauce that came with one of the dishes had developed a skin."], "output": "[['food', 'negative'], ['sauce', 'negative'], ['dishes', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["WHile the seafood by the pound was the freshest I've had in a while, I was pleasantly surprized at the other entrees available on the menu-- Delightfully presented!"], "output": "[['seafood', 'positive'], ['entrees', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The spacious bar, with its own menu of small plates and a lengthy list of wines by the glass, is a boon to single diners."], "output": "[['menu', 'neutral'], ['plates', 'neutral'], ['wines by the glass', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Specials are likely to encompass such exotica as wild Scottish venison and free-range Australian lamb, or seasonal items like springtime's Hudson River shad roe."], "output": "[['Specials', 'neutral'], ['lamb', 'neutral'], ['items', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Yellowtail tuna carpaccio, lightly dressed with a hint of mint, sings of summer, and crab salad partnered with sweet-hot mango mustard and greens hits all the right flavor notes."], "output": "[['Yellowtail tuna carpaccio', 'neutral'], ['hint', 'neutral'], ['mint', 'neutral'], ['crab salad partnered with sweet-hot mango mustard', 'neutral'], ['greens', 'neutral'], ['flavor notes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was a meal I could find anywhere else in the city for a better price."], "output": "[['meal', 'neutral'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Overall,it's a good place to have dinner and hang out if you do not mind waiting for food,weird music and rude manager."], "output": "[['dinner', 'neutral'], ['waiting', 'neutral'], ['music', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Service was unbelievably on target down to the smallest detail; our waiter invited us to sample a new desert under consideration for their menu and a new line of ice wines."], "output": "[['Service', 'positive'], ['waiter', 'positive'], ['menu', 'neutral'], ['wines', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["And for families they have high chairs and waiters were really nice to my kid."], "output": "[['chairs', 'neutral'], ['waiters', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Once seated we were greeted by a very rude waiter who threw menus at us and then snatched them away as we were ordering."], "output": "[['waiter', 'negative'], ['menus', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A regular Japanese menu is available for those who would like to experience traditional Japanese cuisine."], "output": "[['Japanese menu', 'neutral'], ['Japanese cuisine', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There are 1 or 2 vegetarian dishes, but the sides platter has a bit of everything, so you get the full flavor of Latin American food."], "output": "[['vegetarian dishes', 'neutral'], ['Latin American food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had blackened salmon and my fiance had chicken marsala."], "output": "[['salmon', 'positive'], ['chicken marsala', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Drinks took a while, and after a few rounds pf the we're sorry, we don't have this bottle sir routine."], "output": "[['Drinks', 'neutral'], ['sir routine', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["i mean the place was empty and it seemed to take for ever to get food, drink or the check."], "output": "[['place', 'positive'], ['food', 'negative'], ['drink', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The journey may be long and the wait may be longer, but there is nothing that could keep me from this pizza."], "output": "[['wait', 'negative'], ['pizza', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter was pretty much non-existent and when he did come to our table he practically tossed our plates and wine glasses in front of us."], "output": "[['waiter', 'negative'], ['table', 'neutral'], ['plates', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While the environment is still fun and diverse, the food quality has been sliding lately."], "output": "[['environment', 'positive'], ['food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter said 3 words to us, wisked away our food as we were finishing, and the maitre'd could not take his eyes off our table waiting for us to leave."], "output": "[['waiter', 'negative'], ['food', 'negative'], ['maitre', 'negative'], ['table waiting', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Its definitely recommended to make a reservation on the weekends, since its difficult to walk-in and get a table."], "output": "[['reservation', 'neutral'], ['table', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was pretty good, but a little flavorless and the portions very small, including dessert."], "output": "[['food', 'positive'], ['portions', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food and decor is above average, but it is clear the restaurant has bad management and service."], "output": "[['food', 'positive'], ['decor', 'positive'], ['management', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["One of my favorite places to get a cup of tea or to have a casual brunch with the newspaper."], "output": "[['cup of tea', 'neutral'], ['brunch', 'neutral'], ['places', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There were three parties of two standing in the front entrance looking like bumbling idiots while not a single host, waiter, or manager attended to us."], "output": "[['host', 'negative'], ['waiter', 'negative'], ['parties', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["One of my friends told them it was my birthday and the staff relally surprised me when their came to me singing with the mexican hats and a dessert with a candle on it."], "output": "[['staff', 'positive'], ['mexican', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I am not good with using chopsticks and asked for a fork, instead the owner insisted that I try using a chopstick an made me an easy-to-use chop stick right there on the spot!"], "output": "[['chopsticks', 'neutral'], ['owner', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you want to have fresh grill fish served just with virgin olive oil and lemon Telly's Taverna is the place for you."], "output": "[['grill fish served', 'positive'], ['virgin olive oil', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After asking several different people find our waiter, he returned to say he couldn't find any wine and begged us to order sake instead."], "output": "[['waiter', 'negative'], ['wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In addition, they lack basic ammenities like a toaster, and the decor was shabby, at best."], "output": "[['toaster', 'neutral'], ['decor', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The table next to us recommended that share because the portions are big(we split two entrees)The food was so good I wish that there was some left over to take home for the next day."], "output": "[['portions', 'positive'], ['entrees', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["so back to the Napoleon was pretty yamie but over deep fried."], "output": "[['Napoleon', 'positive'], ['fried', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The owner walks around barking at his employees every chance he gets, and makes everyone----customers and staff----nervous."], "output": "[['owner', 'negative'], ['employees', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This is not haute cuisine, but that' part of what I love about it - it has an honest, intimate feel with no pretensions, just like eating in an Italian family's home."], "output": "[['cuisine', 'negative'], ['feel', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The hostess was snooty since we did not have a reservation but the rest of the dining experience amply made up for it."], "output": "[['hostess', 'negative'], ['dining', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The hostess had us wait in the bar while our table was set up and we ordered what had to be the best mojitos in the city."], "output": "[['hostess', 'neutral'], ['bar', 'neutral'], ['mojitos', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The problem is that if you want anything to continue the meal, if you need an extra minute to go over the menu, or if, horrors, you want the check, you might be in for a lengthy wait."], "output": "[['menu', 'neutral'], ['wait', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have never tried anything else on the menu the burgers are so good."], "output": "[['menu', 'neutral'], ['burgers', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The shrimp and lobster bisques are very good, but serverd in styrofoam cups which will affect the taste if not eaten quickly."], "output": "[['shrimp and lobster bisques', 'positive'], ['taste', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The hostess told me she could accomodate my group without a reservation but we ended up waiting nearly an hour and were seated in the smallest cramped area."], "output": "[['hostess', 'negative'], ['reservation', 'neutral'], ['area', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["From soups (love the pumpkin corn bisque), to sandwiches (gilled cheese is my favorite), to the hot food that's mostly asian influenced, and salads that even include seared tuna, there's something for everyone."], "output": "[['pumpkin corn bisque', 'positive'], ['sandwiches', 'neutral'], ['hot food', 'neutral'], ['salads', 'neutral'], ['tuna', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The portions are not huge, but they do include an alcoholic beverage or fresh juice, so that made up for it."], "output": "[['portions', 'negative'], ['fresh juice', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Got a table during restaurant week for lunch and the service was cordial, if slower than usual."], "output": "[['lunch', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["But despite that our dinner took far too long to be served."], "output": "[['dinner', 'neutral'], ['served', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were here for lunch and were seated promptly in the bright, comfortable dining room."], "output": "[['lunch', 'neutral'], ['seated', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Service: Below Average, the staff joked stood around in the dinning room joking around with each other."], "output": "[['Service', 'negative'], ['staff', 'negative'], ['room', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is great and I found it to be fresh and the prices are below to average compared to other Greek Restaurants."], "output": "[['food', 'positive'], ['prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitress was slow and had to ask the kitchen first every time we asked her about anything on the menu."], "output": "[['waitress', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Lovely place with the kind of Chinese food I like -- clean presentation, sizeable menu, and a bit of a French twist."], "output": "[['place', 'positive'], ['menu', 'positive'], ['twist', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The baked goods are all pretty good, though the bagels are a touch stale and dry."], "output": "[['baked goods', 'positive'], ['bagels', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The guacamole was below average compared to any other decent Mexican restaurant."], "output": "[['guacamole', 'negative'], ['Mexican restaurant', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter never came back to check on us or refill coffee, he got one of the orders wrong, and we both left wondering what we were going to eat when we got home."], "output": "[['waiter', 'negative'], ['coffee', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After making reservations 1 month ahead, they sent us to the bar when we arrived, you know to get you out some extra bucks because they had available tables at the moment."], "output": "[['bar', 'neutral'], ['tables', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Enjoyed a very nice Caesar Salad while my wife had arugula and goat cheese."], "output": "[['Caesar Salad', 'positive'], ['arugula', 'neutral'], ['goat cheese', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Wish the Greenwich street location had more seating like their 2nd Ave location, because one invariably leaves it smelling of grease."], "output": "[['seating', 'positive'], ['grease', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["On the menu says Free delivery (Minimun order $10) but I was charged a couple of dollars on both opportunities."], "output": "[['menu', 'neutral'], ['delivery', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I got fed up waiting that I went to get the check and paid for it at the counter where my waitor was busy flirting with the cashier."], "output": "[['waiting', 'negative'], ['counter', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The four of us were seated in the outdoors patio(not requested) and suffered through a muddled menu, indifferent food, a below average waiter, as well as excessive noise, wind and cold."], "output": "[['menu', 'negative'], ['waiter', 'negative'], ['noise', 'negative'], ['outdoors patio', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Overall, cute place with poor service, and even worse food."], "output": "[['place', 'positive'], ['food', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The decor is like a brasserie and has a fairly laid-back atmosphere."], "output": "[['decor', 'neutral'], ['atmosphere', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The SUM IT: Dim sum standard fair, noodles ok, other dishes ok."], "output": "[['Dim sum', 'neutral'], ['noodles', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The only thing I didn't like was the bread that came to the table before dinner."], "output": "[['bread', 'negative'], ['table', 'neutral'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Beautifull people, and a dj that was making me just want to stay and drink more!"], "output": "[['dj', 'positive'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Dinner seating scheme is unintelligible with many tables left empty while guests and servers jab and jostle in the narrow entrance; most of the former not informed of the restaurant policy that allows you to place your name on the dinner list and then return hours later to claim your reservation."], "output": "[['Dinner seating', 'negative'], ['servers', 'negative'], ['dinner list', 'neutral'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The owners Pat and John are very friendly and can often sit and have a beer with you."], "output": "[['owners Pat', 'positive'], ['beer', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had the first pasta listed on the menu and it left me craving the taste again for days after."], "output": "[['pasta', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Coffee served without sugar/milk and took more than 10 min to catch the waiter to ask for it."], "output": "[['Coffee served', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The host greeted us warmly and eagerly and the wait staff was just as receptive."], "output": "[['host', 'positive'], ['wait staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Despite almost flawless service, I had my birthday there for a party of 15 and we were given a private area on the top floor, which was so cold, we had to keep our jackets on throughout the entire meal."], "output": "[['service', 'negative'], ['private area', 'negative'], ['floor', 'neutral'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had dinner here with a few friends recently, and while I must admit that the food and service was okay, the prices simply did not match the environment and cuisine."], "output": "[['dinner', 'neutral'], ['food', 'positive'], ['service', 'positive'], ['prices', 'negative'], ['cuisine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["(they should if you are willing to spend $400 on dinner) if the owner of this restaurant saw how the staff was acting he would fire ALL of them."], "output": "[['dinner', 'neutral'], ['owner', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["while I think the menu could use better appetizers all of the main courses are DELICIOUS- also the service is so much better than the ratings."], "output": "[['menu', 'neutral'], ['appetizers', 'neutral'], ['ratings', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There is a long bar area wide enough to accommodate large crowds, large screen tv's on the walls to view games, but not that do not dominate the atmosphere, and up front there is a large lounge are with several booths and a working fireplace."], "output": "[['crowds', 'negative'], ['atmosphere', 'neutral'], ['lounge', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The decor isn't the best and the place is very modest, but if you're around Ditmars Blvd."], "output": "[['decor', 'negative'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The staff had apparently booked the room for 2 groups with a 30 minute overlap."], "output": "[['staff', 'negative'], ['room', 'neutral'], ['overlap', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Items are a la carte, so if you order lamb chops, that's all you get."], "output": "[['la carte', 'neutral'], ['lamb chops', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Beautiful Chilled seafood platters (and I don't eat shellfish) that would make a Kosher person convert!"], "output": "[['Chilled seafood platters', 'positive'], ['Kosher', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is just ok, not at all worth having to put up with the disgusting staff, the manager/owner in particular."], "output": "[['food', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter was rude to my friend when she asked for a small plate to share an appetizer."], "output": "[['waiter', 'negative'], ['appetizer', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The chips and salsa are good, but the meal is not worth the wait."], "output": "[['meal', 'negative'], ['wait', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Oh, you should have seen the look on the waiter's face when we told him we didn't want any coffee after the meal."], "output": "[['waiter', 'negative'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They expanded the seating with a cozy new back section, added some great new dishes (I had the most fantastic j erk Shrimp and exciting maize crusted salmon) but kept everything that was good (amazing staff and Mac Jack!)"], "output": "[['seating', 'neutral'], ['new dishes', 'positive'], ['j erk Shrimp', 'positive'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service was not great, the wait staff were not clear on the ingredients and or preparation details of the meals."], "output": "[['wait staff', 'negative'], ['ingredients', 'neutral'], ['meals', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food: Bland and unoriginal, despite the creative writing in their menu."], "output": "[['Food', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Upon his arrival the staff checked in his bags and put them in the storage room, but when my bf asked for a check-in ticket, the host refused to give one and threw the bags back at us."], "output": "[['staff', 'neutral'], ['storage room', 'neutral'], ['host', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Odd, traditional and clashing decor will only detract from your experience if the square box layout or perma-draft through the pane glass door doesn't get you first."], "output": "[['decor', 'negative'], ['box', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After all that, it is average food at best with huge bill at the end."], "output": "[['food', 'neutral'], ['bill', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The outdoor garden more than doubles the dining space and is tented in winter."], "output": "[['outdoor garden', 'positive'], ['dining space', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["But even on New Years, when they were busy, the owners took the time out to visit our table frequently, even pouring us drinks herself from her own creations."], "output": "[['owners', 'positive'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was very good but portions were small."], "output": "[['food', 'positive'], ['portions', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Both times, however, I endured lazy service, old bread, overcooked pasta and sour wine w/my meal."], "output": "[['service', 'negative'], ['bread', 'negative'], ['pasta', 'negative'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I ate here once for dinner, and once for brunch, and both times I was very impressed with the quality and uniqueness of the food."], "output": "[['dinner', 'neutral'], ['brunch', 'neutral'], ['quality', 'positive'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Waitress kept trying to get us to order more drinks while apologizing but wouldn't even bring bread to keep us from starving."], "output": "[['Waitress', 'negative'], ['drinks', 'neutral'], ['bread', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They may love the wacky/tacky decore, the overly gracious host, Gus, and his staff, the loads of freebies (oranges, cookies, lollies and wet naps), but the food is just mediocre."], "output": "[['decore', 'positive'], ['staff', 'neutral'], ['lollies', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After some good food and spotty service, my friends and I were surprised to get a bill that had a 20% tip included post-tax."], "output": "[['service', 'positive'], ['bill', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Got 2 apps that were delicious and the bartender made some strong drinks, he could have at least smiled said my girl, but his service was great with our orders."], "output": "[['bartender', 'positive'], ['drinks', 'positive'], ['service', 'positive'], ['orders', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Everyone around me was eating stuff that wasn't on the menu and looked tastier, but the waitress didn't bother to suggest any of these things, even when asked for suggestions."], "output": "[['menu', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene Upstairs in a narrow, handsome but oddly shaped space, this serene, refined restaurant caters to a mostly business-oriented crowd that, auspiciously one presumes, is predominantly Japanese."], "output": "[['Scene', 'neutral'], ['space', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Their dumplings have a LOT of chicken in them."], "output": "[['dumplings', 'neutral'], ['chicken', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere was fun and if you sit by the window, there is a lot of people-watching to be had!"], "output": "[['atmosphere', 'positive'], ['window', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our server spilled a drink on the table cloth and it was cleaned up in an instant, no mess, free drinks to compensate, and left us impressed at how seamlessly this was fixed."], "output": "[['server', 'negative'], ['table', 'neutral'], ['drinks', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After a few minutes, seeing we were without menus, a slightly more pleasant waitress approached us and explained that the manageress had asthma and wasn't in a good mood."], "output": "[['menus', 'neutral'], ['waitress', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In the winter they have the fireplaces working which immediately creates a cozy romantic feel."], "output": "[['fireplaces', 'neutral'], ['feel', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["from the pad thai, pad see yu, to the duck dishes and of course to the ubiquitious thai tea and coffee, Rice delivers good quality, affordable and pretty darn authentic Thai food in a city known for fusing it with every other imaginable combination."], "output": "[['pad thai', 'neutral'], ['duck dishes', 'neutral'], ['ubiquitious thai tea', 'neutral'], ['coffee', 'neutral'], ['Rice', 'neutral'], ['quality', 'positive'], ['Thai food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["after dinner we went downstairs atmosphere was completely different , nice crowd , we stayed there more time than expected."], "output": "[['dinner', 'neutral'], ['atmosphere', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Since the waiter NEVER checked on us during the meal, she never had the chance to ask for hoisin."], "output": "[['waiter', 'negative'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene There's nothing fancy about this joint, where the line for takeout often dwarfs those huddled at the three patio-style tables."], "output": "[['Scene', 'negative'], ['takeout', 'neutral'], ['tables', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Be prepared to wait for a table - go to the upstairs bar and crack open a bottle of wine, or a nice bottle of Italian beer, and get to know everyone else waiting - who knows, you could be sitting with them for dinner!"], "output": "[['table', 'neutral'], ['bar', 'neutral'], ['bottle of Italian beer', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service was punctual, having been asked for our drink orders even before opening our menus."], "output": "[['service', 'positive'], ['drink', 'neutral'], ['menus', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Despite the servers' best intentions, it's easy to feel rushed while perusing the menu -- an awkwardly large blackboard."], "output": "[['servers', 'positive'], ['menu', 'neutral'], ['blackboard', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waitress brought him a regular coke instead of a diet coke, and the salsa had OIL floating at the top."], "output": "[['waitress', 'negative'], ['salsa', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My mouth almost dropped, and for good reason, when the server brought my sandwhich and side of macaroni."], "output": "[['server', 'negative'], ['sandwhich', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service is excellent -- the staff is attentive and the waitress was well-informed about the menu."], "output": "[['service', 'positive'], ['staff', 'positive'], ['waitress', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene With its long zinc bar, plush couches and patterned suede walls, the lounge is a swank spot for midtown's cocktail crowd."], "output": "[['Scene', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have never paid so much at a dinner in my life but we also got very nice 3 bottles of wine."], "output": "[['dinner', 'neutral'], ['wine', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was scrumptious-not the usual wedding."], "output": "[['food', 'positive'], ['wedding', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was not gourmet fare it was perfectly fine burgers, salads and pasta."], "output": "[['food', 'negative'], ['salads', 'positive'], ['pasta', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["DINERS serve better french toast than Balthazar."], "output": "[['DINERS', 'neutral'], ['french toast', 'positive'], ['Balthazar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have dined here for over 20 years and I know the management will NOT compromise the cuisine for any haute trendy fare."], "output": "[['management', 'negative'], ['fare', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We went to Steinhof about a week ago and sat at the bar since the place was packed, but they have the full menu at the bar."], "output": "[['place', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After 2 tries by the waiter to take it away (we hadn't even looked at it yet, we had full beers yet to drink), the manager approached and told us they needed the table for people with reservations."], "output": "[['waiter', 'negative'], ['beers', 'positive'], ['manager', 'negative'], ['reservations', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["He, however, gave great service even though he just brought our food since they didn't have a runner."], "output": "[['food', 'neutral'], ['runner', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After our waitress brought us menus took our drink orders, a diff hostess came over asked us to give up our table."], "output": "[['waitress', 'neutral'], ['drink', 'neutral'], ['hostess', 'negative'], ['table', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["it was really good, but i also mistakenly chose the lobster course as my entre and it turned out to be the same dish as my appetizer (but warmed)."], "output": "[['lobster course', 'negative'], ['dish', 'neutral'], ['appetizer', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After I have my dinner I try to talk to the manager and let him know that he had very good workers and that he should be more considerate with them and the answer that I got from him was (THey can leave I don't care)."], "output": "[['dinner', 'neutral'], ['manager', 'positive'], ['workers', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Mango ice cream or coffee-flavored gelatin finishes the flavorful journey."], "output": "[['Mango ice cream', 'neutral'], ['journey', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Also had to ask the host for our apps becasue our waiter was never around."], "output": "[['host', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Service was a little but flawed, (they brought us beers without the glasses brought the main course out before cleaning off the appetizers) but nothing that would ruin your evening."], "output": "[['Service', 'negative'], ['beers', 'neutral'], ['glasses', 'neutral'], ['appetizers', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["loved everything from the ricotta cheese they put on the table to the osso bucco with risotto, wish i understood their menu its all in italian, not good for a sweed."], "output": "[['ricotta cheese', 'positive'], ['osso bucco', 'positive'], ['risotto', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food was ok, appetizers were expensive compared to the cheap main dishes."], "output": "[['Food', 'neutral'], ['appetizers', 'negative'], ['dishes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They lost our reservations and the manager quickly came over and apologized and then gave us a free round of drinks and free dessert."], "output": "[['reservations', 'neutral'], ['manager', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Wonderful service, not too long a wait for tables, price is right - in a word, go!"], "output": "[['service', 'positive'], ['wait', 'positive'], ['tables', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After our disappointing meal and terrible service we asked to speak to the manager (who was sitting alone having a glass of wine) when we were told he was too busy to speak to us!"], "output": "[['service', 'negative'], ['manager', 'negative'], ['glass of wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene There are exactly three small tables at this tiny hole in the wall, but for food lovers on a budget, it's heaven."], "output": "[['Scene', 'neutral'], ['tables', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There are some unusual items on the menu like the salted popcorn that comes with appetizes and the Yucca potatos that come with some of the meals, foo foo drinks, but overall, I enjoyed everything about this place."], "output": "[['salted popcorn', 'positive'], ['foo foo drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["You dont have to be a connoisseur to know damn well that cutting a steak up just permits the juices to flow out that much quicker, leading to dried out, colder meat."], "output": "[['juices', 'neutral'], ['meat', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["i've been here for brunch twice, and the food's not bad -- was getting sick of teddy's and relish every weekend."], "output": "[['brunch', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["To be fair, I realize I was there for lunch and that the food is probbably better at dinner service when a full kitchen staff has arrived and prepped, but I doubt I'd return to find out with so many other options in the neighborhood i already trust."], "output": "[['lunch', 'neutral'], ['kitchen staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our server was a delight, she helped guide us through the menu with honest insight."], "output": "[['server', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Have the kitchen split as an appetizer its signature cheese and linguini pasta that is curled in a large round cheese bowl that look like a giant candle right at your table."], "output": "[['appetizer', 'neutral'], ['signature cheese', 'neutral'], ['pasta', 'neutral'], ['round cheese bowl', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was no better then average, and the waitress rushed us through our meal in less then an hour ( drinks, appetizer, entree, desert)."], "output": "[['food', 'negative'], ['waitress', 'negative'], ['meal', 'neutral'], ['drinks', 'neutral'], ['appetizer', 'neutral'], ['entree', 'neutral'], ['desert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["And like all McNally hot spots, it crackles with energy, particularly from the groups who gather to share a bite in the bar."], "output": "[['spots', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Olives served at the bar are wonderful."], "output": "[['Olives served', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food An a la carte menu offers specialties like Kobe beef cooked on a hot rock, but the Kaiseki, a traditional multicourse tasting dinner served on gorgeous pottery and porcelain, promises dining adventure."], "output": "[['Food', 'neutral'], ['a la carte menu', 'neutral'], ['multicourse', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I would definately recommend it everyone, even if you aren't a red meat fan, my friend had the pasta and completely cleaned her plate."], "output": "[['red meat', 'negative'], ['pasta', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My advice is to head south to Chinatown where you can get better food at half the price and that communal dining experience too!"], "output": "[['food', 'positive'], ['price', 'positive'], ['dining', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For dinner I had their lobster risotto (phenomenal)."], "output": "[['dinner', 'neutral'], ['lobster risotto', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["26 seats also has the most reasonable prices in NYC, it is a true gem."], "output": "[['seats', 'neutral'], ['prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The wine did not come until we were half way through our entree and the waitress overcharged us by a bottle of wine."], "output": "[['entree', 'neutral'], ['waitress', 'negative'], ['wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Went early with reservation, place was empty, and they squeezed our two top in between other diners at a banquette."], "output": "[['reservation', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While the food was good enough (if old-fashioned - my meal tasted like it was out of a fancy 1950s cookbook, all creamy and rich) the environment was sort of bizarre - rich tapestries, yucky corner-grocer roses on the tables, and a strange '80s mirrored wall, which we sat against at the back of the restaurant."], "output": "[['food', 'positive'], ['meal', 'positive'], ['environment', 'positive'], ['tables', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food is served simply but quickly with a smile."], "output": "[['Food', 'neutral'], ['served', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["from the white sheets that hang when you come into the restaurant, to the gorgeous marble communal table in the center of the bottom floor, to the great atmosphere upstairs at the bar."], "output": "[['white sheets', 'neutral'], ['marble communal table', 'positive'], ['atmosphere', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["fresh fish, huge selection of hot entrees for those that dont eat sushi- and LOTS of rolls and appetizers for sushi lovers."], "output": "[['fish', 'positive'], ['hot entrees', 'positive'], ['rolls', 'positive'], ['appetizers', 'neutral'], ['sushi lovers', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Okay, so the bathroom is a little scary and the milieu brings to mind an old diner or cafeteria, but simply put, the food here is the best."], "output": "[['bathroom', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The presentation of some of the dishes and desserts were great but taste and quality of the food was sub-par especially for the prices that we were paying."], "output": "[['dishes', 'positive'], ['desserts', 'positive'], ['food', 'negative'], ['prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The thin organic burger lacks the flavor of a prime beef patty, requiring add-ons like cheese (cheddar, Swiss or soy-based), bacon (maple-cured or faux) and grilled onions."], "output": "[['thin organic burger', 'neutral'], ['a prime beef', 'negative'], ['cheddar', 'neutral'], ['bacon', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["As well, I haven't eaten animal products in over 6 years and the waiter was not sure which dishes had honey or casien in the food."], "output": "[['waiter', 'negative'], ['dishes', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Also some other appetizers, like the snow crab or the steak, lobster, can't tell which one was better!But would recommend to go with the tasting courses."], "output": "[['appetizers', 'neutral'], ['snow crab', 'neutral'], ['lobster', 'neutral'], ['courses', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food Meat is the name of the game here, especially if you are a fan of mutton: the legendary chop is rightly gamey and thick as a brick."], "output": "[['Food Meat', 'neutral'], ['chop', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have never been to an establishment that boasts traditional French service that basically throws food at you; waiters not only reach across the table but drip wine and water all over their diners."], "output": "[['food', 'neutral'], ['waiters', 'negative'], ['wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had reservations and were seated immediately, got a nice table by the window."], "output": "[['reservations', 'neutral'], ['seated', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the heroes are enough for lunch and dinner."], "output": "[['heroes', 'positive'], ['lunch', 'neutral'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Downstairs, with the lighter menu, and uncomfortable seating, is only worthwhile if people watching and the energy of the bar scene is more important to you than the food."], "output": "[['menu', 'positive'], ['bar scene', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The other steaks on the menu were $30-$40, so the waiter really should have told them the price of the special."], "output": "[['menu', 'neutral'], ['waiter', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The bartender has a nasty attitude, and it took a party of two 1 1/2 hours to get seated while party after party of the hosts 'friends' were given seating immediately."], "output": "[['bartender', 'negative'], ['seating immediately', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Not the best ambiance, but meat that'll make you drool."], "output": "[['ambiance', 'negative'], ['meat', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Forget Brunch- there are usually people waiting outside, although the brunches are delish as well!"], "output": "[['waiting', 'neutral'], ['brunches', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The bar is small so come close to reservation time."], "output": "[['bar', 'negative'], ['time', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Maybe it was because we went during the restaurant week lunch special, but the service was not impressive at all and the food was okay, but not great."], "output": "[['lunch', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The seafood salad was yummy as was the filet of sole stuffed with crabmeat."], "output": "[['seafood salad', 'positive'], ['filet', 'positive'], ['sole stuffed', 'positive'], ['crabmeat', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The french fries are soggy, the service is so/so and while it looks like a cute little homestyle cafe you'd find in SF, the food is below average."], "output": "[['service', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter brought us the desert menu, and when we refused asked if we were really sure we didn't want anything."], "output": "[['waiter', 'negative'], ['desert menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Service during dinner was alright, but one's perception to a restaurant usually starts from the very beginning: the entrance."], "output": "[['Service', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My two best friends took me to Cafe Gray for my birthday and by the end of the dinner, they were apologizing for the poor service and so-so food."], "output": "[['dinner', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["As for dinner, my favorite is the steak frites or the crabcake."], "output": "[['dinner', 'neutral'], ['steak frites', 'positive'], ['crabcake', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In addition to Pizza, Dani has great homemade Ravioli and Maniccoti."], "output": "[['Pizza', 'neutral'], ['homemade Ravioli', 'positive'], ['Maniccoti', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["complaints were shrugged off and service was slow, causing the dinner to go on for over 2 hours."], "output": "[['service', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you go in, make sure to listen to the unbelievably loud microphone that the folks at the counter use to dictate orders to the cooks who stand about two feet behind them."], "output": "[['counter', 'neutral'], ['cooks', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although the decor is lovely as usual, service has detiorated."], "output": "[['decor', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It is a thick drink which almost taste like a cream of rice."], "output": "[['drink', 'negative'], ['cream of rice', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My partner had ordered an appetizer that was no longer available; the waitress did not inform us when reviewing the specials."], "output": "[['waitress', 'negative'], ['specials', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The other food they serve is also very good, but the pizza keeps calling me back!"], "output": "[['food', 'positive'], ['serve', 'neutral'], ['pizza', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The brunch is $12 and includes unlimited pound cake (homemeade) and mimosas, and complimentary OJ."], "output": "[['brunch', 'neutral'], ['pound cake', 'positive'], ['OJ', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter brought the wrong food and charged us for food and drinks we didn't order."], "output": "[['waiter', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While the food was good and reasonably priced, the service was horrible."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I left feeling unsatisfied, except for having a nice chance to people watch in the cozy atmosphere with my over-priced pasta bolognese."], "output": "[['atmosphere', 'positive'], ['pasta bolognese', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Pizza - the only pizza in NYC that should not have additional toppings - the crust tastes like the best, freshly baked bread!"], "output": "[['toppings', 'neutral'], ['crust', 'positive'], ['bread', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After a 21/2 hour lunch in which our displeasure was apparent, we didn't receive an apology or an explanation from the waiter or manager."], "output": "[['lunch', 'neutral'], ['waiter', 'negative'], ['manager', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food wasn't overwhelming, but was very tasty, and the space wasn't overcrowded or obnoxious - the waiters and waitresses were attentive and helpful, but not obtrusive."], "output": "[['food', 'negative'], ['space', 'positive'], ['waitresses', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For entrees, we all had the steak frites and it was to die for."], "output": "[['entrees', 'neutral'], ['steak frites', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We showed up and waited 30 minutes in line 30 minutes to get our drinks -after we asked twice, the service was the worst I've had in nyc."], "output": "[['drinks', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Dining experience begins with cracked, filthy vinyl tile flooring tables so small close together that you couldn't move."], "output": "[['Dining', 'neutral'], ['tile flooring tables', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It's always exciting to see celebrities hiding in the corner banquettes or behind sunglasses at the bar, but the real draw is the chef's short ribs and the volumous wine list."], "output": "[['bar', 'neutral'], ['chef', 'neutral'], ['ribs', 'positive'], ['volumous wine list', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The decor reminds me of Miami nightclubs, and we sat in a cool communal strip, where you share your table with people."], "output": "[['decor', 'positive'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food was cold when it arrived, waitress would vanish for 30 minute periods before reappearing, wrong side dishes were served, meals improperly cooked, and the manager failed to apologize when confronted."], "output": "[['Food', 'neutral'], ['waitress', 'negative'], ['dishes', 'negative'], ['manager', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Last night the wife and I went for the daily 5pm-7pm $18 prix-fixe, which included choices of appetizer (my stuffed mushrooms were delicious), entree (rigatoni for me, chicken for her), and dessert (tiramisu and zeppoles)."], "output": "[['appetizer', 'neutral'], ['stuffed mushrooms', 'positive'], ['chicken', 'neutral'], ['dessert', 'neutral'], ['tiramisu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I like how the ambiance changes from the cafeteria style of lunch to a sit down dinner in romantic lighting."], "output": "[['ambiance', 'positive'], ['style', 'neutral'], ['lunch', 'neutral'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was delicious; the service was a little slow, but it didn't seem TOO bad (maybe becuase of the martinis I consumed while waiting for my table)."], "output": "[['food', 'positive'], ['martinis', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The bagels here are so good that to put cream cheese on them would be an injustice."], "output": "[['bagels', 'positive'], ['cream cheese', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["some old drunk guy who claims he is an American born in France seems to be a regular at the bar, he sat down next to us, listened to our whole conversation then started aggressing us verbally, and the waiter took the longest time to intervene."], "output": "[['bar', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When our first order came, they forgot the torro (which we later learned it was finished for the night."], "output": "[['torro', 'negative'], ['night', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When the pizza arrived it was definitely hot, however the topping was rather soggy from the moisture from the fresh tomatoes."], "output": "[['pizza', 'positive'], ['topping', 'negative'], ['tomatoes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For dinner I order linguine w/ red clam sauce, the pasta was perfect and the sauce was flavorful but the clams tasted funny so I ate around them."], "output": "[['w/ red clam sauce', 'neutral'], ['pasta', 'positive'], ['clam s', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There is no bar so therefore no place to wait except the lounge that was packed so after wondering where to stand the hostess grabbed us."], "output": "[['bar', 'neutral'], ['lounge', 'neutral'], ['hostess', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After ordering our food was brought to our table very quickly despite the huge crowd."], "output": "[['food', 'positive'], ['crowd', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Great inexpensive meal for lunch or for dinner."], "output": "[['meal', 'positive'], ['lunch', 'neutral'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The wine list was small but had a nice variety."], "output": "[['wine list', 'negative'], ['variety', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitress came to our table once for our order, but then we were tended to by who I thought was the hostess."], "output": "[['waitress', 'negative'], ['table', 'neutral'], ['hostess', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They do have a large menu of things along the diner lines, and they go a little gourmet on the brunch omelette fixins/combos."], "output": "[['menu', 'positive'], ['diner lines', 'neutral'], ['gourmet', 'negative'], ['fixins/combos', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Don't go here for sushi, but for one of the other lovely seafood dishes, i."], "output": "[['sushi', 'negative'], ['seafood dishes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["As for the main attraction, the pies are known for their crisp outer edge and gooey middle, and feature the unorthodox layering of sauce over mozzarella."], "output": "[['middle', 'positive'], ['layering', 'neutral'], ['sauce over mozzarella', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiters are nice, but weren't particularly good - waited forever to order and resented not being told that my dinner companion and I had ordered enough for a table of 10 (given the size of the sushi)."], "output": "[['waiters', 'positive'], ['dinner', 'neutral'], ['size', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Try the fresh ricotta cheesecake with a beautifully buttery crust and fresh raspberry topping, or the chocolate and Kahlua mousse, with a gelato-like consistency that pairs wonderfully with vanilla ice cream."], "output": "[['ricotta cheesecake', 'positive'], ['crust', 'positive'], ['chocolate and Kahlua mousse', 'neutral'], ['ice cream', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The crab croquettes were fried and completely lacking in crabmeat, our meat appetizer was dripping with grease and mostly fatty, and our main course was mushy rice drowned in some sauce with the consistency of baby food."], "output": "[['crabmeat', 'negative'], ['meat appetizer', 'negative'], ['main course', 'neutral'], ['rice', 'negative'], ['sauce', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["first of all, the hostess was not pleasant and had a bit of an attitude when seating us."], "output": "[['hostess', 'negative'], ['seating', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Yes, the prices SEEM afordable, but the portions are so small that you end up spending $100+ just to fill 2 people and get a couple drinks."], "output": "[['prices', 'positive'], ['portions', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Portion was just a bit small compare with other restaurant but the price was lower than usualy as well (7."], "output": "[['Portion', 'negative'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Take out and delivery is next door and usually will be better if you are looking to get your food faster."], "output": "[['delivery', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The place was nice and the bartenders were friendly, but the cocktail girl was rude, obnoxious, and over charging all of us."], "output": "[['place', 'positive'], ['cocktail girl', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Service was a treat from my French (Canandian)waiter who knows more about wine than anyone waiting on me in NYC in a long time."], "output": "[['wine', 'positive'], ['time', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We then split some appetizers as the portions are large - the calamari salad was fantastic."], "output": "[['appetizers', 'neutral'], ['portions', 'positive'], ['calamari salad', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I haven't had the pasta, but the appetizers, salads, and entrees (especially the steak and lamb) are extraordinary."], "output": "[['pasta', 'negative'], ['appetizers', 'positive'], ['steak', 'positive'], ['lamb', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We could not believe that the owner only laughed and continued serving him drinks."], "output": "[['owner', 'negative'], ['serving', 'neutral'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Get the Steak, get the Ham Fried Rice, Get the Braised Fish, Get anything Pork and Ham, Appetizers are good too."], "output": "[['Ham Fried Rice', 'neutral'], ['Braised Fish', 'neutral'], ['Pork', 'neutral'], ['Appetizers', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A+  was planning a party for my staff, and was treated rudely by another restaurant when trying to add more people to reservation (a simple no would have worked)."], "output": "[['staff', 'negative'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We waited at the bar for only 10 minutes (we had a reservation) - can't complain about that, the restaurant was full and I enjoyed the lively atmosphere and music."], "output": "[['bar', 'neutral'], ['atmosphere', 'positive'], ['music', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The specials of the day are the way to go."], "output": "[['specials', 'positive'], ['day', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The bright point of dinner was dessrt."], "output": "[['point', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The manager also managed to insult one of my dining partners, even using an expletive to mock his last name when returning his credit card."], "output": "[['manager', 'negative'], ['dining', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Service at the bar was fine, just as you would expect."], "output": "[['Service', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the staff prefers to watch TV in the main dining room infront of their waiting customers then serve their customers."], "output": "[['staff', 'negative'], ['main dining room', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service isn't spectacular and neither is the ambience, but on a lunch hour, all you're looking for is a satisfied stomach."], "output": "[['service', 'negative'], ['ambience', 'negative'], ['lunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service was terrible, we had to wait for everything and ask several of different people for the same thing before we were allowed to be served."], "output": "[['service', 'negative'], ['served', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu goes on to include some of traditional greek favorites but each has a twist that will suprise and delight you."], "output": "[['menu', 'neutral'], ['traditional greek', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you're tired of the long waits for table at nearby place, then head to Moutarde for a delicious meal that won't keep you waiting."], "output": "[['meal', 'positive'], ['waiting', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I even overheard the one waiter argue to the host about that and then they conveniently switched to speaking Spanish."], "output": "[['waiter', 'negative'], ['host', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I don't claim to know enough about authentic Italian cuisine but the food is good, provided they have the menu item you order."], "output": "[['Italian cuisine', 'positive'], ['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Romano family is very hands on with the father supervising the kitchen and Santo, the son, running the room with a high degree of personal attention."], "output": "[['Romano family', 'positive'], ['kitchen', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This seems to be a big hit and draws a large crowd, so be prepared for a wait."], "output": "[['crowd', 'positive'], ['wait', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Finally got our food after waiting a long time for oysters, doesn't take that long to shuck 'em, the place isn't that big, and it was OK."], "output": "[['food', 'neutral'], ['time', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Gobo's scallion pancakes are a bit dry, and the beet salad is low on beets, but the majority of dishes, especially those showcasing vegetables, are delicious in their simplicity."], "output": "[['scallion pancakes', 'negative'], ['beet salad', 'negative'], ['beet s', 'negative'], ['majority', 'neutral'], ['dishes', 'positive'], ['showcasing vegetables', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu is varied but I think it is the chicken which they do best as."], "output": "[['menu', 'neutral'], ['chicken', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We wouldn't have had a problem with this if the burger had actually been tasty but even with the foie-gras, cheddar cheese, apple smoked bacon, leaks, etc."], "output": "[['burger', 'negative'], ['cheddar cheese', 'neutral'], ['apple smoked bacon', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Since it's a small place, it's best to get there early for dinner as the wait can be quite long if you don't make a reservation."], "output": "[['wait', 'negative'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The prices are decent for this type of food and dining experience."], "output": "[['prices', 'positive'], ['food', 'neutral'], ['experience', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The manager finally came by to apologize and offered to give us a greek salad on the house."], "output": "[['manager', 'positive'], ['greek salad', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The was very little if any seasoning on the meat, and the outsiside has nice sear marks and a rich taste."], "output": "[['seasoning', 'neutral'], ['meat', 'neutral'], ['sear marks', 'positive'], ['taste', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There are times when there is a long wait at lunch so be safe and make a reservation."], "output": "[['wait', 'negative'], ['lunch', 'neutral'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["She asked for only a glass of water, and the waitress refused, to her face, twice."], "output": "[['glass of water', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the waitress was not attentive at all and we had to keep getting the attention of the water servers to get more drinks."], "output": "[['waitress', 'negative'], ['servers', 'neutral'], ['drinks', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Stay away from the two specialty rolls on the menu, though- too much avocado and rice will fill you up right quick."], "output": "[['menu', 'neutral'], ['rice', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although the food was good, the way our waiter treated us was so rude and bad-mannered that it almost ruined our night and he even asked us to give him a better tip!!!"], "output": "[['food', 'positive'], ['waiter', 'negative'], ['tip', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Its great for people who want to try Korean food, but can't understand the servers or the menu on 32nd St."], "output": "[['Korean food', 'positive'], ['servers', 'neutral'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Went to dinner on a Friday night and the place was packed and hot."], "output": "[['dinner', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Philippe should re-train their wait staff to communicate with one another and better orchestrate the timing of food service."], "output": "[['wait staff', 'negative'], ['food service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This is a busy spot from 1130 AM to 130 PM M-F but you never have to wait more than 5 minutes for a table, unless you have a large party, thanks to fast and friendly service provided by the waitstaff and kitchen."], "output": "[['service', 'positive'], ['waitstaff', 'neutral'], ['kitchen', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I ordered the plane no fuss SALMON and it was honestly the best salmon EVER."], "output": "[['plane', 'neutral'], ['salmon EVER', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I noticed many of the other comments had negative things to say about the service and food - my thoughts and suggestions are: eat at the bar to avoid a rude waiter or bad service here and Artisanal's reputation is based on the cheese, get the CHEESE and not the steak or whatever."], "output": "[['food', 'neutral'], ['bar', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["it is a small take-out style restuarant but they have a few tables."], "output": "[['take-out', 'neutral'], ['tables', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food The meal begins slowly, with a plate of excellent garlic knots."], "output": "[['Food', 'negative'], ['meal', 'negative'], ['garlic knots', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have been there for dinner and the food is even more spectacular."], "output": "[['dinner', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Aside from the service being slow, the place was packed w/ a good crowd and music was amazing."], "output": "[['service', 'negative'], ['place', 'positive'], ['crowd', 'positive'], ['music', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["And the paella for two is actually too much food for two!"], "output": "[['paella', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have been going to this restaurant for years, in the past the service was average and the food inconsistant."], "output": "[['service', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Overall, I would rather go to a chain coffee house up the street for the same priced coffee, but a much more relaxing atmosphere, and no one forgetting my order."], "output": "[['priced coffee', 'negative'], ['atmosphere', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food The French-Belgian menu is small, but everything on it is satisfyingly savory, from a simple pot of mussels in a choice of sauces (beer and bacon, creamy mushroom, or white wine and garlic broth), to beef stewed with beer and prunes; from a juicy croque monsieur and beyond."], "output": "[['Food', 'negative'], ['French-Belgian menu', 'negative'], ['pot', 'positive'], ['mussels', 'positive'], ['beef stewed with beer', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["From the space shuttle trip entrance to mars, to the molecular regenerator exit to earth, it was all an exquisite dining experience."], "output": "[['space', 'neutral'], ['dining experience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["However, you're bothered by things like sub-par food (don't get the cajun fries), waiters who hate you and anything that looks like you, close proxmitity with strangers, and cheap talking and singing skelletons, do NOT go."], "output": "[['cajun fries', 'neutral'], ['waiters', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Asked for recommendations, waitress said read everything on the menu which already wasn't to unique."], "output": "[['waitress', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had the tasting menu -- which was not a meal!!!"], "output": "[['menu', 'positive'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The un-customer-friendly manager comped us NOTHING for waiting for room temperature food, so we stopped ordering drinks."], "output": "[['manager', 'negative'], ['waiting', 'negative'], ['room temperature food', 'neutral'], ['drinks', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We told the waitress we'd like the fries hot with our main courses but she only ordered more once the rest of the food had arrived so we didn't get them until we were half way through."], "output": "[['waitress', 'negative'], ['fries', 'neutral'], ['main courses', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["hard to work a buzz with the server taking so long between every round, but worth trying the signature african rum cocktail and happily surprised they had our favorite white - sancerre by the glass at this japanese restaurant."], "output": "[['server', 'negative'], ['glass', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have been a vegetarian for over 10 years, I do eat cheese but when a person is on a diet it is so hard to enjoy PIZZA."], "output": "[['cheese', 'neutral'], ['PIZZA', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter brought the wrong dinner for me (shrimp provencal instead of the salmon) but then comped my meal with no question."], "output": "[['waiter', 'negative'], ['dinner', 'negative'], ['salmon', 'neutral'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Def, Def try the green papaya salad for an appetizer."], "output": "[['green papaya salad', 'positive'], ['appetizer', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Service was slow and our drink order took forever (and the place wasn't crowded)."], "output": "[['Service', 'negative'], ['drink', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["One friend's pizza arrived about 15 minutes before the rest of our meals (the remainder of our entrees did not even arrive at the same time), and our waiter half-heartedly apologized for the delay while rolling his eyes."], "output": "[['meals', 'neutral'], ['waiter', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Minutes turned into an hour-long wait with non-existent standing room."], "output": "[['wait', 'neutral'], ['non-existent', 'neutral'], ['room', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Desserts were pleasent enough, if not trying way to hard on presentation, lacking portions and interest."], "output": "[['Desserts', 'neutral'], ['portions', 'negative'], ['interest', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When my friend's chicken salad sandwich arrived, she noticed a nice crust, and it wasn't part of the bread."], "output": "[['chicken salad sandwich', 'neutral'], ['crust', 'positive'], ['bread', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": [") other food is served in too-small portions, but at least it leaves room for dessert."], "output": "[['portions', 'negative'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When I asked the waitress she told me it was because I ordered pancakes."], "output": "[['waitress', 'negative'], ['pancakes', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After reading other reviews I was expecting poor service and ambience but was pleasantly surprised by our more than helpful waiter."], "output": "[['service', 'negative'], ['waiter', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu was filled with of course the standard sushi fair, but the real gem was the unuusal and creative combinations of sushis and sauces and other ingredients they had as well."], "output": "[['menu', 'neutral'], ['sushis', 'positive'], ['sauces', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When we went, the wait staff did not talk to us about any of the specials/the menu etc and handed us our bill while we were still eating."], "output": "[['wait staff', 'negative'], ['specials/the menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The raspberry/marscapone-stuffed pancakes are so divine it's actually worth putting up with the rude and incompetent service."], "output": "[['raspberry/marscapone-stuffed pancakes', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There are deli items and cookies as well, but I just can't tear myself away from the bagels!"], "output": "[['items', 'positive'], ['bagels', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Those waiting inside to get a free table and waitresses carlessly walking by only served to make matters worse."], "output": "[['waiting', 'neutral'], ['table', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Downstairs is an entirely different scene: There's a fireplace with sofas and comfy chairs set around it, and a bar off to the side."], "output": "[['Downstairs', 'positive'], ['chairs', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I understand its a very busy night of the week but it is unacceptable that I was hung up on by the hostess twice (I also called back and she refused to answer the phone for 15 minutes) and was told that I should have picked up my food instead of having it delivered."], "output": "[['hostess', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The attention to detail whether it's decor or service or menu made us feel fortunate to be part of the Camino Sur dining experience."], "output": "[['decor', 'positive'], ['service', 'positive'], ['menu', 'positive'], ['dining', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Service was ok, took a while to order even drinks."], "output": "[['Service', 'positive'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If I had a car, I'd go there more often, but I live 35 blocks away and don't trust carrying pastries home on the bumpy crowded B41 busline."], "output": "[['pastries', 'neutral'], ['busline', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu is Prix Fixe, so be prepared to spend at least $60 per person, but it is Well worth itsuperb food."], "output": "[['menu', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The deli-diner-soul-food menu, featuring everything from matzo balls to barbecued chicken and ribs to 10-ounce burgers, is available until late."], "output": "[['menu', 'positive'], ['barbecued chicken', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Nice ambience and bar while waiting for a table."], "output": "[['ambience', 'positive'], ['bar', 'positive'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Go for brunch - it's sure to please for those who like their eggs spicy!"], "output": "[['brunch', 'neutral'], ['eggs', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have had occasion to go to this establishment several times - a few times for dinner, and once for Saturday dimsum, and I must say that while I felt slightly intimidated by the fact that I was one of the few non chinese speakers there, the food was rather good."], "output": "[['dinner', 'neutral'], ['dimsum', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Particularly good is the chicken verde burrito with a refreshingly spicy salsa that avoids the heat overkill."], "output": "[['chicken verde burrito', 'positive'], ['overkill', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene There are two distinct personalities to the place: The loud, seemingly always-crowded bar with hanging paper decorations and dim lighting, and the two main dining areas, where the noise level and decor is notably more subdued."], "output": "[['bar', 'negative'], ['two main dining', 'neutral'], ['noise level', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Try a traditional latin favorite like Arroz con pollo (yellow rice w/ chicken red bell pepper) but meat lovers should definitely not miss out on the churrasco!"], "output": "[['latin', 'neutral'], ['yellow rice w/ chicken red bell pepper', 'positive'], ['meat', 'positive'], ['churrasco', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service was okay, fast seating (for two), looked like a group nearby had been there a long time."], "output": "[['seating', 'positive'], ['time', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service was warm, but it took forever to get the check."], "output": "[['service', 'positive'], ['check', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had to ask for water even after we were asked what type we preferred, and then the busboy spilled it while he was pouring it out."], "output": "[['water', 'neutral'], ['busboy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This newly opened restaurant is another one of those Indian places that has a hugely promising menu and a greatly disappointing food."], "output": "[['menu', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you go for lunch as we did, get there when they open as seating is fairly limited."], "output": "[['lunch', 'neutral'], ['seating', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["too bad that the 2 sushi chefs have become a bit too busy to chat away with the guests at the counter, but they try and hey, we are here for the food !!!"], "output": "[['counter', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["as an appetizer we had some amazing citrus shrimp and for our main courses we each got a pasta dish."], "output": "[['appetizer', 'neutral'], ['citrus shrimp', 'positive'], ['pasta dish', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Their food is delicious and they send you cut up oranges to cleanse your palate after dinner which is a very nice touch."], "output": "[['food', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Each table has a pot of boiling water sunken into its surface, and you get platters of thin sliced meats, various vegetables, and rice and glass noodles."], "output": "[['pot of boiling water', 'neutral'], ['platters', 'neutral'], ['meats', 'neutral'], ['vegetables', 'positive'], ['rice', 'neutral'], ['glass noodles', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Not the best ambience and the service is sometimes just mediocre, but the quality of the food is incredible."], "output": "[['ambience', 'negative'], ['service', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The hostess was inefficiently seating people and disappeared for minutes at a time, letting the line grow to 15+ people waiting to put their names on the list."], "output": "[['hostess', 'negative'], ['seating', 'neutral'], ['waiting', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene Vintage suitcases and black-and-white photos of old ocean liners evoke the Golden Age of travel in the front bar, where a worldly clientele sips cocktails around a flickering faux fireplace."], "output": "[['Scene', 'neutral'], ['bar', 'neutral'], ['clientele', 'positive'], ['cocktails', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Bar has, french fries, bunch of different vegs and fruits, sushi, ribs (not great, wait for the waiters that come around with the meat)."], "output": "[['Bar', 'neutral'], ['french fries', 'neutral'], ['vegs', 'positive'], ['ribs', 'neutral'], ['waiters', 'neutral'], ['meat', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After ordering my dinner and having it come to the table totally wrong, the manager argued with me over whether my meal was correct or not, and further argued that the mushrooms in my dish were really the eggplant that I ordered."], "output": "[['dinner', 'neutral'], ['manager', 'negative'], ['mushrooms', 'negative'], ['dish', 'neutral'], ['eggplant', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The decor is sparse and elegant, the service warm (though my waitress was occasionally difficult to find), and the sushi fresh."], "output": "[['decor', 'positive'], ['service', 'positive'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had the pasta special, which had tremendous amount of seafood."], "output": "[['pasta special', 'neutral'], ['seafood', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu does not have much and what we did have - original pizza with pepperoni and sausage was not so great."], "output": "[['menu', 'neutral'], ['pepperoni', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["(The band is positioned in front of the windows, in a space roughly the size of a living room."], "output": "[['band', 'positive'], ['space', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Their seafood is fresh-- have their fried soft-shell crab, or their whole fish with red chiles and basil."], "output": "[['seafood', 'positive'], ['fried soft-shell crab', 'neutral'], ['whole fish with red chiles', 'neutral'], ['basil', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["i've had better mashed potatoes from a box, and the vegetables were soaked in oil."], "output": "[['mashed potatoes', 'positive'], ['box', 'neutral'], ['vegetables', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Their Brunch must be good too if it's Sangria included."], "output": "[['Brunch', 'positive'], ['Sangria', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": [") Service was good not great, waiters stood around,didn't ask how everything was."], "output": "[['Service', 'positive'], ['waiters', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I've eaten dinner here quite a few times and the sushi/sashimi has been very fresh on every occasion."], "output": "[['dinner', 'neutral'], ['sushi/sashimi', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Compared to New York prices, the menu seems reasonably priced (it is not cheap like Fridays, but is reasonable compared to top quality food experiences in this city)."], "output": "[['prices', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Adding insult to injury, the waiter had to ask for the wine bottle by number (where are we?"], "output": "[['waiter', 'negative'], ['wine bottle', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food Nothing makes for better bar snacks than this down-home Southern menu."], "output": "[['Food', 'neutral'], ['bar', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["With only 2 tables occupied in the whole place, the waitress spent her time behind the bar and only came to help us when we got up and asked her to."], "output": "[['tables', 'neutral'], ['waitress', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Half way through the meal my husband had to go to the bar to order his own beer, since the server never came back."], "output": "[['meal', 'neutral'], ['bar', 'neutral'], ['beer', 'neutral'], ['server', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Additionally the bar upstairs is picturesque and spacious, even though the techno music is horrible."], "output": "[['bar', 'neutral'], ['techno music', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For entrees, we had the chicken with string beans, steamed stripe bass with ginger and soy sauce, fried rice with chives (which I LOVED!"], "output": "[['entrees', 'neutral'], ['chicken with string beans', 'neutral'], ['steamed stripe bass with ginger and soy sauce', 'neutral'], ['fried rice', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our Peruvian waiter was very nice, and the food was ok, but forget about ordering an expensive bottle of wine there."], "output": "[['waiter', 'positive'], ['food', 'positive'], ['bottle of wine', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We sat at the bar so the service wasn't too bad."], "output": "[['bar', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The dessert was as good as the waiter said it would be."], "output": "[['dessert', 'positive'], ['waiter', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was very good but the portions are pretty small, so while the prices are low, the place is not quite a bargain it seems to be."], "output": "[['food', 'positive'], ['portions', 'negative'], ['prices', 'positive'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This time, I ordered the tasting menu and the only two dishes I enjoyed were the squab and the sorbet."], "output": "[['menu', 'positive'], ['dishes', 'positive'], ['sorbet', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The only complaint I have is that the tables for 2 along the booth are very close together so it wasn't as romantic a dinner as we wanted but all in all, we were in our own world, more like in heaven."], "output": "[['tables', 'neutral'], ['booth', 'neutral'], ['dinner', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although almost the entire back room had tables available, the owner made people wait to be seated while dragging waitresses around by the arm and loudly telling them they were doing things wrong."], "output": "[['tables', 'neutral'], ['owner', 'negative'], ['waitresses', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It is a nice diner atmosphere, they have booths all around and a couple of middle tables."], "output": "[['diner atmosphere', 'positive'], ['tables', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There's no bar, only beer and wine, and you're likely to be annoyed by unruly Park Slope offsprings, so come late and enjoy the smart wine list."], "output": "[['bar', 'neutral'], ['wine list', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The clientel, however, make it a scene for creative, talented people--inlcuding a soon-to-be-famous theater director who used to waitress there!"], "output": "[['clientel', 'negative'], ['waitress', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were not offered bread and the host did not apologize until we asked for another update 45 minutes later."], "output": "[['bread', 'neutral'], ['host', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Looks like an ordinary pizza joint from the outside, but the back room has excellent, cheap Italian food, and the owners and workers couldn't be nicer."], "output": "[['pizza', 'negative'], ['Italian food', 'positive'], ['owners', 'positive'], ['workers', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["To make matters worse, the waitress followed us out, and demanded that we leave a better tip."], "output": "[['waitress', 'negative'], ['tip', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The bartender had offered us ONE beer on the house for our troubles."], "output": "[['bartender', 'positive'], ['beer', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the service was somewhat spotty, but we were rewarded with free drinks and the waiters were all sweet and lovely, genuinely french-speaking but not snooty!"], "output": "[['service', 'negative'], ['drinks', 'positive'], ['waiters', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The final blow was when the waiter brought us the check before we had even finished dessert--never mind that the only reason we were taking a long time to finish the meal was because of the extreme delay in the service of our food."], "output": "[['waiter', 'negative'], ['dessert', 'neutral'], ['meal', 'neutral'], ['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Even the expensive (11-20$) fru-fru drinks lacked flavor and quality ingredients."], "output": "[['drinks', 'negative'], ['flavor', 'negative'], ['ingredients', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["SKIP THIS PLACE FOR LUNCH, BUT MAKE SURE YOU GET THERE FOR DINNER."], "output": "[['LUNCH', 'negative'], ['DINNER', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the roll was great as usual but the salmon was old the tuna did not look good at all."], "output": "[['roll', 'positive'], ['tuna', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Corner Bistro, despite the hoopla and critical praise, is nothing more than a burger joint with long lines."], "output": "[['burger', 'neutral'], ['lines', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After dinner our waiter takes the bill and the manager tells him to clear our table so that we could leave."], "output": "[['dinner', 'neutral'], ['waiter', 'negative'], ['bill', 'neutral'], ['manager', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We orderes and our food took about 1 hour to get it, after the long wait."], "output": "[['food', 'neutral'], ['wait', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Went on a 3 day oyster binge, with Fish bringing up the closing, and I am so glad this was the place it O trip ended, because it was so great!"], "output": "[['Fish', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Where else can you go to get freshly made Italian food at ridiculously low prices?"], "output": "[['food', 'positive'], ['prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiters are very kind and helpful, and I regularly get something on the house - coffee, dessert or a drink."], "output": "[['waiters', 'positive'], ['coffee', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While the appetizers I sampled (gnocchi; shrimp wrapped in coconut or somesuch) were not so impressive (the gnocchi portion is meager and overpriced), my table was 100% satisfied with their entrees too."], "output": "[['appetizers', 'negative'], ['table', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was good, the service was fine, and the place has a lot of visual atmosphere, but I would not go back unless I was stuck eating with someone I didn't want to listen to."], "output": "[['place', 'neutral'], ['atmosphere', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although our waitress was pleasant and accomdating, the overpriced food was quite the opposite."], "output": "[['waitress', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The hostess did not verify/review the menu prices with us nor did they inform us of the logistics of the brunch."], "output": "[['hostess', 'negative'], ['brunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For every simple winner like Newport steak with pistachio salsa verde, there's an overconceived braised lamb with cinnamon, olives and cilantro or a meek salt- and pepper-crusted shrimp with citrus slices."], "output": "[['steak with pistachio salsa', 'neutral'], ['braised lamb', 'positive'], ['olives', 'neutral'], ['citrus slices', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The front desk person gave us quite a struggle to find a good seat."], "output": "[['person', 'negative'], ['seat', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When I read some of the reviews in this section, I am not sure if they had diner in the same restaurant and also I would not be suprise if they decided to have their Branzino well done with butter on the side."], "output": "[['diner', 'neutral'], ['butter', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Nothing too special about the location or the atmosphere, but DAMN, the pizza is good."], "output": "[['atmosphere', 'negative'], ['pizza', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["At our table we didn't get any bread until 30 minutes into the seating, which may I emphasize the waiter took really long to come to our table, about 20 minutes."], "output": "[['seating', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["- , the desserts are sinful, the moroccan hospitality evident in the wait staff's friendliness and there is an overall ambience that makes you want to stay all night!"], "output": "[['desserts', 'positive'], ['wait staff', 'positive'], ['ambience', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Enjoy a drink at the bar over fresh shucked oysters."], "output": "[['drink', 'positive'], ['bar', 'neutral'], ['oysters', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Be warned that this place can get pretty crowded, though the $3 bloody mary's at the bar and the killer DJ make the wait more than bearable."], "output": "[['bar', 'neutral'], ['killer DJ', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I did not like the place because: -it took the waiter over 20 min to take our order and then over an hour until we got our food."], "output": "[['waiter', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Then the waiter came back for our food order at 10, and we hadn't received our drinks yet."], "output": "[['waiter', 'negative'], ['food', 'neutral'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter did not take a drink order from us."], "output": "[['waiter', 'negative'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["OUr waiter was a little confused about how to serve champagne."], "output": "[['waiter', 'negative'], ['champagne', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although there was a 30 min wait I didn't mind because I was able to sit at the bar and have some drinks while talking to the beautiful, charming hostess there."], "output": "[['bar', 'neutral'], ['drinks', 'neutral'], ['hostess', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Also, be wary of what time of the day you go; around dinnertime, the restaurant becomes a jungle of diners and hustling waitresses."], "output": "[['diners', 'neutral'], ['waitresses', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the food isn't spectacular, but I have yet to be disappointed in anything I've been served, and there's a definite attempt by the kitchen to keep the menu fresh and interesting."], "output": "[['food', 'negative'], ['kitchen', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["All in all this is a place that attracts people of all races, colors and economic status, as I noticed suited clients as well as hippies, or soiled clothed laborers who stop in for a quick good meal or a business lunch or dinner."], "output": "[['meal', 'positive'], ['business lunch', 'neutral'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When one purchases a bottle of wine, it's fairly common practice for a server to come by and refill your glass, but not the case here; 2."], "output": "[['server', 'negative'], ['glass', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We went here for lunch a couple of weeks ago on a Saturday, and I was thoroughly impressed with the food."], "output": "[['lunch', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["At the end of your meal they bring a fortune cookie and an orange or pineapple slice."], "output": "[['meal', 'neutral'], ['cookie', 'positive'], ['orange or pineapple slice', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter was less then welcoming when taking our drink orders (apparently he doesn't like beer or milkshakes)."], "output": "[['waiter', 'negative'], ['drink', 'neutral'], ['beer', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It was absolutely delicious to the point where i went back and asked for a variety plate They were so nice to accomodate me and gave me almost everything on the menu to taste from."], "output": "[['plate', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The only downer was the fruit fondue desert from the prie fixe menu wasn't as good as it looked (the chocolate was runny), and the wait between our salad and main course was too long."], "output": "[['fruit fondue', 'negative'], ['prie fixe menu', 'neutral'], ['wait', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Flavors range from standards to hard-to-find Italian options, like tiramisu, hazelnut and zuppa inglese."], "output": "[['Flavors', 'negative'], ['tiramisu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you're looking for barbeque like Dallas BBQ (soaked in sauce from a bottle, generic, homogeneous food) then you won't like Blue Smoke."], "output": "[['food', 'positive'], ['Smoke', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We would have to flag down the bored looking wait staff to refill our tea."], "output": "[['wait staff', 'negative'], ['tea', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I HAVE HAD LOBSTER IN FINISTIST RESTAURANTS IN MANHATTAN AND I NEVER TASTED IT AS GOOD AS RIZZO."], "output": "[['LOBSTER', 'neutral'], ['RIZZO', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food OK (DRY fried chicken, overcooked pork, great mac and cheese) I dont understand the high rating."], "output": "[['fried chicken', 'negative'], ['pork', 'negative'], ['mac and cheese', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A collection of stormy sea paintings and two mermaid figureheads hoisting lights above the bar set a lulled maritime mood."], "output": "[['sea paintings', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Not just that tapas was small portions (duh) but, for example, $10 piggy-back dates only came with 6 little appetizers."], "output": "[['tapas', 'neutral'], ['portions', 'negative'], ['appetizers', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The california roll was too big and overfilled with imitation crab meat, so it's not the best I had."], "output": "[['california roll', 'negative'], ['crab meat', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Their delivery of fresh hot pizza."], "output": "[['delivery', 'neutral'], ['pizza', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Try Le Madeleine for a similar price but much better food."], "output": "[['price', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is excellent so long as you like Austrian cuisine."], "output": "[['food', 'positive'], ['cuisine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It's a place for the owner staff's friends, so if you're not one of them, you're in for a wait."], "output": "[['owner staff', 'negative'], ['wait', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The ensuing dinner was definitely worth the wait; I'll be dreaming about chef Jodi Williams' extraordinary fried squash blossoms for a long time."], "output": "[['ensuing dinner', 'positive'], ['chef', 'neutral'], ['fried squash blossoms', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Besides the price, here are some other annoyances: bleaching the floors during the dinner and automatically charging you 20% gratuity on your credit card without your knowledge."], "output": "[['price', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["All my favorite dim sum, especially the flaky pastry that contains either curry chicken or roast pork."], "output": "[['pastry', 'positive'], ['curry chicken', 'neutral'], ['roast pork', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the pizza is a no-brainer, and the dinners are drastically underrated."], "output": "[['pizza', 'negative'], ['dinners', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I felt that the meat had little flavor(ribs and chicken) and as result I had to use A ALOT of their bbq sauce (which is good) and the ribs were not falling of the bone."], "output": "[['meat', 'neutral'], ['flavor', 'negative'], ['bbq sauce', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the hostess really underestimated the wait time for outdoor seating and never apologized, and our waitress was apathetic and unattentive."], "output": "[['hostess', 'negative'], ['outdoor seating', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have been coming here for several years and know that the staff and bartender would be there with my favorite drinks and dishes I like to eat and drink on any given night."], "output": "[['staff', 'neutral'], ['drinks', 'positive'], ['dishes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The music is a little bit louder, but the food is excellent."], "output": "[['music', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["During the weekend nights, the crowd is full of 20 somethings (in which a few look much younger) and is almost Coyote Ugly style where ladies are dancing all over the bar."], "output": "[['style', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["not having a menu was rather strange at first but the food was superb."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["decent, if greasy, fishsticks, but served on a mound of soggy fries that could feed about 5-6 people!"], "output": "[['served', 'neutral'], ['fries', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter returned and said the bartender refused to take my drink back because there was nothing wrong with it and I would have to pay for it."], "output": "[['waiter', 'neutral'], ['bartender', 'negative'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was certainly fine, although prices were high by any standard, with dinner for four being over $300 without drinks."], "output": "[['prices', 'negative'], ['dinner', 'neutral'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Not only did we have to flag the waiter down every time for every course or request, but they spilled our drinks twice all over the table - and once was hot tea."], "output": "[['waiter', 'negative'], ['drinks', 'neutral'], ['tea', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter didn't know the menu or the ingredients."], "output": "[['waiter', 'negative'], ['menu', 'neutral'], ['ingredients', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Service was a tad spotty, but the food was VERY good and the noise never detracted from the dining experience."], "output": "[['Service', 'negative'], ['food', 'positive'], ['experience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": [") My date and I were greeted by the host and informed there would be a slight wait."], "output": "[['host', 'positive'], ['wait', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The restaurant was recently taken over by new managment and, having eaten there under the prior management, I can say that the quality of the dishes has improved."], "output": "[['management', 'neutral'], ['quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Try the stir fried cube steak, shabu sahbu, or the Oden, or anything else you want to try on the menu."], "output": "[['stir fried cube steak', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have a litany of complaints -- being over-charged for wine that I didn't order, shady waiters, so-so food that arrived at the table luke warm, main course portion sizes barely large enough to be appetizer sizes, lack of fabulosity that Mr."], "output": "[['wine', 'neutral'], ['waiters', 'negative'], ['food', 'negative'], ['table', 'neutral'], ['main course portion sizes', 'negative'], ['appetizer', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you've been out partying and have a yen for quality Korean food at 3:00am, there's a table waiting for you at Kang Suh Restaurant."], "output": "[['Korean food', 'positive'], ['table waiting', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After 10 minutes of waiting, he finally returned to the table and snootily explained to us that the wine he had opened was actually better and more expensive (not yet on the menu, of course), but he would charge us the price of the bottle we had originally ordered."], "output": "[['waiting', 'neutral'], ['table', 'neutral'], ['wine', 'negative'], ['menu', 'neutral'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["sushi portions were bigger than most places and service was average, far better options available in the area."], "output": "[['sushi portions', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food There's no need to slump into a well-known comfort zone of teriyaki and udon."], "output": "[['comfort', 'positive'], ['teriyaki', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The staff didn't even tell us (college kids) about the prix-fixe special, but the pair of older adults sitting next to us took advantage."], "output": "[['staff', 'negative'], ['prix-fixe special', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The ceviche had way too much onion which masked the flavor of the fish."], "output": "[['ceviche', 'neutral'], ['onion', 'negative'], ['flavor', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Wonton dough filled with gently steamed and seasoned pork are common but add this amazing soup to the wonton, seal it and serve it steaming hot and the dumpling becomes new again."], "output": "[['seasoned pork', 'neutral'], ['soup', 'positive'], ['dumpling', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In Short Take a quick trip to Maine at this classic lobster pound where the outdoor picnic tables are the prime seats in summertime."], "output": "[['lobster', 'positive'], ['outdoor picnic tables', 'neutral'], ['seats', 'positive'], ['summertime', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have been dining at Narita for 6 years and have thoroughly enjoyed every meal."], "output": "[['dining', 'neutral'], ['meal', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene Behind the often-fogged windows at this small restaurant is a homey atmosphere, full of smiling employees and Filipino families crowded around simple red tables."], "output": "[['Scene', 'neutral'], ['atmosphere', 'positive'], ['employees', 'positive'], ['tables', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The prices were very resonable when you don't factor in the cost of beer (which seemed to be on the high side)."], "output": "[['prices', 'positive'], ['cost of beer', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The $5 menu does have smaller portions, and I found the ravioli dish to be not too much better than a can of Chef Boyardee."], "output": "[['menu', 'neutral'], ['portions', 'negative'], ['ravioli dish', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["To enhance the dining experience, there is a live jazz band, which further isolates you from the world outside the gates."], "output": "[['dining', 'positive'], ['live jazz band', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The tasting menu was delivered at a break-neck pace, leaving no time to enjoy the wine or even digest the food."], "output": "[['menu', 'positive'], ['wine', 'positive'], ['food', 'positive'], ['pace', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although the tables may be closely situated, the candle-light, food-quality and service overcompensate."], "output": "[['tables', 'negative'], ['candle-light', 'positive'], ['food-quality', 'positive'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The pasta, chicken and veal dishes are one of the best values in town, almost always served with bread and salad (and pasta for the meat dishes)."], "output": "[['chicken and veal dishes', 'positive'], ['bread and salad', 'neutral'], ['meat dishes', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We first got a table next to a VERY loud speaker and had no view, but the waiter was kind enough to move us when we asked."], "output": "[['table', 'neutral'], ['waiter', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The portions are big so you can split an appetizer."], "output": "[['portions', 'positive'], ['appetizer', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["But, quickly all would realize that most items on the menu are grease-laden, and the portions are so big that you'd get tired of the flavors before you finish half a plate."], "output": "[['menu', 'neutral'], ['portions', 'positive'], ['flavors', 'negative'], ['plate', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had the 5 course tasting menu and had the waiter select a perfect bottle of wine to go with our selections."], "output": "[['waiter', 'neutral'], ['bottle of wine', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The daily fresh fish can be remarkably good, served in a variety of combinations, ranging up to the omakase chef's choice dinner."], "output": "[['daily fresh fish', 'positive'], ['chef', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I arrived with one other person at ~8:30 on a Wed night -- the hostess was very kind and showed me the reservation computer which showed that they were completely booked."], "output": "[['hostess', 'positive'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Meals not served at once and service was inattentive and forgetful."], "output": "[['Meals', 'neutral'], ['served', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My friends and I made plans to go out on Friday for some good latin food and decide to go to Yuca Bar since we've been there for brunch and we love it, we figured dinner has to be good."], "output": "[['latin food', 'positive'], ['brunch', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Yet, it still took over an hour for us to get our food, which was alright; my nephew said his tortellini tasted like Costco, they even forgot to bring my beverage."], "output": "[['food', 'negative'], ['beverage', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Fish and tomato sauce both have great flavors and the dishes are under $20."], "output": "[['Fish and tomato sauce', 'neutral'], ['flavors', 'positive'], ['dishes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They have recently fired their staff and brought in new people who dont even know how to serve a beer, I might add you are on average paying $6."], "output": "[['staff', 'negative'], ['beer', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It was well past 8 pm when they finally got us the check, and we asked for free rounds of champagne to compensate for the poor service (since the wine dinner had started, and were denied."], "output": "[['champagne', 'neutral'], ['service', 'negative'], ['wine dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Inside as we waited momentarily for our table, the bartender made light conversation as he made our drinks."], "output": "[['table', 'neutral'], ['bartender', 'positive'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Don't know about the rest of the food, but the burgers are one of New York's hidden treats."], "output": "[['burgers', 'positive'], ['treats', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["we told our waiter to make five selections for each of us, and he decided instead to charge us for each glass separately instead ($80 instead of $20)."], "output": "[['waiter', 'negative'], ['glass separately', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A friendly staff works the room, delivering favorites like crisp, crackling spring rolls and shredded pork rolls wrapped in rice paper."], "output": "[['staff', 'positive'], ['room', 'neutral'], ['spring rolls', 'positive'], ['pork rolls', 'positive'], ['rice paper', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The place is a little over-priced for brunch but it is a nice restaurant so that was expected Food (i had the omelette with cheddar, mushrooms and herbs), service, coffee, atmosphere were all fantastic."], "output": "[['place', 'negative'], ['brunch', 'neutral'], ['cheddar', 'neutral'], ['mushrooms', 'neutral'], ['herbs', 'neutral'], ['service', 'positive'], ['coffee', 'positive'], ['atmosphere', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The only other negative, we found the waiter to be slightly pompous, and when I asked him some very basic wine questions, he was lost."], "output": "[['waiter', 'negative'], ['wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Not only did the food take an eternity to come out; but the waiter never checked in, explained the delay for the food, or refreshed our drinks."], "output": "[['waiter', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My experience at the The Pearl Room was like no other place in Bay Ridge, you walk into a dimly lit atomsphere and a well dressed crowd."], "output": "[['Pearl Room', 'neutral'], ['crowd', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food's ok here, but AVOID this place for brunch, dinner or any other time!"], "output": "[['food', 'positive'], ['brunch', 'neutral'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For dessert go with the flan as the chocolate cake was not too moist."], "output": "[['dessert', 'neutral'], ['the chocolate cake', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Unfortunately, service was slow and when our server noticed we had not received our entree he comp'ed us two delightful margaritas - AND charged us only for appetizers , thereby cutting our bill in half."], "output": "[['service', 'negative'], ['server', 'negative'], ['bill', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The owner promised my party a table and bottle service and took care of it immediately as we all arrived."], "output": "[['owner', 'positive'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["You wanna wait a hour for a cramped table to eat mom's macaroni and cheese?"], "output": "[['wait', 'neutral'], ['table', 'negative'], ['cheese', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food When the counter guy asks, Would you like better fries with that?"], "output": "[['Food', 'neutral'], ['counter', 'neutral'], ['fries', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Please, please don't waste your money (85 cents for a slice of tomato on your overpriced sandwich."], "output": "[['slice of tomato', 'neutral'], ['sandwich', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went there for lunch a couple of times but whenever I went there (even though we pinpointed our order on menu), waitress messed up our order and they never said sorry."], "output": "[['lunch', 'neutral'], ['menu', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["What made our visit extra special was that we didn't have room for dessert at the end of our meal (the pasta was so amazing we just kept eating), our waiter suggested we come back after our show, which we did."], "output": "[['dessert', 'neutral'], ['pasta', 'positive'], ['waiter', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the place had open doors and windows and a very relaxed, candle-lit type of atmosphere."], "output": "[['place', 'positive'], ['open doors', 'neutral'], ['atmosphere', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Two minutes later, the waitress said we NEED the table, you can not have the appetizer that you ordered."], "output": "[['waitress', 'negative'], ['appetizer', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Grabbed a lunch here on a weekday and it was reasonably priced, well-portioned and generally well-prepared."], "output": "[['lunch', 'neutral'], ['priced', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Fortunately, unlike many Mexican joints, the abundance of cheese never tastes greasy, and portions are filling but not overwhelming."], "output": "[['Mexican', 'neutral'], ['abundance of cheese', 'negative'], ['portions', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Thought I didn't have reservations, the hostess politely informed me that it would be a 45 minute wait and we were actually seated in 40."], "output": "[['reservations', 'neutral'], ['hostess', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter never once came back to our table to ask how our meal was OR if we needed another drink."], "output": "[['waiter', 'negative'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Their desserts were limited - I mean REALLY limited to 2 items (nothing like the online menu)."], "output": "[['desserts', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I haven't eat a lamb chop as delicious as that,the salads are really nice dressed with lemon and extra virgnin olive oil."], "output": "[['lamb chop', 'positive'], ['salads', 'positive'], ['lemon', 'neutral'], ['extra virgnin olive oil', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food and our server(s) were very very excellent, prices were very good, but she's just left a horrible taste in our mouth both times."], "output": "[['food', 'positive'], ['server', 'positive'], ['prices', 'positive'], ['taste', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My one recommendation is try not to geta seat by the door, there is a large brass bell that people like to whale on when they leave the place."], "output": "[['seat', 'negative'], ['door', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although all of the menu items and specials always sound tantalizing, we often end up ordering the pastaless eggplant lasagna and the gnocchi souffle."], "output": "[['menu items', 'positive'], ['specials', 'positive'], ['pastaless eggplant lasagna', 'neutral'], ['gnocchi souffle', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the service was very slow and his knowledge of the menu wasnt that good."], "output": "[['service', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Unfortunately, that lunch can take a loooooong time as the waiters seem to forget food orders, forget drink orders, and forget to refill water glasses."], "output": "[['lunch', 'neutral'], ['waiters', 'negative'], ['water glasses', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Second, the value was great; after ordering a ton of food and several drinks, the bill still came to less than $40 a person (though I suspect that the nice manager might have given us a few freebees!"], "output": "[['value', 'positive'], ['food', 'positive'], ['bill', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Great place to get a good fulfilling meal but do not go for ambience or service."], "output": "[['fulfilling meal', 'positive'], ['ambience', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I would feel different if we were just drinking water and eating cake but we had 20 people drinking multiple overpriced beverages AND one friend had called ahead of time to find out about the cake and no one ever picked up the phone."], "output": "[['water', 'neutral'], ['beverages', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["All the dishes that we had at our table were consistently good, although not great (nor poor, either)."], "output": "[['dishes', 'positive'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Though the celery root soup was super yummy - everything else was an overpriced letdown- the plates come out looking like it's the depression era."], "output": "[['celery root soup', 'positive'], ['plates', 'positive'], ['era', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We waited an hour for our appetizers, (I suspect the waitress forgot to put in our order because the restaurant was not busy) and then the entrees came at the same time!"], "output": "[['appetizers', 'neutral'], ['waitress', 'negative'], ['entrees', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After they were done poking and prodding our food, the waiter took it right from their table and tried to give it to us."], "output": "[['food', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["On top of it all, I was with family from out of town and the only reason I took them there was because a friend had mentioned the place and Coffee Shop had a little wait."], "output": "[['place', 'neutral'], ['Coffee', 'neutral'], ['wait', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The portion size / price combo makes it expensive if you're really hungry, but we went for a late dinner."], "output": "[['portion size / price combo', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Still the bill was close to $300(with 1 bottle of lower-priced wine)."], "output": "[['bill', 'neutral'], ['wine', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We have been waiting for months for a 8pm reservation at this very average restaurant."], "output": "[['waiting', 'negative'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["bartenders management and at first were a bit disappointed with food."], "output": "[['bartenders management', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They've got some of the best french toast you'll ever eat for Sunday brunch, and while their dinner menu hasn't changed much in the past few years, their food is reliable and they I always find something new in their chicken or fish specials, which are usually prepared with a red or white wine-based sauce."], "output": "[['brunch', 'neutral'], ['dinner menu', 'neutral'], ['food', 'positive'], ['chicken', 'positive'], ['white wine-based sauce', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Plus, everything comes in small to average portions, so the next time you get a sushi craving, I don't recommend that you go here."], "output": "[['portions', 'negative'], ['sushi', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["He prepares the most authentic dishes, I guess that's why the bar is usually filled with Japanese."], "output": "[['dishes', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you hate waiting for a table, then get take-out just around the corner next door."], "output": "[['waiting', 'negative'], ['table', 'neutral'], ['door', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I've eaten at this Zen Palate location a few times, and each time have had the same reaction- I feel the food's sub-par, but decide to give it another chance and order something else."], "output": "[['location', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My next thought was god i could use a few drinks and a bathroom."], "output": "[['drinks', 'negative'], ['bathroom', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had to try the sweet tea, which was served in a plastic cup at room temperture."], "output": "[['sweet tea', 'positive'], ['served', 'neutral'], ['cup', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had to chase down our waitress for the food and the bill."], "output": "[['waitress', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the sushi is so-so, the 70s orange-themed atmosphere is 2000ish, and there is no reason for the staff's attitude."], "output": "[['atmosphere', 'neutral'], ['staff', 'negative'], ['attitude', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I found that the food variety was great, and the waitress was very accommodating to my vegan boyfriend describing all items' ingredients and how you may request more of what YOU like, creating a unique experience."], "output": "[['food variety', 'positive'], ['waitress', 'positive'], ['ingredients', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Be careful with the waiting list- the hostess skipped over our party on the list as we sat waiting for a table, for over an hour."], "output": "[['hostess', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["we literally waited for over 45 minutes to finally getting our sushi which was pretty simple rolls."], "output": "[['sushi', 'positive'], ['rolls', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were rudely told by the waiter that chips are only available at the bar."], "output": "[['waiter', 'negative'], ['chips', 'neutral'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["You cannot beat having the waiter spooning butter over your steak before you are served!!"], "output": "[['waiter spooning butter', 'positive'], ['steak', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My roommate says she has had good food here at night, at the bar."], "output": "[['food', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service was average and the tables are really close together (but who cares when the food is this good)."], "output": "[['tables', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the setup is cool with pool table and chill area in front and dining on side and back."], "output": "[['area', 'positive'], ['dining', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It's a quiet crowd but if you just want to relax, get a bottle of wine and some great tapas, this is the place."], "output": "[['bottle of wine', 'neutral'], ['tapas', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I ordered a dirty martini that was not dirty at all-and when I asked the waitress to make it dirtier, instead of reshaking/making it at the bar, she broght me over some olive juice in a cup!?"], "output": "[['martini', 'negative'], ['waitress', 'neutral'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Small dishes, a bit pricier than you'd pay in Miami or LA, but the atomsphere is on the sexy side (however pared down) and its cozy."], "output": "[['dishes', 'negative'], ['Miami', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I go generally with one friend but on occasion have popped in with more, if a table is not possible, as they are booked solid every night, well, the food and service is just as over-the-top amazing at the bar or in the lounge as it is in the dining room."], "output": "[['table', 'neutral'], ['service', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["You can get a completely delish martini in a glass (that's about 2 1/2 drinks) for $8."], "output": "[['martini in', 'positive'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The collard greens were tasty, but in too much liquid that made it seem more like a soup."], "output": "[['collard greens', 'positive'], ['soup', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The greens were ok, but probably were too salty for those who don't hail from the south (I do) or don't have access to authentic southern cooking."], "output": "[['greens', 'neutral'], ['southern cooking', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Mussels in bread pot, homemade ravioli filled with things like swordfish and truffles, orange-ginger shrimp and pizzas from a wood-burning oven in back are all recommended."], "output": "[['Mussels in bread pot', 'positive'], ['homemade ravioli filled', 'positive'], ['swordfish', 'neutral'], ['truffles', 'neutral'], ['pizzas', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The bar area was fairly crowded but service remained friendly and efficient."], "output": "[['bar area', 'negative'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["However, our one and only complaint was when I received my drink I gave my coupon to our waiter, he returned minutes later to tell me that it could not be used in the dining room, only at the lounge or at the bar."], "output": "[['drink', 'neutral'], ['waiter', 'negative'], ['dining room', 'neutral'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere is classy with salsa music in the background."], "output": "[['atmosphere', 'positive'], ['salsa music', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Tasting menu a mixed bag: lobster soup amuse with grapefruit intriguing, but marred by excess bitterness as prepared."], "output": "[['menu', 'positive'], ['mixed bag', 'neutral'], ['lobster soup', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere is nice - it's all dark wood with the bar in the front."], "output": "[['atmosphere', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The New Prospect Cafe pretends to be fancy and the prices indicate fancy, but the food is mediocre at best and the service is terrible."], "output": "[['prices', 'positive'], ['food', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Even some of the staff that was working that night was served their dinner before my table got our dinner entrees."], "output": "[['staff', 'negative'], ['dinner entrees', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When we sat down - our waiter did not know what to recommend - neither food nor wine."], "output": "[['waiter', 'negative'], ['food', 'neutral'], ['wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food The fun factor is high on the menu of experimental, multi-ethnic shared plates."], "output": "[['Food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had reservations, and so did the strangers, and yet the management claimed the other tables were reserved."], "output": "[['reservations', 'neutral'], ['management', 'negative'], ['tables', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["And Mondays fajita are half price all night."], "output": "[['fajita', 'neutral'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After being treated like we were at Nobu by the hostess, our waitress brought us our check before we even asked for it and denied us a 2nd round of drinks because."], "output": "[['hostess', 'negative'], ['waitress', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There is always a fun and friendly crowd at the bar, mostly locals, if you just want to come by for happy hour."], "output": "[['crowd', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Unfortunately, the food along with the unhelpful service doesn't make up for the atmosphere."], "output": "[['food', 'neutral'], ['service', 'negative'], ['atmosphere', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I did not find the wait staff to rude at all, how involved do you really want them in your meal right?"], "output": "[['wait staff', 'positive'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In April, the service was fair but again, the food was at best only warm."], "output": "[['service', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["not only were we waiting for half an hour with reservations, once we got seated we waited another 15+ minutes for the waiter to come and take out drink menu."], "output": "[['waiting', 'neutral'], ['reservations', 'neutral'], ['menu', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The wine list is good, and overall it is not too expensive, though, and the atmosphere is very dark and brick-covered, much like any damp basement."], "output": "[['wine list', 'positive'], ['atmosphere', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The cranberry sauce was unrecognizable in taste."], "output": "[['cranberry sauce', 'negative'], ['taste', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter was attentive but not overbearing and gave good recommendations on the cocktails."], "output": "[['waiter', 'positive'], ['cocktails', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["All in all, I would not recommend for the food or drinks but I guess I can't expect better for the prices."], "output": "[['drinks', 'negative'], ['prices', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": [") Scores of employees walking around, but no one seems to clear a plate or offer more drinks."], "output": "[['employees', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Within 10 minutes of being seated at our table, the hostess asked us if we could move."], "output": "[['seated', 'neutral'], ['hostess', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["before we could say anything, one waiter picked it up while another brought a knife to our table on a platter."], "output": "[['waiter', 'negative'], ['table', 'neutral'], ['platter', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Low-fat and low-carb options (such as flatbread) lure in health-conscious diners, while everyone else can sink their teeth into warm, crispy baguettes piled with mesquite chicken or smoked turkey, Philly cheese steaks and more."], "output": "[['options', 'positive'], ['mesquite chicken', 'neutral'], ['smoked turkey', 'neutral'], ['Philly cheese steaks', 'neutral'], ['diners', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Order a beer and then sit and wait for the steamy, salty soup dumplings that burst with a snap."], "output": "[['beer', 'neutral'], ['soup dumplings', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["He may be a little hard to take, but he knows how to run a kitchen and put together a creative menu."], "output": "[['kitchen', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you can get a corner table you can see the entire room while eating in elegance."], "output": "[['corner table', 'neutral'], ['room', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were seated next to some obnoxious women who bogarted the server's time and attention, so he bought us drinks."], "output": "[['server', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you order the platters all of your typical Indian side items are included so it is a good value."], "output": "[['platters', 'neutral'], ['Indian side items', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Eventually another waiter cleaned up the table and allowed us to sit there."], "output": "[['waiter', 'positive'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I liked the overall setting A LOT and it was only improved by the fact that our waiter was pleasant and attentive even though we only ordered entrees (no drinks, no appetizers, no coffee)."], "output": "[['setting', 'positive'], ['waiter', 'positive'], ['drinks', 'neutral'], ['appetizers', 'neutral'], ['coffee', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the space is very comfortable - they don't rush you - you don't have a server holding your bill in their hand asking if you'd like anything else."], "output": "[['space', 'positive'], ['bill', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Its not kept frozen, but close to room temperature so you get the real taste of the ice cream and not just the ice."], "output": "[['taste', 'positive'], ['ice cream', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["THE SERVICE WAS CIVILIZED INFORMATIVE;WE NEVER FELT RUSHED , EVEN THOUGH PATRONS WERE WAITING TO BE SEATED."], "output": "[['SERVICE', 'positive'], ['WAITING', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had to wait 30-45mins after we were already seated to get our orders in, waited what felt like an hour to get our food, was not given utensils with our dinner (had to wait for that too), and had the wrong dessert brought to our table and never remedied even after we brought it to the waiter's attention."], "output": "[['food', 'neutral'], ['dinner', 'neutral'], ['dessert', 'negative'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Sure, you can sit back and watch the celebrites pour in, or sit at the bar, and watch true masters create old world sushi, and new world rolls."], "output": "[['bar', 'neutral'], ['rolls', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["None of us were able to get drinks in a timely fashion, and the bartender was EXTREMELY rude to us."], "output": "[['drinks', 'neutral'], ['bartender', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For appetizers, we shared summer rolls and spring rolls - they were good, not great."], "output": "[['appetizers', 'neutral'], ['spring rolls', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["He is a gracious chef who comes to the table and greets the guests."], "output": "[['chef', 'positive'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Just look at all those people waiting outside to feat in an unadorned space of cramped shared tables?"], "output": "[['waiting', 'neutral'], ['space', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The appetizers were tasty and the snail ravioli quite adventurous, however the main courses were quite bland and even though the steak was featured with mustard sauce it really was just plain stone ground mustard."], "output": "[['appetizers', 'positive'], ['snail ravioli', 'positive'], ['mustard sauce', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There is no pretention here, no tofu, no foie gras, and no vegi burger, just a straight forward burger with great meat cooked perfectly."], "output": "[['tofu', 'neutral'], ['foie gras', 'neutral'], ['meat', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["On the menu, unusual offerings like mango salad, Kashmiri chicken and whole fish cooked in mustard sauce refute the strip's infamous reputation for one-sauce-fits-all cooking."], "output": "[['menu', 'neutral'], ['mango salad', 'positive'], ['Kashmiri chicken', 'positive'], ['mustard sauce', 'neutral'], ['cooking', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I asked one waitress if I could change tables and she didn't say no outright."], "output": "[['waitress', 'negative'], ['tables', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene Though this looks like any other sushi counter, with purple vinyl booths and a koi pond in the small dining room, there are glimpses of superiority."], "output": "[['sushi counter', 'neutral'], ['dining room', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I highly recommend the potato and cheese pierogis and the polish kielbasa entreesbut the real stars on the menu are the sides."], "output": "[['potato and cheese', 'positive'], ['polish kielbasa', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have to say the seating at the bar and dining areas are very nice and the service is exceptional."], "output": "[['seating', 'neutral'], ['dining areas', 'positive'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitstaff is nice, but is pushy and seemed irritated when we did not order an a la carte side vegetable (we already had a cheese plate, appetizers and ordered 2 entrees)."], "output": "[['la carte side vegetable', 'neutral'], ['appetizers', 'neutral'], ['waitstaff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The East Side is a little fancier and larger, but still a Wonderland with the same great food, scones, cakes and more - a dinner menu and drinks like Mar-TEA-nis."], "output": "[['food', 'positive'], ['scones', 'positive'], ['cakes', 'positive'], ['drinks', 'neutral'], ['Mar-TEA-nis', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It's also a good place to unwind after dinner and have some coffee and cake."], "output": "[['dinner', 'neutral'], ['coffee', 'positive'], ['cake', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menus took about 15 minutes to come, the menu were already set up for Valentines day the salad was good my dinner was a soup of about 2 or three shrimps, THAT'S IT!"], "output": "[['menus', 'neutral'], ['day', 'neutral'], ['dinner', 'neutral'], ['soup', 'neutral'], ['shrimps', 'neutral'], ['salad', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For as busy as this place is, the owner could afford to hire additional servers."], "output": "[['owner', 'neutral'], ['servers', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Just make sure you make reservations a few days in advance because there aren't a lot of tables."], "output": "[['reservations', 'neutral'], ['tables', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is good and cheap BUT the attitudes of the bartender and wait staff are almost unbearable."], "output": "[['food', 'positive'], ['bartender', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Well, literally 7 minutes later we were being served dinner, with no apologies from the server who was too scared to come to our table."], "output": "[['served dinner', 'neutral'], ['server', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is average, at best (I have been repeatedly underwhelmed by the mediocre fare) and the service is only good if Elaine is within range."], "output": "[['fare', 'negative'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["overall the food we ordered (pancit luglug, chicken adobo, romy's ribs, lumpia shanghai, a bowl of green soup that resembles the polyjuice potion harry potter drank) was not screaming with taste."], "output": "[['food', 'negative'], ['ribs', 'neutral'], ['potion', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["She walked away in a huff, and had the BUSBOY pass on the same message: you can't order coffee because you've already paid (have these people never heard of someone changing their mind?"], "output": "[['BUSBOY', 'negative'], ['coffee', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Their pre-theater prix fixe was a cut above the rest: appetizer stand out - Duck breast with mushroom canelloni."], "output": "[['appetizer', 'positive'], ['Duck breast with mushroom canelloni', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food The menu seems quirky, but upon a closer look ingredients are familiar and made into appealing combinations, with influences from Maine to the Mediterranean."], "output": "[['Food', 'positive'], ['menu', 'positive'], ['ingredients', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["However, the wait was worth it, the food was just great - make sure you have the tuna."], "output": "[['wait', 'positive'], ['food', 'positive'], ['tuna', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["THE DECOR HAS BEEN UPDATED TO A FULL BLOWN RESTAURANT BUT THE QUALITY AND THE QUANTITY HASN'T CHANGED."], "output": "[['DECOR', 'positive'], ['QUALITY', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Wine has had C-Tails at the bar(SUPRISE!!!)"], "output": "[['Wine', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The only downfall was that our appetizer never showed up, we were apologized to, and it wasn't on our bill, but we also didn't get the jumbo shrimp we were all craving."], "output": "[['appetizer', 'negative'], ['bill', 'neutral'], ['jumbo shrimp', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our cocktails were ok but at ridiculous dance club prices."], "output": "[['cocktails', 'positive'], ['prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Meanwhile, the bartender continued to pour champagne from his reserve after we had finished our bottle and we enjoyed an amuse of turnip soup with pureed basil, gratis."], "output": "[['bartender', 'positive'], ['champagne', 'neutral'], ['turnip soup with pureed basil', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It's listed under appetizers, but it's definitely filling enough to have as a meal."], "output": "[['appetizers', 'neutral'], ['meal', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our dinner took over two hours because of the slow service."], "output": "[['dinner', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Service is wonderful- I've sat there for over 3 hours at dinner and never felt rushed to leave."], "output": "[['Service', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My first and LAST visit included a waiter telling me We're casual- pour your own wine and then handing me a check with a place for the Captain's tip."], "output": "[['waiter', 'negative'], ['wine', 'neutral'], ['Captain', 'neutral'], ['tip', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In my experience, Olympic Flame, a traditional NYC Greek coffee shop, offers good value for one's money in terms of food cost but passable to rude service, depending on who you get."], "output": "[['food cost', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The price is cheap - 5 dumplings for $1."], "output": "[['price', 'positive'], ['dumplings', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the waiters had a really hard time remembering to bring drinks, and when they did they were not what was ordered."], "output": "[['waiters', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Curries are another menu highlight, with several choices including Pa Nang with coconut milk, lemongrass leaves, onions and peppers, and Gang Paa with hot and spicy chili sauce."], "output": "[['menu', 'positive'], ['Nang with coconut milk', 'neutral'], ['onions', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["brunch menu had nice variety to choose from, miniblueberrrymuffins better than some bakeries, included in their price mimosa/bloody mary's were nice."], "output": "[['brunch menu', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I was intimidated by the menu - which is entirely in Italian, and the wine list - which strictly lists Italian wines, but my waiter - Nathan - was quick to help."], "output": "[['menu', 'positive'], ['wine list', 'positive'], ['Italian wines', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["cause, I was bored by the club scene and too overdressed for the local bar."], "output": "[['club scene', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had a burger which was great and my wife had a steak."], "output": "[['burger', 'positive'], ['steak', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had a decent chicken sald w olives, red peppers, and croutons."], "output": "[['chicken sald w olives', 'positive'], ['red peppers', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Anyhow, there were a lot of Japanese people seated at the bar, eating chatting up the chefs, surely that's a good sign of authentic sushi."], "output": "[['seated', 'neutral'], ['bar', 'neutral'], ['chefs', 'positive'], ['sushi', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene Bo Ky is a Vietnamese no-frills noodle shop with some 30 different soups."], "output": "[['noodle', 'neutral'], ['soups', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food was good but portions were quite tiny."], "output": "[['Food', 'positive'], ['portions', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was awesome if you can deal with wait staff who you can hardly ever find."], "output": "[['food', 'positive'], ['wait staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were able to reserve a spot at the chef tasting bar with Morimoto who actually called in sick that night, but we were still charged full price."], "output": "[['bar', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["At the end of our meal, I approached the waitress and asked that they not charge us for the $25 appetizer."], "output": "[['meal', 'neutral'], ['waitress', 'negative'], ['appetizer', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the Sangria is sooo perfect, I can't have one glass, the Chicken is always moist and delicious served in a portion I have yet to ever completely finish."], "output": "[['Sangria', 'positive'], ['glass', 'neutral'], ['Chicken', 'positive'], ['portion', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Bar BQ will knock your socks off with every entree (pulled pork and the ribs -- go full rack, kid, it won't do you wrong) and the homey taste of the sides (love that slaw, them beans, and all that tater salad) matches up perfectly."], "output": "[['Bar', 'neutral'], ['ribs', 'neutral'], ['rack', 'neutral'], ['sides', 'positive'], ['salad', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My mom I take it to go eat in our car across the street--the BBQ Pork Rice another favorite, Duck Soy sauce chicken rice!"], "output": "[['BBQ Pork Rice', 'positive'], ['Duck Soy sauce chicken rice', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Try the Bocadillos to start and don't forget to order a Mojito from the bar (they're the best!"], "output": "[['Mojito', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The crowd doesn't disappoint: A well-heeled, fashionable clientele packs the polished-wood-and-glass-partitioned space, settling into one of two dining rooms, or the bar, which is located at the farthest corner from the entrance."], "output": "[['crowd', 'positive'], ['dining rooms', 'neutral'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Good brunch menu - it was hard to make a decision between the breakfast tacos, huevos rancheros, and salads on the menu although our waiter was happy to rank menu items upon our request."], "output": "[['brunch menu', 'positive'], ['salads', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Orange Valve is probably the best bar that I've been to in a while."], "output": "[['Orange Valve', 'neutral'], ['bar', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The wait staff were incredibly attentive, though as a warning, if you like wine, but also a little privacy, this might not be a good idea, since they have the tendency to hover a bit."], "output": "[['wait staff', 'positive'], ['wine', 'positive'], ['privacy', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although the prices are kind of high for lunch the atmosphere is nice."], "output": "[['prices', 'negative'], ['atmosphere', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I used to eat there two meals a day until my company moved to stupid Madison avenue (UGH, nasty food for rip off tourist price!)"], "output": "[['meals', 'neutral'], ['food', 'negative'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Special touch -- my dessert plate had Happy Birthday drizzled in chocolate."], "output": "[['dessert plate', 'positive'], ['chocolate', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Another quick tell-tale sign is the furniture at the bar and the seating tables."], "output": "[['furniture', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I've had the same steak at Peter Lugers for double the price."], "output": "[['steak', 'neutral'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The staff has been nice, but they seemed really stressed and the unisex bathroom needs to be cleaned more often."], "output": "[['staff', 'positive'], ['bathroom', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["YYMV, we visited for Restaurant Week so the quality of the food may have been below normal standards because of the crowds."], "output": "[['quality', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When we asked the waiter for water - he gave us dirty looks and it took at least 15 minutes to get it."], "output": "[['waiter', 'negative'], ['water', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Many meals were delivered by two servers, besides having a waiter to oversea the process."], "output": "[['meals', 'positive'], ['servers', 'neutral'], ['waiter', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The best thing on the menu was probably the creamed spinach side and that's saying alot for a steakhouse."], "output": "[['menu', 'neutral'], ['creamed spinach', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We picked on a bunch of different appetizers as dinner and everything was yummy."], "output": "[['appetizers', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Unfortunately it gets very crowded on the weekends, so if you don't mind dining at the bar you can skip the wait for a table."], "output": "[['dining', 'negative'], ['wait', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Chef Richard is always eager to please, and will be happy make something special 'off the menu' if you ask."], "output": "[['Chef', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The chick pea/eggplant dish was quite bland, and the saag paneer was a huge disappointment--more like some kid's worst experience of creamed spinach with tofu-like cheese."], "output": "[['chick pea/eggplant dish', 'negative'], ['saag paneer', 'negative'], ['spinach', 'negative'], ['tofu-like cheese', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I took a friend for dinner for his birthday here and the food was amazing."], "output": "[['dinner', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Not in the mood for sushi, try the fantastic okonomiyake."], "output": "[['sushi', 'negative'], ['okonomiyake', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["This coffee shop offers many varieties of food."], "output": "[['coffee', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I thought the service was a little slow and not attentive enough for the price but other than that I'll be back when I can afford to spend $60 on dinner!"], "output": "[['price', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The birthday girl's dessert included a candle the staff came by with birthday wishes."], "output": "[['dessert', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Some of the things we ordered were The Duck Spring Rolls, Lobster and Goat Cheese Quesadillas, Wild Mushroom Ravioli and the concluded dinner with a steak special that was out of this world."], "output": "[['Duck Spring Rolls', 'neutral'], ['Lobster and Goat Cheese Quesadillas', 'neutral'], ['Wild Mushroom Ravioli', 'neutral'], ['concluded dinner', 'positive'], ['steak special', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The downside is that perhaps due to rice's eclectic nature, the chef has trouble cooking any single type to perfection."], "output": "[['rice', 'neutral'], ['chef', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My friends and I dropped by on a Sunday, and there was absolutely NO SERVICE (the supposed only female bartender even told us there was no one else but her, and given that there were people in there waiting to dine and drink, that was ridicoulas!"], "output": "[['SERVICE', 'negative'], ['dine', 'neutral'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We loved the recommendation for the wine, and I think the eggplant parmigiana appetizer should become an entree."], "output": "[['wine', 'positive'], ['eggplant parmigiana appetizer', 'neutral'], ['entree', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Other than that, for $30 person you will have one of the best meals and that included a bottle of wine."], "output": "[['meals', 'positive'], ['bottle of wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I realized that you dont have to wait hours and pay crazy prices for food."], "output": "[['prices', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For dinner, I love the churrasco and halibut with of course black beans and yellow rice."], "output": "[['dinner', 'neutral'], ['churrasco', 'positive'], ['halibut with of course black beans', 'positive'], ['rice', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Was there for dinner last night, and the food was great."], "output": "[['dinner', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu sounded good but the grilled eggplant roll was oversauced with a pile of mint, pork chop was leathery, and everything just tasted wrong."], "output": "[['menu', 'neutral'], ['grilled eggplant roll', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Service is coddling and correct and there's no sense of hurry, so diners linger over a cheese course or a round of liqueurs."], "output": "[['Service', 'positive'], ['cheese', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["USC has a cold smoker and smoked the avocado in order to make the dish more complex."], "output": "[['avocado', 'neutral'], ['dish', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}