{"task_type": "generation", "dataset": "mams", "input": ["The food was served promptly but the meal wasn't rushed - we had plenty of time to enjoy the appetizers and our entrees as well as sit and chat while finishing up our drinks even after we paid."], "output": "[['food', 'neutral'], ['served', '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": ["When I got home, there was a message on the machine because the owner realized that our waitress forgot to charge us for our wine."], "output": "[['owner', '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": ["The Scene Shun Lee Palace is popular with midtown locals, possibly because the upscale room means you can impress a client and have Chinese for lunch at the same time."], "output": "[['Scene', '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": ["To both our surprise, this inquiry was interpreted as a personal offense by the waiter who told my wife to leave the store if she didnt want the pastries."], "output": "[['waiter', 'negative'], ['pastries', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 find their menu offerings at other places for better qualities and lower prices."], "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": ["Been here a few times and food has always been good but service really suffers when it gets crowded."], "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": ["It's sad that everything about this place was great (even the service and decor) except for the steak."], "output": "[['service', 'positive'], ['decor', '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": ["to be honest we only had drinks and appetizers downstairs as we were there for a collegues leaving drinks but the staff was very friendly (typical aussies) and the food i did have was pretty darn good."], "output": "[['appetizers', 'neutral'], ['staff', '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": ["The brasserie-style menu remains relatively unchanged, featuring classic bistro choices like frisee salad with bacon, blue cheese and a poached egg, steak tartare, moules and steak frites, and various burgers and sandwiches."], "output": "[['brasserie-style menu', 'neutral'], ['bistro choices', 'positive'], ['frisee salad with bacon, blue cheese', 'neutral'], ['a poached egg', 'neutral'], ['steak tartare', 'neutral'], ['moules', 'neutral'], ['steak frites', '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": ["we all liked the brunch items we had but when we later asked if the chips were supposed to come with the meal, the waitress explained it away by saying sometimes they forget instead of apologizing and offering something extra."], "output": "[['brunch', 'positive'], ['chips', '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": ["Appetizers are the safest bet, including a bountiful calamari plate or the appropriately earthy mushroom polenta."], "output": "[['Appetizers', 'positive'], ['bountiful calamari plate', 'neutral'], ['appropriately earthy mushroom polenta', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 had better burgers and fries at the local dinner in my neighborhood: 3 guys dinner on 96th and Madison Avenue."], "output": "[['burgers', 'positive'], ['fries', 'positive'], ['local 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 Scene Hunky waiters dub diners darling and it sounds like they mean it."], "output": "[['Scene', 'neutral'], ['waiters', 'negative'], ['diners', 'neutral'], ['darling', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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, 4 members of the wait staff were giggling and carrying on at the corner of the bar."], "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": ["We had to wait 20 minutes before getting a beer, and we never got our burger order."], "output": "[['beer', 'neutral'], ['order', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 forgot our coffee, took forever to take our order, never checked in with us after the food came and when we were done, didn't bring us the check for the longest time."], "output": "[['waitress', 'negative'], ['coffee', '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 had no problems with our resevations and found the service and the meal well worth a wait, had we run into one."], "output": "[['service', 'neutral'], ['meal', '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": ["One of our diners didn't like her fish and both the waitress and the manager insisted on replacing it."], "output": "[['fish', 'negative'], ['waitress', '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": ["A glass of wine for each of us (decent), shared appetizer (snow peas, excellent), individual pizzas (just ok, and really, less filling than two slices at your local slice joint, not *nearly* as good as John's or Totonno's), a shared dessert (good but rather small), and the bill."], "output": "[['glass of wine', 'positive'], ['individual pizzas', '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 the menu, there are many inexpensive snacks, drinks and meals to choose from."], "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": ["My dining companion and I have nothing but raves about the  environment and the Food."], "output": "[['dining', 'neutral'], ['environment', '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": ["While waiting for a table, tried to get a drink from a bartender who seemed more interested in arguing with his waiters."], "output": "[['waiting', 'neutral'], ['table', 'neutral'], ['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": ["There should be more choices of items to load on the pie, still quality of their classic pizza is a slice above."], "output": "[['pie', '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 meat, onions, and cheese were good as was the roll, but I'd go back if I could forego the sauce."], "output": "[['meat', 'positive'], ['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": ["Rich appetizers (baked fontina, lentil cake, french onion soup) and ample, tasty salads."], "output": "[['appetizers', 'positive'], ['baked fontina', 'neutral'], ['lentil cake', 'neutral'], ['french onion soup', '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": ["Went here with my husband on a Saturday night for dinner since the place looked like it had great atmosphere."], "output": "[['dinner', 'neutral'], ['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": ["The bartender, the wait staff and management all put the customer first and that was clear and much appreciated."], "output": "[['bartender', 'positive'], ['wait staff', 'positive'], ['appreciated', 'positive'], ['customer', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I find the attitude of the managers to be appallingly superior, and the food below average, at sky-high prices."], "output": "[['attitude', 'positive'], ['managers', '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 recently ate Brunch there and was dismayed and dissapointed by the service."], "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": [") The food was good, but not at all 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": ["He described the specials in great detail and gave wine and appertizer suggestions."], "output": "[['specials', '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": ["The portions were kid sized and we spent about $100 a person in cluding wine (4 of us)."], "output": "[['portions', 'negative'], ['cluding 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 only quibbles are service - which was confused (we waited 10 minutes for menus), and the wine list, which is over-the-top expensive."], "output": "[['service', 'negative'], ['menus', '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": ["The waiter made a huge production over what order he should deliver the food, as we all agreed the miso should be eaten with the sushi to aid digestion."], "output": "[['waiter', '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": ["The kitchen turns out a long list of American bar food staples, like burgers and fries."], "output": "[['list', 'positive'], ['American bar food staples', 'neutral'], ['burgers', 'neutral'], ['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": ["When we went to dinner here, the place was empty, which should have been a clue."], "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": ["Went to celebrate my sisters birthday on 9/11 was 1st taken back on the waiters rude answering of a question we had about the menu."], "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": ["The food is pretty good, but after 2 or 3 bad experiences at the restaurant (consistently rude, late with RSVP'd seating), I decided I would only order delivery."], "output": "[['food', 'positive'], ['seating', 'neutral'], ['delivery', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The backyard provides a relaxing alternative, with wood-planked walls, climbing vines and umbrella-topped tables."], "output": "[['backyard', 'neutral'], ['alternative', '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": ["Bernard is a great host; it didn't bother me a bit that he recited the entire menu to my wife."], "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 I called the waitress on it, she said that they simply couldn't serve tap water."], "output": "[['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": ["Telly's has the best octopus ever and the fish was so good on the grill."], "output": "[['fish', 'positive'], ['grill', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Especially the manager or host who kept walking by and giving us the evil eye to see the progress of our dinner so they could turn the table over to other customers."], "output": "[['manager', 'negative'], ['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": ["the salad was good but my friends hardly ate their pasta."], "output": "[['salad', 'positive'], ['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 chicken breast with mole sauce, guacamole, sour cream and pico de gallo is a delicious main course and quite filling."], "output": "[['chicken breast with mole sauce', 'neutral'], ['guacamole', 'neutral'], ['sour cream and pico de', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 Buffet lunch and the sauce was water down, not at all spicy."], "output": "[['Buffet lunch', '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": ["ran ~$30 ($12 for the taco, 8 for the rb, 10 fir the drink) plus tax and a very deserved tip."], "output": "[['drink', 'neutral'], ['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": ["Of course we went there with a large party and had to wait a bit to get seated (even with reservations), but we had all our dishes served at the same time and promptly."], "output": "[['reservations', 'neutral'], ['dishes 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": ["We hunted the waitress to at least pay for the 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": ["Otherwise, you can eat at the bar (It was Saturday afternoon and the place was empty)."], "output": "[['bar', '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 not so goods: very pricey appetizers - $12 for a half cup of fried clams, $6 for two corn on the cob and $6 for a small plate of fries."], "output": "[['appetizers', 'negative'], ['cup of fried 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": ["I ordered the fried catfish, which had very little to no seasoning, the yams, and mac and cheese which were just okay."], "output": "[['fried catfish', 'negative'], ['seasoning', 'negative'], ['yams', 'positive'], ['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": ["When the manager came to our table at the end of the meal and asked how our experience was, I complained to him about the cold."], "output": "[['manager', 'neutral'], ['table', 'neutral'], ['cold', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 redeeming factor of the night was the dessert which was very good but certainly not worth the cost of an overall horible experience."], "output": "[['dessert', 'positive'], ['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 waiter knew about every item on the menu and explained it 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": ["Our waiter seemed to really care about getting us to the show on time, and made some good reccomendations on the menu for doing it."], "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": ["WAY OVER PRICED , HAD MUCH BETTER MEALS FOR JUST OVER HALF THE PRICE IN PLACES JUST AS NICE."], "output": "[['PRICED', 'negative'], ['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 peanut sauce came in a tiny plastic cup smaller than a shot glass."], "output": "[['peanut sauce', '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": ["Ten minutes later the manager relented and dropped off a glass of water with an upturned nose."], "output": "[['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": ["While the staff was kind and attentive, our waiter never once broke a smile, even when I told him it was my friend's birthday, although he did bring a dessert with a candle at the end of the meal."], "output": "[['staff', 'positive'], ['waiter', 'positive'], ['dessert', 'neutral'], ['candle', '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": ["They each included salad, miso soup, a california roll, and a whole plate of food."], "output": "[['california roll', '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 planned a holiday dinner at Kurio and we ended up waiting two hours for the appetizers."], "output": "[['holiday dinner', 'neutral'], ['waiting', '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 food was barely decent and our server was nowhere to be found."], "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": ["They've also got a huge salad/sushi/appetizer bar that you won't even get to if you're eating the meat."], "output": "[['bar', 'positive'], ['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": ["Amazing crust (and I hate pizza crust typically), great cheese, sauce isn't too sugary."], "output": "[['pizza crust', 'negative'], ['cheese', 'positive'], ['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 were however seated right away and was immediately told by our waiter that they were out of sparking mineral 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": ["The third time, after, an hour and a half of waiting, my friend went up to the host to check the status."], "output": "[['waiting', '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": ["Art and miscellany adorn the black-painted walls; strings of colored lights, disco balls and TVs are hung here and there; and on weekends a DJ fills the dining room with loud dance beats."], "output": "[['disco balls', 'negative'], ['DJ', 'neutral'], ['dance beats', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 the waitress down to get a drink refill and waited an extrodinarily long time for our entrees."], "output": "[['waitress', 'negative'], ['drink', '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 dessert, go with the delicate, subtle flan over the pasty rice pudding."], "output": "[['dessert', 'neutral'], ['flan', 'positive'], ['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": ["Maybe I've just gotten lucky with seating, but I've never had more than a ten minute wait."], "output": "[['seating', '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": ["So are cooked plates: Marinated Kobe beef practically melts on its skewers, soy-buttered scallops collapse with sweet brine and Chawanmushi custard, quivering in eel-soy broth with black truffles and foie gras, is over the top."], "output": "[['plates', 'neutral'], ['Marinated Kobe beef', 'positive'], ['scallops collapse', 'positive'], ['eel-soy broth with black truffles and foie gras', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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, the waiter tried to backpedal saying its too hard to time the cooking of miso soup with the sushi bar offerings."], "output": "[['waiter', 'negative'], ['cooking of miso 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": ["Start by enjoying the atmosphere while having a glass of wine at the bar and we you are ready, go and enjoy your food!"], "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": ["You're not going there for the decor you're going there for the best freeking pizza on the face of this earth and I garuntee you Dom delivers big time!"], "output": "[['decor', 'negative'], ['freeking 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": ["We ordered whole wheast toast; the waiter didn't bring it until 15 minutes after we had received our brunch."], "output": "[['waiter', '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": ["In retrospect, that was kind of foolish, as the portions for dinner were obscene."], "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": ["The mango salsa with fish cake was too sour, the apple suace for pork chop too sweet."], "output": "[['mango salsa with fish cake', 'negative'], ['apple suace', 'negative'], ['pork chop', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 rather slow but our waiter was very pleasant and obliging."], "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": ["If you don't mind interacting with sour-puss employees, then by all means, enjoy the treats at Sweet Melissa."], "output": "[['employees', 'neutral'], ['treats', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 want cheap eggs, omelets, pancakes or French Toast, with all the trimmings plus good coffee, fast and straight-up, this is the place if you live in Park Slope."], "output": "[['eggs', 'positive'], ['pancakes', 'neutral'], ['French Toast', '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 open-faced sandwich I tried had fluffy scrambled eggs and the silkiest smoked salmon I've ever had, and I've eated a lot of lox over the years!"], "output": "[['open-faced sandwich', 'neutral'], ['scrambled eggs', 'positive'], ['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": ["While the service and setting were average, the food was excellent."], "output": "[['service', 'negative'], ['setting', '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 so excited since I was reading great review of this place, however we were disappointed with the taste of the food."], "output": "[['place', 'negative'], ['taste', '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": ["So we showed up with our reservations and even though the place stayed pretty empty throughout the night, they seated us right next to the swinging kitchen doors."], "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": ["Also, overheard gent at the next table complaining to the manager about his food."], "output": "[['table', 'neutral'], ['manager', '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": ["At 1:15 we were still waiting for our plates!"], "output": "[['waiting', '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 sat at the bar and were constantly bumped by the waitress flying past; had fabulously fresh raw oysters with pieces of shell in every bite; lobsters rolls were tasty but the large pieces of meat were tough; the apple crumble was excellent but the ice cream was over-frozen and the stench of frying oil was nearly unbearable."], "output": "[['bar', 'neutral'], ['waitress', 'negative'], ['rolls', 'positive'], ['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": ["Half the menu is comprised of original creations while the other half consists of unique slants on orthodox cuisine such as the single super-sized gnocchi with cinammon."], "output": "[['menu', 'neutral'], ['gnocchi', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 Manhattanites like us that are used to pretentious attitudes and expensive tabs, this place is definitely a nice change from the rest of the meatpacking district."], "output": "[['attitudes', 'negative'], ['district', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 were good, but don't have blueberry pancakes on the menu of you are not able to produce more than three tiny blueberries in each pancake."], "output": "[['blueberry pancakes', '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 had reservations for 9:30pm and after waiting more that 50 mins and bunch of lies that you're next."], "output": "[['reservations', '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": ["Otoro tuna, gorgeously marbled with fat, is captivating; hamachi sashimi, topped by the chef with a whisper of sea salt and a barely-there squeeze of lemon, creates eye-rolling pleasure."], "output": "[['Otoro tuna', 'positive'], ['sashimi', 'neutral'], ['chef', 'neutral'], ['whisper', 'neutral'], ['sea salt', 'neutral'], ['pleasure', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Dropped in for a quick bite with a friend -- like the previous reviewer it took more than 15 minutes for any kind of service at all (including getting water) and then another 45 minutes to get a burger (which admittedly was good)."], "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": ["Great pizza for lunch place."], "output": "[['pizza', '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": ["seems everyone ordered sushi there were tons of delivery orders (we can tell as we sat near the back)."], "output": "[['sushi', '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": ["Arrive at 7:00pm, the waiters didn't give us our menus till an 1 1/2 hour later."], "output": "[['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": ["The round pizza doesn't taste as good as I recall, it's still wonderful, but the Sicilian is to die for."], "output": "[['round pizza', '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": ["I'm also a big fan of the chicken pizza on their new bar menu (no bread - weird, huh?"], "output": "[['new bar menu', '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": ["Start with fennel-fragrant grilled sardines and the extraordinary pastas, such as poppy-seeded sweet beet ravioli, brown-butter-slicked squash tortelli, and airy swiss chard-ricotta malfatti (misshapen gnocchi with fried sage)."], "output": "[['fennel-fragrant grilled sardines', 'neutral'], ['pastas', 'positive'], ['sweet beet ravioli', 'positive'], ['brown-butter-slicked squash tortelli', 'positive'], ['swiss chard-ricotta', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 didn't pay for the meal (and it's about $22 bucks a plate, way over my normal eating range), I have to say that it was better than any food I've ever had in little Italy, and there weren't any touristy elements to be found."], "output": "[['range', '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 servers, attentive if slightly unpolished, gladly direct inquisitors to menu strengths--like rum-flambeed dessert bananas foster--and allow leisurely enjoyment."], "output": "[['servers', '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'm totally into the space-age vibe of this place, but I wish they had more tables to sit down at."], "output": "[['vibe', 'negative'], ['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": ["Ask for a table closer to the bar than in back of the dining area; the drop ceiling the back compromises enjoying the soaring space of Guastavino's."], "output": "[['bar', 'neutral'], ['drop ceiling', '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": ["When we got our bill the drinks were full priced and when we asked, our waitress said that there is no happy hour on the roof."], "output": "[['bill', '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 hostess was condescending and the waiter was somewhat absent and unaccomodating (sure, we made a reservation to sit outside but when I asked to be moved indoors after I heard thunder he didn't even try to make it happen, giving me a blank stare and a shrug when I asked what we would do if it rained)."], "output": "[['hostess', 'negative'], ['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": ["The server was so busy the night we visited that she forgot to put in our food order."], "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": ["The Food The versatile Austrian menu, fused with French and American, rewards both high and low-end appetites: rich, cheese-laden onion soup, grilled Gruyere and country ham sandwiches and big-bunned burgers are as satisfying as velvety liver terrine with kumquat-cranberry compote, speck and sausage charcuterie and inexpensive cheese plates."], "output": "[['Food', 'neutral'], ['versatile', 'neutral'], ['menu', 'neutral'], ['French', 'neutral'], ['onion soup', 'positive'], ['country ham sandwiches', 'positive'], ['liver terrine', 'positive'], ['kumquat-cranberry', 'positive'], ['speck', 'positive'], ['sausage', 'positive'], ['cheese 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": ["There are no price listed in the menu, and she will not provid them with a smile."], "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": ["The food was served promptly and was really hot."], "output": "[['food', '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 This isn't for those on a budget, but portions are generous."], "output": "[['Food', '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": ["When I couldn't hear any of my selections in the dining room, the manager told me that the broken speakers in were 'not his fault'"], "output": "[['dining room', '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": ["Candles on the tables, cozy furnishings and music at just the right level make it a great dining experience."], "output": "[['Candles', 'neutral'], ['furnishings', 'positive'], ['music', 'positive'], ['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 always find myself asking the waiter to make something bland and different than what is 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": ["My only complaint was that when I tried to go back with some friends on a crowded night, the place was packed, yet they told us there was a 20 minute wait and that we should wait 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 wait for a table is interminable."], "output": "[['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": ["Great value for the price-- lunch is an even better value, with entree and appetizer for between $8-10 or so."], "output": "[['price', 'positive'], ['lunch', '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": ["Having eaten here for lunch many times, I can definitely vouch this place for having some of the best per-slice Pizza in the city."], "output": "[['lunch', 'neutral'], ['per-slice 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 food and service was top notch, only the complain is that this place is so small that some seats are not made for a big guy."], "output": "[['food', 'positive'], ['service', 'positive'], ['seats', 'negative'], ['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": ["went there for sunday brunch after a wonderful massage - the food was terrible-bland/tasteless, cold, expensive."], "output": "[['brunch', '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": ["Our waitress did not take our drink order until I finally flagged her down and even then she seemed disinterested in our meal."], "output": "[['waitress', 'negative'], ['drink', 'neutral'], ['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": ["wait staff have no room to get to tables because of overflow from bar area, and knocked into the back seats of our table constantly."], "output": "[['wait staff', 'negative'], ['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": ["The concoction was thrown away a mere two blocks from the Bar."], "output": "[['concoction', '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": ["Had the calamari app, which TGIFriday's makes better, and the scallop ceviche - that is NOT ceviche!"], "output": "[['calamari app', 'neutral'], ['scallop ceviche', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 could be a bit better, and if there was a small bar the overall atmosphere would be a bit more inviting (especially for regulars)."], "output": "[['decor', 'negative'], ['bar', '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": ["Maybe it was the choices the chefs had put on the Restaurant Week Menu, but much of our food was just so-so."], "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": ["I love the shrimp summer role, chicken kabob's, and all the chicken and shrimp dishes."], "output": "[['shrimp summer role', 'positive'], ['shrimp 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 got a steak special that was way overpriced ($12 more then the steak on the menu and no warning from the waitress) and it was cooked to the wrong temperature."], "output": "[['steak special', 'negative'], ['menu', 'neutral'], ['waitress', 'negative'], ['temperature', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 people are late, you could lose your reservation and/or the staff does pressure you to start ordering even if your whole party hasnt arrived."], "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": ["People will literally spend their entire lunch break waiting and for what - an average fastfood burger."], "output": "[['lunch', 'neutral'], ['waiting', '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": ["If you like an ecclectic crowd and an overall good time where you and your friends can get together whether it be to eat, drink or just play some good old pictionary (they provide crayons and a blank white sheet at every table), go to the Cargo!"], "output": "[['time', 'positive'], ['drink', 'neutral'], ['sheet', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 a sleek, cool lounge with refreshing new color, lighting and surfaces, Fig 27 mirrors its around the corner sibling, PS450 with a yummy menu of small bites, great drinks and wonderful staff."], "output": "[['lounge', 'positive'], ['new color', 'positive'], ['mirrors', 'neutral'], ['menu', 'positive'], ['drinks', '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": ["We would rather pay more prices and expect the better food and service."], "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": ["We finally flagged down another server who brought us more to drink, and then they took forever with the check."], "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": ["When we asked a waiter for an explanation of the long wait with some many empty tables he had no answer so we asked for the manager."], "output": "[['waiter', 'negative'], ['tables', '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": ["went here late night after a a few drinks at my favorite watering spot and was amazed that a place which serves food till 4 can be so damned good."], "output": "[['drinks', '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": ["Although she was obviously busy, she was helpful in describing certain items on the menu and suggested a duck dish that was out of this world."], "output": "[['menu', 'neutral'], ['duck 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 bartendars were right on top of getting us our wine and setting up free blue cheese dip and chips for us."], "output": "[['wine', 'neutral'], ['bartendars', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 got a little bizarre when we asked the waiter how the joint got it's name, and he made his hands into cups in reference to placing them on a woman's breasts and said, No, not this."], "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": ["The waitstaff are surprisingly uninformed and unintelligent, and I say this even though I liked my waiter."], "output": "[['waitstaff', '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": ["Right after we finished the main course (the organic chicken was dry), but before we finish drinking the wine the check was placed on the table, and the waitress came back and picked it up three times."], "output": "[['organic chicken', 'negative'], ['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": ["The outdoor patio is really nice in good weather, but what ambience the indoors possesses is negated by the noise and the crowds."], "output": "[['outdoor patio', '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": ["The Food There's a trimmed-down version of the regular Blue Ribbon menu--all manner of sandwiches, and a solid selection of American main courses--but the real attraction is the vast, well-edited range of cheese, fish and vegetable portions (goodies like foie gras terrine aside, the meat selections are disappointingly indistinct)."], "output": "[['Food', 'neutral'], ['Blue Ribbon menu', 'neutral'], ['sandwiches', 'neutral'], ['range of cheese', 'positive'], ['vegetable 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": ["Most of the food has a vinegary flavor (I think because of the injera)."], "output": "[['food', '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": ["It does get crowded with plenty of blue shirted cigar smoking wannabes, so make a reservation."], "output": "[['blue shirted cigar', '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": ["My bass was even worse - smothered in some kind of tomato sauce that just did not go with fish and the spinach that accompanied the dish was extremely dry and flavorless."], "output": "[['bass', 'negative'], ['tomato sauce', 'neutral'], ['fish', 'negative'], ['spinach', 'negative'], ['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": ["service was attentive at the beginning but the waiter lost us towards the end and we had to flag them down for the check."], "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": ["For the price ($8), the quality of the buffet is great!"], "output": "[['price', 'neutral'], ['quality of the buffet', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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, but not least, when we walked in, most of the clientelle was Vietnamese and next to us was a food critic whose review was on the back of the menu."], "output": "[['clientelle', 'negative'], ['food', '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 bottom line is that Mercadito is All style and No substance (the drinks had far too much salad and seasoning in them."], "output": "[['drinks', 'neutral'], ['salad', 'negative'], ['seasoning', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 warm, sexy, and very romantic but the lighting wasn't good for reading the menu."], "output": "[['atmosphere', 'positive'], ['lighting', '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 reading the negative sushi reviews, my boyfriend and I opted for their Korean fare."], "output": "[['sushi', 'negative'], ['Korean 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": ["With all of the kitchen goof-ups (appetizer coming out before the entree and one entree coming out ten minutes before the other) you would think that the wait staff would have been more attentive."], "output": "[['appetizer', '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": ["One Entree from their restaraunt is enough to fill two adults, not to mention that all their dishes are out of this world."], "output": "[['Entree', '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 I asked the waitress, she told me they couldn't afford the salmon, and had changed the dish (though not on the menu)."], "output": "[['waitress', 'neutral'], ['salmon', '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": ["I had reservations for a week but was seated at the worst table in the room,against a wall near the entrance to the kitchen,very claustaphobic."], "output": "[['reservations', 'neutral'], ['table in the 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 food was a mix of sandwiches, salads and appetizers that were mostly healthy and had a nice Brazilian touch."], "output": "[['food', 'neutral'], ['mix of sandwiches', 'positive'], ['salads', '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": ["My vegetable Napoleon was good; although i first got the veggie burger because the waitress mis-heard and stood my friend up for another 15 minutes of waiting to have it served."], "output": "[['vegetable Napoleon', 'positive'], ['veggie burger', '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": ["If you're going to label spicy items on your menu as spicy (like the Buffalo and Cajun wraps), I think you should go ahead and label all the spicy items as spicy."], "output": "[['menu', 'neutral'], ['Cajun wraps', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 our menu away, without taking our food order!"], "output": "[['waitress', 'negative'], ['menu', '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": ["Great for those hungover mornings when you need a decent pint and delicious, homemade food that will tide you over for the whole day."], "output": "[['homemade food', '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": ["Into our appetizer, an adjacent table became available, and we asked if we could use it, but the waiter said it most likely was being used."], "output": "[['appetizer', '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": ["To make matters worse an hour into our dinner we see a waiter take mojitos to another table."], "output": "[['dinner', 'neutral'], ['waiter', 'negative'], ['mojitos', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 dinner at becco on a friday night, and were seated in the left bar area, which while pretty crowded, had a manageable noise level."], "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 huge terrace is just so beautiful--and rumor has it they'll be tenting the space this fall, so we midtowners can continue to dine outside through the end of the year."], "output": "[['terrace', '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": ["about 10 minutes apart each, so we were all eating cold eggs by the time we got our food."], "output": "[['eggs', '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 demanding a free round of drinks from a third manager, our party decided to bail on this horrific french import."], "output": "[['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": ["Been there a few times for dinner, brunch or just a drink (the French cosmos are fantastic) and it just keeps getting better."], "output": "[['dinner', 'neutral'], ['drink', 'neutral'], ['French cosmos', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Steak - Porterhouse for 2 was served for 1, overspiced, overpriced and tasted frozen, with a hint of msg Dessert - best part of meal, good espresso Overall - if food quality matters to you over pretty lights and models handing you towels in the bathroom, i don't recommend."], "output": "[['msg Dessert', 'positive'], ['food 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": ["They served the salad and the main course together and didn't even bring the dessert menu."], "output": "[['salad', 'neutral'], ['main course', 'neutral'], ['dessert 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": ["This happened while many diners were enjoying their meal and it was rudes."], "output": "[['diners', '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 food was good (and the $25 prix fixe made it all that much better), but the dinner started to feel like an assembly line when our appetizer arrived 5 minutes after ordering."], "output": "[['food', 'positive'], ['prix fixe', '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": ["We preferred to gaze at our burgers while avoiding having to look at the wait staff, but no complaints."], "output": "[['burgers', '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": ["Interesting crowd for people watching - old school Italian music cranking - friendly Italian waitress brought us our wine garlic bread in no time."], "output": "[['music', 'positive'], ['waitress', 'positive'], ['wine 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": ["I didn't even have time to finish my single cocktail and the waiter didn't even ask if we wanted coffee but instead, gave us our check without us even requesting it."], "output": "[['cocktail', 'neutral'], ['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": ["All the food was carefully prepared and the presentation was a cut above."], "output": "[['food', 'positive'], ['presentation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 possibly the worst service in New York I have waited until the waiter has finished his paper, begged for water and waited over an hour for my meal."], "output": "[['service', 'negative'], ['waiter', 'negative'], ['water', '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": ["When my (pregnant) friend asked about a non-alcoholic version of a drink, the answer was simply no, with no further suggestions."], "output": "[['drink', 'neutral'], ['answer', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 friends coffee shop makes great food the service is great and they are very poilte i think that they should open more because there the best food store i ever ate from the food is addicting and you cant stop eating because it so delious."], "output": "[['coffee', '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": ["From beginning appetizers, the scallops were incredible, to the delicious chocolate souffle with rasberry mint sorbet, we were delighted by the taste sensations."], "output": "[['beginning appetizers', 'neutral'], ['scallops', 'positive'], ['chocolate souffle with rasberry mint 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 waiter didn't know the menu, didn't bring more than one item at a time, and put some orders in twice with the kitchen."], "output": "[['waiter', 'negative'], ['menu', '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": ["deserts were slow to order as waiters passed us twice, even with the menus closed."], "output": "[['deserts', 'negative'], ['waiters', 'negative'], ['menus closed', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 negligent in alerting customers when an order is ready - you could end up waiting for half an hour while your food is sitting on their counter getting cold."], "output": "[['waiting', 'neutral'], ['food', '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": ["I was at Son Cubano a few months ago, and although i was only at the bar (without prior reservations which are a must), i had an awesome time."], "output": "[['bar', 'neutral'], ['reservations', '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 busboys were more helpful than my server who then made me wait at the bar (very crowded with what appeared to be tasty margaritas) to pay the bartender - what's that about?"], "output": "[['busboys', 'positive'], ['server', 'negative'], ['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": ["There were a lot of scensters who couldnt afford dinner hanging in the waiting area so we got bumped around a lot."], "output": "[['dinner', 'negative'], ['waiting 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": ["Our food took forever, the bartender seemed more interested in refilling drinks for the regulars and never even brought bread or water, as requested."], "output": "[['food', 'negative'], ['bartender', '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": ["Renderings of mythical creatures festoon its walls, and heavily tattooed waitresses pick up orders from the open kitchen and chat at the small bar."], "output": "[['waitresses', 'negative'], ['open kitchen', '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 staff even went out of their way to print up menus without prices at my request, since the dinner party was my treat."], "output": "[['staff', 'negative'], ['menus', '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": ["Despite reservations, we ended up waiting for 1hr+"], "output": "[['reservations', '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 mussels marina are a must for an appetizer, although you can't go wrong with the stuffed artichoke either."], "output": "[['mussels marina', '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 waiter didn't recommen any special for the night, didn't come back to the table to check if everything is okay, didn't even offer me the dessert menu at the end."], "output": "[['waiter', 'negative'], ['table', 'neutral'], ['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": ["The trick to the tomato and onions is ask for it light on the onions, heavy on the tomatoes, order steak for one less person than you have in your party and if the steak is too rare, you can cook the individual pieces more by placing them on the platter around the edges."], "output": "[['tomato and onions', 'neutral'], ['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": ["My party felt like we got put in a dining room for tourist, which must have been the penalty box area for the disgruntled wait staff on duty."], "output": "[['dining room', '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": ["then the manager gave us lemon juice instead of ceasar dressing for a ceasar salad which ruined the salad."], "output": "[['manager', 'negative'], ['lemon juice', 'neutral'], ['ceasar dressing', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 won't blink twice at the restaurant's spartan decor: As the packed crowds and critics' praises wallpapering the front wall agree, this longtime local favorite is truly one of the area's most exquisite finds."], "output": "[['Scene', '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": ["But on a recent Sunday brunch excursion, I was greeted by a uniformly unfriendly staff - starting with the hostess and extending to foul faced wait staff."], "output": "[['brunch', 'neutral'], ['hostess', 'negative'], ['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": ["Our waiter brought out three main courses, but the fourth wasn't ready so we had to wait for 10 minutes for the last dish to arrive, but they were very nice and gave us free red pepper hummus while we waited."], "output": "[['waiter', 'neutral'], ['main courses', 'neutral'], ['dish', 'neutral'], ['red pepper hummus', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 mouthwatering sardinian Stuffed Squid and a Catfish fiumarola from Rome( think was capers and anchovies sauce)."], "output": "[['sardinian Stuffed Squid', 'positive'], ['Catfish', '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": ["The service was great -- my glass was refilled without having to ask, we were greeted by the manager that day to ask how our food was."], "output": "[['service', 'positive'], ['manager', '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": ["got the guac but no drinks until it was all gone (approximately 20 minutes later)."], "output": "[['guac', '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": ["Although when I went to eat dinner at Bombay Talkie on a crazy busy night, my waiter was extremely helpful through the menu, polite and polished."], "output": "[['dinner', 'neutral'], ['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": ["Zippier palates share sesame-fried lobster spring rolls, shrimp dumplings with citrus soy, and inventive maki, like the smoky and sweet filet mignon-pineapple variety."], "output": "[['lobster spring rolls', 'neutral'], ['shrimp dumplings with citrus soy', 'neutral'], ['smoky', 'neutral'], ['filet mignon-pineapple 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": ["Towards the end of our meal, a server came out, apparently our orders had been double-filled."], "output": "[['meal', '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": ["This place would be so much better served by being run by a group that actually understands customer service."], "output": "[['served', '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": ["Only thing we didn't like was the steamed chocolate cake with mint ice creama group of the 4 of us did not want to finish this dessert!"], "output": "[['steamed chocolate cake with mint ice', '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 situation was verified by taking 3 dishes that were over an hour late off the bill and free desserts and coffee but the experience left most of us never wanting to go to the supposed hip cool 66 ever again."], "output": "[['dishes', 'neutral'], ['bill', 'neutral'], ['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": ["The perfect meal; delux combo raw bar as an appetizer, King crab as your entree."], "output": "[['meal', 'positive'], ['bar', 'neutral'], ['King 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": ["I went there about three times, one for dinner on a sunday evening which is a salsa night after dinning, the service was slow and a bit rude, the plates average some shrimp octopus and empanadas."], "output": "[['dinner', 'neutral'], ['service', 'negative'], ['shrimp octopus', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 care about the wait staff as long as they bring you your drinks and dinner, then go to Opa."], "output": "[['wait staff', '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": ["Food was average, the appetizers were better than the main courses."], "output": "[['appetizers', 'positive'], ['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": ["Sure the food was - as always - very good, but we were quite outrageous about the waitress."], "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": ["I go there to eat dinner, brunch, or to just drink and hang out at the bar with the friendly staff."], "output": "[['dinner', 'neutral'], ['drink', 'neutral'], ['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": ["My husband and I had dinner here last week and the food was very good."], "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": ["Bouley has done an excellent job creating this dining establishment with almost a museum sense, the artworks on the wall have a very Klimty feeling and the gold ceiling completes the rest of the experience."], "output": "[['dining establishment', 'neutral'], ['artworks', 'positive'], ['gold 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": ["The service was polite, friendly and prompt, the characters walking around entertained the kids but werent intrusive to our meal."], "output": "[['service', '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": ["Includes a diverse array of entrees ranging from Boar (prepared in your choice of either the French or Asian tradition), Mussels, or Pad Thai that grace the menu all at once, each one prepared in a distinctly different and delicate sauce."], "output": "[['entrees', 'positive'], ['Mussels', '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": ["we live down the street and have eaten here many times for lunch and dinner, and the food is consistently terrific."], "output": "[['lunch', '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": ["Service has improved drastically from the old days, you are now seated by a hostess instead of standing behind a nearby table waiting for them to finish."], "output": "[['Service', '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 service was great, the chef even gave me a complimentary dish."], "output": "[['service', 'positive'], ['chef', '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": ["We asked for bread plates when the bread was brought to the table and the server's response was management has decided not to offer bread plates."], "output": "[['table', 'neutral'], ['server', 'negative'], ['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": ["Service was prompt, although at times the waiters seemed to be spending more time dealing with the overflow from the bar than the diners (ever heard of cocktail waiters)."], "output": "[['Service', 'negative'], ['bar', 'neutral'], ['diners', 'neutral'], ['cocktail 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": ["the place has an awesome decore, with fish swiming below certain tables."], "output": "[['decore', 'positive'], ['fish', '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": ["I had a 9pm reservation and wound up sitting down closer to 10, but the bar was entertaining enough for the almost-an-hour wait (excellent martinis)."], "output": "[['bar', 'neutral'], ['martinis', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 ceviche was amazing pared with mango."], "output": "[['Lobster ceviche', 'positive'], ['mango', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 and while our food took time to be prepared, our waiter earned points for his sparkling conversation to pass time and for also knowing practically every ingredient of every special under consideration."], "output": "[['food', '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": ["Decor is old, but the bathrooms are clean and updated."], "output": "[['Decor', 'positive'], ['bathrooms', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 reasonable, probably $55/pp with appetizers, main course, dessert and a drink."], "output": "[['Prices', 'positive'], ['appetizers', 'neutral'], ['main course', '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": ["This was not the same hostess I usually see there who happens to be very sweet and provides excellent service."], "output": "[['hostess', '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 is nothing else on the menu except for exotic teas and cold beverages, but with a meal this cheap and delightful, who would care?"], "output": "[['menu', 'neutral'], ['exotic teas', 'neutral'], ['beverages', '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 servers were snobby and got mad at me when I asked if they serve by the slice."], "output": "[['servers', 'negative'], ['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": ["I have reservations about the all you can eat deal, however -- the choices are fairly limited and you can probably order more food than you can eat for less than $18 by just going off the menu."], "output": "[['reservations', 'neutral'], ['choices', 'negative'], ['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": ["Try the olive cream cheese or the lox spread on a whole wheat everything bagel."], "output": "[['olive cream cheese', 'positive'], ['lox spread', '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": ["Sometimes I grow a bit weary of dining in those pretentious, haughty taughty, high fashion eateries."], "output": "[['dining', 'neutral'], ['eateries', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The meat was great, but vegetables needed flavor and etc."], "output": "[['meat', 'positive'], ['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": ["However, if you want to, drink and enjoy the pleasures of food, Sam's is your new home away from home."], "output": "[['drink', 'neutral'], ['pleasures', '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": ["While they adhere to a certain traditionality in serving their teas; eg: samovar for the russian, chinese tea sets for the green, the food labours under no such restrictions and there is nothing ordinary on the menu."], "output": "[['serving', 'neutral'], ['teas', 'neutral'], ['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": ["For a normal dinner, I prefer a place that has a bit more room and that has a slightly more relaxed vibe."], "output": "[['dinner', 'neutral'], ['vibe', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Shun Lee has been serving creative Chinese food in a deluxe dining room for 30 years--they must be doing something right!"], "output": "[['Chinese food', 'positive'], ['deluxe 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 smoked salmon appetizer was pretty good (it comes with goat cheese, calpers and onions)."], "output": "[['smoked salmon appetizer', 'positive'], ['goat cheese', '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": ["The staff was courteous and explained the menu with detail."], "output": "[['staff', 'positive'], ['detail', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 are no guarantee of prompt seating, have a pre-game drink, pop a xanax and you can handle the drama of having a res and getting no love from the hostess."], "output": "[['Reservations', 'neutral'], ['pre-game drink', '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": ["Soy abounds, in all forms: as firm patties, pure squares of glistening tofu, and something called a hijiki patty--mixed tastily with shreds of seaweed, then fried."], "output": "[['patties', 'negative'], ['tofu', 'neutral'], ['mixed', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 always people waiting to be seated and the chairs are not comfortable."], "output": "[['waiting', 'neutral'], ['chairs', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 playing god with his headset and reservation list, the bar was packed with horney drunken investment bankers, reservations are a joke and after haplessly sliding the plates at us when serving the food, they couldn't wait to collect the plates until we were done."], "output": "[['bar', 'neutral'], ['reservations', '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": ["Instead, Yasuda's swarm of waiters and waitresses hovered incessantly overhead, seizing any opportunity to fill a glass, reorganize the table, ask if we were done, and of course clear us out of there in under 80 min."], "output": "[['waitresses', '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 love Chinese food and have been looking for the alternative to the greasy stuff on every corner of New York- ya, you know, the stinky take-out joints that leave you smelling like dinner for 100 for the rest of the night!"], "output": "[['Chinese food', 'positive'], ['stuff', '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 waitress was a bit cold but she was still attentive and food came quickly."], "output": "[['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": ["One would think we'd get an apology or complimentary drinks - instead, we got a snobby waiter wouldn't even take our order for 15 minutes and gave us lip when we asked him to do so."], "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": ["The Food The classic Italian menu gets off to a good start with Queen's famous bread basket, which is loaded with a slew of crunchy, yeasty homemade varieties."], "output": "[['Food', 'neutral'], ['Italian menu', 'positive'], ['bread', 'positive'], ['varieties', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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's almost enough to prove its legitimacy to me, but eating there, both for a quick slice and sit-down for pasta with my family has always been a delicious, inexpensive and fun experience."], "output": "[['pasta', 'positive'], ['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": ["Mac cheese is nothing to write home about; the beet salad is boring, mostly lettuce; tuna sandwhich - boring, mostly mayo; the french fries looked re-fried and were cold; the excellent pork sandwich came on one of those supermarket hot-dog buns."], "output": "[['Mac cheese', 'negative'], ['beet salad', 'negative'], ['tuna 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": ["Ok I got the edamame and something from the sushi chef for free, but the quality of food is more important to me than a free small dish (maybe that's why the restaurant gives it to attact new customers."], "output": "[['edamame', 'neutral'], ['sushi chef', 'positive'], ['quality of food', '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": ["We were directed to a table by a member of staff, which we were then informed was reserved, and lost our seats at the bar, all this after spending upwards of $30 each on very expensive drinks over a two-hour period."], "output": "[['table', 'neutral'], ['staff', 'negative'], ['seats', '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 our meal,the manager, even took some of his time to sit with us and give us a lesson in Sake 101."], "output": "[['meal', '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": ["So if he can't find fresh-good product, he'll remove a dish from the menu which I think is fantastic."], "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": ["This much heralded restaurant brought my wife and I some excitement as we walked in the door, but we were met with an awkward maitre'd who barely spoke to us at all and just seemed standoff-ish."], "output": "[['door', 'neutral'], ['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": ["we were in haven from appetizers, my favorite was the tuna tartare, to the dim sum,the best was shrimp and foie gras dumpling, and i could go on and on, everything was an explosion of flavors."], "output": "[['appetizers', 'neutral'], ['tuna tartare', 'positive'], ['dim sum', 'positive'], ['shrimp', 'positive'], ['foie gras dumpling', 'positive'], ['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": ["The prices seemed reasonable with entrees ranging from $14-$25."], "output": "[['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": ["it would be better to place the bar closer to the front of the restaurant and away from the tables."], "output": "[['bar', 'neutral'], ['front', '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": ["we wanted to join another 2 top table to ours and the manager abruptly said, that won't work for us!"], "output": "[['table', '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 only drawback was slow service, but the food and ambience are so nice that your wait is A) pleasant and B) worth it."], "output": "[['service', 'negative'], ['food', 'positive'], ['ambience', '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": ["I like the somosas, chai, and the chole, but the dhosas and dhal were kinda dissapointing."], "output": "[['somosas', 'positive'], ['chai', 'positive'], ['chole', 'positive'], ['dhosas', 'negative'], ['dhal', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 is okay - not many vegetarian options, and the portions are small."], "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": ["Not a destination restaurant, but if you're hungry for breakfast or lunch, big portions and good quality for the money."], "output": "[['breakfast', 'neutral'], ['portions', 'positive'], ['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": ["Had a dinner date (her suggestion) :) Had the mussels (really good) and smoked salmon (not the best) for appys."], "output": "[['mussels', 'positive'], ['smoked salmon', 'negative'], ['appys', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 vegi burgers (and the full bar) are the main draws: ranging from the Super Veg-Burger with lettuce, tomato and Abijah's secret sauce to the McKate (two un-beef patties, special sauce, lettuce, dairy or nondairy cheese, etc."], "output": "[['full bar', 'positive'], ['tomato', 'neutral'], [\"Abijah's secret sauce\", 'neutral'], ['un-beef patties', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 did not check on us, ask if we needed anything, refill our water or get our dessert order right."], "output": "[['server', 'negative'], ['water', '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": ["Between the seven of us we sampled just about everything on the menu, and nothing disappointed (ribs pulled pork seemed like the biggest hits)."], "output": "[['menu', 'neutral'], ['ribs', '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": ["However, when our waitress realized her faux pas, an extra glass of wine was sent to our table and all was forgiven."], "output": "[['waitress', 'negative'], ['glass of wine', '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 The Mediterranean influence shows up in the not-so-dainty tuna salad tossed with artichoke hearts, roasted red peppers, black olives and capers."], "output": "[['Mediterranean influence', 'neutral'], ['tuna salad', 'positive'], ['roasted 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": ["(Though the filet won't be enough if both have hearty apitites."], "output": "[['filet', 'negative'], ['apitites', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 weren't bad though - dinner ended up at $80 with tip and we had a couple drinks as well."], "output": "[['prices', 'positive'], ['dinner', '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": ["impressive balcony seating and while they forgot to give us the cold appetizers, the waiter and maitre'd more than made up for it by being most accomodating to us."], "output": "[['seating', 'neutral'], ['waiter', 'positive'], ['maitre', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Clinton-frequented restaurant stands handsomely on a quiet residential corner, and the modern interior includes a long dining room, a small bar and harsh lighting."], "output": "[['interior', 'positive'], ['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 staff were rude and rushed us through our meal, clearing plates and laying down dessert menus while others were still eating their main courses."], "output": "[['staff', 'negative'], ['meal', 'neutral'], ['plates', '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": ["Our waiter was a little stressed and brought a couple things out late and as a result, he apologized graciously and gave us wine on the house to compensate for the delay."], "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": ["My only advice is: increase portion sizes; and develop a special drink list."], "output": "[['portion', 'positive'], ['drink 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 Scene Neither trendy and slick nor haute and haughty, it this cozy wine bar adds a bit of Mediterranean sun to the chilly east 70s."], "output": "[['wine bar', 'positive'], ['Mediterranean', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 should expect a wait, big deal, small price to pay for great food as far as I'm concerned."], "output": "[['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": ["Service is not what one would expect from a joint in this price category."], "output": "[['Service', 'negative'], ['price category', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 sliced mozzerella, the sweet roasted peppers, the hint of garlic and oil, are just some of the ingredients that produce the light otherworldly tasty pizza at Grimaldi's."], "output": "[['ingredients', '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": ["Snack on a bowl of fried chickpeas while you browse the menu, then move onto the tender lamb skewers, which arrive atop a slab of French bread, perfectly poised to catch the meat's sweet drippings."], "output": "[['a bowl of fried chickpeas', 'neutral'], ['menu', 'neutral'], ['lamb skewers', 'positive'], ['French bread', '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": ["Anyway we get a table and order some appetizers from one of the waitresses who was pleasently nice."], "output": "[['table', 'neutral'], ['appetizers', 'neutral'], ['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": ["However, it takes ages to get seated (even with a reservation), and the waiters don't seem very knowledgeable about the menu (or receptive to questions)."], "output": "[['reservation', '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 feta cheese wrapped in filo dough and deep fried is a MUST TRY appetizer."], "output": "[['filo dough', 'neutral'], ['deep fried', '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 hostess was totally not accomadating, and even though there were empty tables they still didn't seat us!"], "output": "[['hostess', '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": ["After the meal, you can always walk a little southwest to the beautiful Nelson Rockefeller Park on the Hudson and play some frisbee or touch football."], "output": "[['meal', 'neutral'], ['Nelson', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 took ten mins to get me a glass of water."], "output": "[['service', 'negative'], ['glass', '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 server came by only once to pour additional wine for the table; the rest of the time, we had to fish the bottle out of the two-table communal bucket ourselves."], "output": "[['server', 'negative'], ['wine', 'neutral'], ['the table', 'neutral'], ['fish', 'neutral'], ['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": ["when our server accidentally spilled some wine at our table, he cleaned it up offered us another glass right away."], "output": "[['server', 'positive'], ['wine', '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": ["maybe its the cost of top ingredients but 17."], "output": "[['cost', '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": ["Ive been to Jacques-Imo in New Orleans, the wait is long (3+ hours) but the food and service more than makes up for it."], "output": "[['wait', 'negative'], ['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": ["1) Service is very slow and unattentive (10 minutes for our server to come by with our menus and to take our drink order, another 10 to bring the drinks/take our dinner order, you get the idea."], "output": "[['Service', 'negative'], ['server', 'negative'], ['menus', '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": ["Went with a girlfriend, waited for over an hour while we had drinks, food was ok, service was terrible."], "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": ["The Food The menu includes lovingly made renditions of panini, bruschetta and tramezzini (cocktail-style sandwiches with fillings like tuna with black olive pesto and bresaola with arugula), along with a roster of cured meats, cheeses and olives that have been imported from Italy."], "output": "[['menu', 'neutral'], ['bruschetta', 'positive'], ['tramezzini', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 atmosphere, not a quiet romantic dinner."], "output": "[['atmosphere', '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": ["Met a friend here for lunch and while the food was excellent (I ordered the turkey sandwich with avocado and bacon), the service was rather unattentive -- though well meaning."], "output": "[['lunch', 'neutral'], ['food', 'positive'], ['turkey sandwich with avocado and 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": ["The pastisio platter especially because you get a good amount of salad that's dry as the sahara desert, three wedges of bland potatoes, and a thin slice of microwaved pastisio that was awful for $9."], "output": "[['salad', 'positive'], ['desert', 'negative'], ['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": ["They also have a great deal of 2 cheese slices and a drink for $3."], "output": "[['2 cheese slices', '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 bill came out to like $100pp, and noone touched their food, and drinks were left untouched because after the first bite/sip you want to never touch it again."], "output": "[['bill', 'neutral'], ['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": ["The place was so dark, I needed the table candle to read the menu and could not properly see what I was eating."], "output": "[['place', 'negative'], ['table', '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": ["I recommend the jelly fish, drunken chicken and the soupy dumplings, certainly the stir fry blue crab."], "output": "[['jelly fish', 'positive'], ['drunken chicken', 'positive'], ['soupy dumplings', 'positive'], ['stir fry blue 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": ["I expected high prices at Nello, but as I looked at the menu my eyes became as large as the Birkin Mary-Kate has been seen toting around these days--$18 for soup, $22 for a plate of mixed greens, $40 for pasta."], "output": "[['prices', 'negative'], ['menu', 'neutral'], ['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": ["sometimes i've just ordered arepas and empanadas for my meal; other times, i've split a dinner entree and an appetizer with a friend and been satisfied, since the portions are so huge."], "output": "[['meal', 'neutral'], ['dinner entree', 'neutral'], ['appetizer', '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 grand with a very high ceiling although it is one of those places that they keep so dark you are not really sure what you are eating anyway."], "output": "[['space', 'positive'], ['ceiling', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 choices, and the dining experience lends itself to being a great place for a date, client dinner, parents' dinner or even a start-off to a night out on the town."], "output": "[['dining experience', '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 prices are incredibly reasonable, especially considering the HUGE portions - by noodle soup could have fed both my husband and myself."], "output": "[['portions', 'positive'], ['noodle 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": ["About 10 of us came here for drinks last friday, the atmosphere was good for chatting and hanging out, but not enough lounge or bar space, they should open up the back area w/ more loungable chairs or booths if they want to catch any after dinner sort of bar crowd."], "output": "[['drinks', 'neutral'], ['atmosphere', 'positive'], ['lounge', 'neutral'], ['dinner', 'neutral'], ['bar 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": ["It's a small and quaint place so have your expectations in check, but that doesn't mean anything bad - know going in that you are gonna eat some serious food!"], "output": "[['place', 'negative'], ['check', '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 was not the mistake of the frozen lasagna, it was the icy service of the manager which has spoiled this restaurant for me."], "output": "[['frozen lasagna', 'neutral'], ['service', '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": ["Also, they upped their prices, so I have their old menu, and was surprised when my bill came to over $5 more than it used to (I know, not a huge deal)."], "output": "[['prices', 'negative'], ['menu', '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": ["They crumbed the table once, although it was solied the entire meal."], "output": "[['table', 'neutral'], ['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": ["We asked for more coffee, water and couldn't even get that from our server."], "output": "[['coffee', 'neutral'], ['water', '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": ["It's a great place, the terrific service carried out throughout the night as we sat and got some appetizers and then decided to stay for a bottle too!"], "output": "[['service', '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 Food Regulars swear by the tamales, which are spongy, well-seasoned and pulled from steaming crocks on the counter."], "output": "[['Food', 'positive'], ['tamales', 'positive'], ['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": ["I always listen to the waiters' recommendations, because they're always awesome - either a special or just one of their faves off the menu."], "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": ["Not including the tip for our server, who we saw twice in an hour?"], "output": "[['tip', '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": ["Get a pitcher of red or white sangria and choose from a large selection of tapas."], "output": "[['white sangria', '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": ["Aside from the fact the maitre de claimed the dining room was 'full', we were seated at a great table overlooking the lobby of the hotel and ordered the 5 course tasting menu."], "output": "[['maitre', 'neutral'], ['lobby', '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 only apparent flavor in any of the dishes was heat, and a table of four gourmands left at least half of our meals on our plates."], "output": "[['flavor', 'negative'], ['table', '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": ["Miyagi is my sushi restaurant of choice in the Village; it's never insanely crowded, the service is very sweet (I've never experienced any of the nastiness described in prior reviews), and the tabs are small."], "output": "[['service', 'positive'], ['tabs', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 ceasar salad amounted to some limp lettuce and mayo strewn around a large plate, and the only way I might have died for the mac and cheese is due to natural causes while waiting for it to arrive."], "output": "[['ceasar salad', 'neutral'], ['lettuce', 'neutral'], ['plate', 'positive'], ['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": ["and am content with a dinner of just the grilled tentacles and salad."], "output": "[['dinner', '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": ["The service was non-existant, the manager spent all of his time at the bar."], "output": "[['service', 'negative'], ['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": ["A 3 course-meal took 2 1/2 hours, including 20 - 30 minutes waiting to get the check after dessert."], "output": "[['waiting', '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 then waited until 7:35 before any food arrived at our table, despite the fact that we kept reminding our waitress that we needed to leave by 7:45."], "output": "[['food', 'neutral'], ['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": ["the waitress came to ask me how my NY Strip was, and I could not give her an answer b/c no one gave me a steak knife."], "output": "[['waitress', 'negative'], ['steak knife', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The cupcakes at magnolia's are world famous as of the article in The new york times but although these cupcakes are excellent i would like to say that the people in magnolia's were very rude and another thing was that they were overpriced and this dessert place has very good food!!"], "output": "[['dessert', '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'd recommend getting an appetizer b/c the dinner takes a bit to be cooked, but it was definitely worth the wait."], "output": "[['dinner', '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 waitress was no where to be found at all throughout the course of the meal, did not refill a single drink nor did she bother to inquire about my satisfaction with the food or even bring the check at the conclusion of the meal."], "output": "[['waitress', 'negative'], ['single 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": ["This Restaurant was very  Ask to the waiter or waitress to give you a table in the back room where all the romance of the place is situated with a so-called chimney!!"], "output": "[['waitress', '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": ["very nice servers, but they seemed more interested in conversing with the regulars than bringing food and being attentive."], "output": "[['servers', '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": ["Service was not snooty and you'll be treated the same whether you order one of the $150+ kaiseki dinners or a single entree."], "output": "[['Service', 'negative'], ['kaiseki dinners', '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 crispy fish tacos, the thin-crust pizza with fresh mozzarella, the lobster roll, the bratwurst direct from Indiana."], "output": "[['fish tacos', 'positive'], ['pizza with fresh mozzarella', 'positive'], ['lobster roll', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 a reservation on-line quickly got a call saying that the resturant was under renovation, but the kitchen was still open and was still more than welcome to come enjoy dinner in their lounge."], "output": "[['reservation', 'neutral'], ['kitchen', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 Rack of Lamb, mushroom stuffies, and champagne and she had the Chicken with Soba noodles and baked clams, and merlot."], "output": "[['Lamb', 'neutral'], ['champagne', 'neutral'], ['Chicken with Soba noodles and baked clams', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 calves liver alla veneziana in a fine rich and complex sauce with perfectly fried onions."], "output": "[['calves liver', 'neutral'], ['sauce', 'positive'], ['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": ["A friend of mine and I bumped into this restaurant last week and it didn't look like any special place on the outside, but when we looked at the menu we decided to give it a try."], "output": "[['place', '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 eggplant parmasean was AWESOME (I don't even like eggplant) but my main course was just ok (shrimp with pasta)."], "output": "[['eggplant parmasean', 'positive'], ['main course', 'neutral'], ['shrimp with 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 quality of the sushi was bad, the way it was cut was bad, and the waiters kept trying to clear off my miso soup even when it wasn't finished."], "output": "[['sushi', 'negative'], ['waiters', 'negative'], ['miso 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": ["What do you like more, completely addictive patties of greasy beef, or glasses of cheap refreshing beer to wash it down?"], "output": "[['patties', 'positive'], ['beef', '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": ["The manager apologized and gave us back $20 for the difference, BUT THE WAITER NEVER RETURNED THE $120 CASH WE PAID."], "output": "[['manager', '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 food was great so that made up for the lack of service from the waitress."], "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 defining characteristic of this popular restaurant, aside from dirt-cheap hot dogs, is the beverage selection, which includes a light and refreshing papaya juice, an extremely sweet pineapple juice and a sweet and frothy pina colada drink."], "output": "[['hot dogs', 'positive'], ['beverage selection', 'neutral'], ['papaya juice', 'positive'], ['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": ["Though I wasn't starving, it was still a bit surprising to find four (yes, FOUR) scallops on my plate for dinner."], "output": "[['scallops', '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 party of 7 people for dinner here on a busy night for the restaurant, and our meal was excellent and served with extreme consistency (all appetizers and main courses were served at the right times, with none of the dishes served at the wrong temperature)."], "output": "[['dinner', 'neutral'], ['meal', 'positive'], ['dishes 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": ["I told the waiter that my drink tasted very bad and asked if he could swap it out for a Petron Margarita."], "output": "[['waiter', '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": ["I have eaten here for nearly three years, with firends with family, the service is great attentive and informed, perfect for Thursdays, Fridays and Saturdays."], "output": "[['family', '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 couple of weeks ago we went to Supper in the east village and it was so bad that we got up and left and the only way to save the evening of horrible food was to go to Blue Ribbon Bakery and have at least one thing off the menu."], "output": "[['food', 'negative'], ['Bakery', '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 night I was there, besides extraordinary food and service, the owners; Carmelo Leotta and Pietro Cinquemani were belting out Mario Lanzi tunes on the Steinway piano."], "output": "[['food', 'positive'], ['service', '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": ["The waitress gave us attitude because we orderred the price fix and not the regular menu."], "output": "[['waitress', 'negative'], ['price', '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": ["I won't even wait for an hour and a half when I don't have reservations, but the hostess and the pompous maitre d' just jerked me around and kept on promising me that I'd be the next to be seated."], "output": "[['reservations', 'neutral'], ['hostess', 'negative'], ['pompous 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": ["And with all their recent additions (a jazz bar, and fabulous garden dining) I find that I visit more now than ever."], "output": "[['jazz bar', 'neutral'], ['garden 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": ["I can't imagine waiting for 20 minutes to have my plates removed, given that usually the waitstaff hover around like birds of prey waiting for a fork to drop etc."], "output": "[['plates', '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 strongly recommend dining here, bringing a date, etc; As for me, next time I am going to try the beef from the true Japanese-style charcoal grille!"], "output": "[['dining', '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": ["The waitress could have been more specific when I asked for a wine suggestion."], "output": "[['waitress', 'negative'], ['wine suggestion', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 appeared promptly, took our order, bought us drinks and was never to be seen again."], "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": ["The service can be lacking at times, but the desserts and overall experience certainly counter this flaw."], "output": "[['service', 'negative'], ['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": ["The waiter seemed astounded that I ordered no wine or alcohol -- just water -- with my meal."], "output": "[['waiter', 'negative'], ['wine', '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 a turkey melt, the turkey was fresh, fries were good."], "output": "[['turkey melt', '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": ["Lastly, the bartender didnt give me detailed bill, just my credit card receipt to sign."], "output": "[['bartender', '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": ["00 one does expect more than three small shrimp, one crab cake and two broiled scallops."], "output": "[['shrimp', 'negative'], ['broiled scallops', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 when we showed up the manager told us the wait was over 45 mins."], "output": "[['reservations', 'neutral'], ['manager', '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": ["The wine list was had some of my favorites which I have not seen anywhere in New York, and when I clumsily spilled both water and wine all of the my table the waitress and manager were there in a flash jovially helping me clear up the mess."], "output": "[['water', 'neutral'], ['table', 'neutral'], ['waitress', 'positive'], ['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 also watched several other frustrated customers getting the wrong orders or trying to catch the waiter's attention (he was posing at the soda fountain)."], "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": ["The ambience was all wrong, the bar opened into the main dining room causing the noise to flow into the room."], "output": "[['ambience', 'negative'], ['bar', 'neutral'], ['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": ["yes this place has good pizza but HORRIFIC HORRIFIC delivery service."], "output": "[['pizza', '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 don't remember the dessert item but when it was brought out flashing lights overhead threw colored beams on the walls and a young waiter came over to our table and did a little dance that was Bollywood MTV for the East Village set."], "output": "[['dessert', 'neutral'], ['waiter', 'negative'], ['dance', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The execution in the dining room was on point and we never had any service or food issues."], "output": "[['dining room', '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": ["For the main course, try out the Beef Negimaki."], "output": "[['main course', 'neutral'], ['Beef Negimaki', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 rude, didn't know their drinks and were unable to demonstrate any professionalism in their service mentality."], "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": ["Breakfast, lunch or dinner - Teresa's serves up a hearty meal each and every time."], "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": ["With the large crowds here and the larger menu, be prepared to wait for your dinner to arrive at your table."], "output": "[['crowds', 'positive'], ['dinner', '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 your friends persuade you to check this place out, I suggest that you order all of your drinks, apps, entrees, desserts, and the check up front, because you'll never see your server again."], "output": "[['drinks', '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 manager claimed that he could not compensate us for anything on the bill which just shows the lack of sophistication from the entire group."], "output": "[['manager', '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": ["Our spastic waiter was running around like a chicken with his head cut off, and, thus, slow to take our order, slow to bring us our drinks (they sat on the bar for 5-10 minutes) and slow to get us the water we had to ask for repeatedly."], "output": "[['waiter', 'negative'], ['drinks', 'neutral'], ['bar', '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": ["Our waitress was very nice, not snotty - she even gave us a free apertif after the meal (and left the bottle on the table)."], "output": "[['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": ["We recently had brunch at this establishment with two other couples and I have to say I was majorly dissapointed with the service and how we were treated."], "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": ["Just sit at the bar and sip some amazing Italian wines."], "output": "[['bar', 'neutral'], ['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": ["However when the party was complete we had the other waitress come over who said that we had to order all the food at once and couldnt order just appetizers."], "output": "[['waitress', 'negative'], ['food', '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": ["The waiter kept coming up and asking to take our plates while we were still eating and the manager stood and stared at us through half our meal!"], "output": "[['waiter', 'negative'], ['plates', 'neutral'], ['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": ["Nice decor - but the place is so crowded and noisy you can't enjoy it."], "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": ["I will be back not only because the price was so unbelievable but the atmosphere was just plain COOL and the food was spectacular."], "output": "[['price', '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": ["The piano guy isn't there all the time, but when he is it's a great addition to the meal."], "output": "[['piano', '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": ["When my brother and I we had too much pizza in New York, we would like to order something else from the menu."], "output": "[['pizza', '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's a very chill spot to hang with a group, I went there with a bunch of my friends to have drinks for my birthday and we all had a great time."], "output": "[['spot', 'positive'], ['drinks', '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 nachos were very very good, but the onion bloom felt too greasy and the calamari was soggy."], "output": "[['nachos', 'positive'], ['onion bloom', 'negative'], ['calamari', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 features a wide array of Hawaiian- and Asian-flavored appetizers and entrees."], "output": "[['Food', 'neutral'], ['array', '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": ["Our waiter was not attentive, we waited about 20 mins just to order 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": ["Asked for wine recommendations and the waitress told me her favorites and described them in detail - I don't encounter this much in NYC."], "output": "[['wine', '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 was surprised by the small ice cream dessert from the restaurant to the birthday girl free of charge, but if they're going to give a nice service the one ice cream scoop on a stick didn't leave a strong enough impression."], "output": "[['ice cream dessert', 'positive'], ['service', 'positive'], ['ice cream scoop', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 on a delicate lamb carpaccio, and grilled skate wing, the owner explained that due to low lunch-time patronage, they may be discontinuing lunch altogether."], "output": "[['dining', '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": ["I was told(very snottily) no, but then not even 10 minutes later another group of people came in, asked the same thing and because the same woman waiter knew them she gave them regular menus!"], "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": ["Seating is usually very prompt but expect a wait at peak times such as Sunday Brunch."], "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 service was less than spectacular (two waiters fought in front of us over which one got our table) and the bread put out as an appetizer was sub-par."], "output": "[['waiters', 'negative'], ['bread', '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": ["The atmosphere's a bit grungy, yes, but the music and the coffee are good."], "output": "[['atmosphere', 'negative'], ['music', 'positive'], ['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": ["Other temptations include spumoni, tortoni, cannoli, cookies (try the pinoli), tarts and fluffy white cakes to order."], "output": "[['cannoli', 'neutral'], ['cookies', 'neutral'], ['white 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": ["The menu ranged from standard (steak, duck and mussels-all fantastic) to curious (ostrich-awesome, and tartare-smoked not raw but still so good."], "output": "[['menu', 'neutral'], ['steak', '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": ["The food is decent, average bistro food, the decor is nice, but the service is poor, the waiters always seems to have to many tables andcant keep up with a good services."], "output": "[['bistro food', 'neutral'], ['decor', 'positive'], ['waiters', '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": ["It took 1 1/4 hours to get our appetizers (how long does salad take) and when we complained to the manager, he barely listened."], "output": "[['appetizers', 'neutral'], ['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": ["I would have told the wait staff if anyone had asked me if I enjoyed my meal, but no one asked."], "output": "[['wait staff', '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": ["This time, the service was decent and the food was mediocre at best."], "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 food was pretty good, but due to our large size (~16) the manager asked us to limit our appetizers to just 3 selections b/c he didn't want to overburden his cooks."], "output": "[['manager', '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": ["It is always hard to find a seat and the selection is not that great but it is one of the few places to get lunch for only a buck."], "output": "[['seat', 'neutral'], ['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": ["I love the food here, and although it is pricey, the entree comes with rice, naan, dal, and salad, which makes it worthwhile."], "output": "[['food', 'positive'], ['entree', 'neutral'], ['naan', 'neutral'], ['d al', '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": ["I'm not a fan of any of their appetizers or Thai food, but their Japanese food is great."], "output": "[['appetizers', 'neutral'], ['Thai food', 'neutral'], ['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": ["A bustling crew of sage green-shirted servers whisk plates of luncheon and light dinner favorites to power lunchers, tourists, and ladies who lunch."], "output": "[['crew', 'negative'], ['servers', 'negative'], ['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": ["our waiter forgot a dish and we were constantly checked on afterwards and treated to a complimentary dessert for the mix up."], "output": "[['waiter', 'negative'], ['dish', 'neutral'], ['dessert', 'neutral'], ['mix up', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Black Duck is a great date place, whether going for dinner or just for a drink at their huge, antique-ish bar."], "output": "[['Black Duck', '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": ["I understand the area and folks you need not come here for the romantic, alluring ambiance or the five star service featuring a sommlier and a complicated maze of captain and back waiters - you come for the authentic foods, the tastes, the experiance."], "output": "[['ambiance', 'positive'], ['service', 'positive'], ['sommlier', 'neutral'], ['captain', 'positive'], ['back waiters', 'neutral'], ['foods', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 two entrees that were ordered were very large portions."], "output": "[['entrees', '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": ["Tried it again for brunch, when the service was worse."], "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": ["the service is pushy and the food looks good but is completely average (chewy steak, tasteless rice and beans)."], "output": "[['service', 'negative'], ['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": ["however, we went for lunch and were the only ones eating there and yet the service seemed eager for us to be done and to get out."], "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": ["Downtown Dinner 2002 - Prixe fix: Appetizers were ok, waiter gave me poor suggestion."], "output": "[['Dinner', 'neutral'], ['Appetizers', '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": ["Perhaps if the owner manager would concentrate more on service then acting as a dj this restaurant would run better."], "output": "[['owner manager', 'neutral'], ['service', 'negative'], ['dj', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 at the table our waitress managed on two occasions to take 15 minutes bringing drinks to our table, our plates sat uncleared on the table for just as long."], "output": "[['waitress', 'negative'], ['drinks', '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": ["nice place, good service but the price is a little bit more expensive when compare with the area, location and small dishes."], "output": "[['service', 'positive'], ['location', '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": ["My boyfriend and I went one Friday night to find that the place was empty except for one other table."], "output": "[['place', '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 servers and/or bus persons dart back and forth through the dining room, never even making eye contact to see if you have any needs."], "output": "[['servers', '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": ["The atmosphere could be considered amiable, if you possess roguish frat-boy nostalgia."], "output": "[['atmosphere', 'positive'], ['nostalgia', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 in a few times for brunch as it does get quite busy, it's worth it though especially now that they have those amazing Blueberry Waffles."], "output": "[['brunch', 'neutral'], ['Blueberry Waffles', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 scoop on this new hot spot and decided to give it shot for a client dinner."], "output": "[['spot', '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 waiters knocked over my purse 3 times and spilled water on the table 3 times as well."], "output": "[['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": ["This is definitely a special occasion spot, unless you don't mind a hefty bill, but rest assured that either way, it's well worth it."], "output": "[['spot', '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 didn't really know the menu and was not attentive."], "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 place was packed but we were able to get drinks at the bar w/out a problem despite the crowd."], "output": "[['place', '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": ["Mussels in deeply aromatic lemongrass broth make an excellent starter, as do the light and spicy house samosas."], "output": "[['Mussels', 'neutral'], ['starter', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 a chef from Liguria, Italy, authentic Neapolitan brick oven pizza and one of the most impressive Italian wine lists I've ever seen, this was the real deal!"], "output": "[['chef', 'neutral'], ['brick oven', '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": ["Very cheesy wanna be romantic decor and entertainment, but have some vodka and you want to come right out onto the dance floor and dance the night away to a mix of really bad russian and american disco music."], "output": "[['decor', 'positive'], ['entertainment', 'positive'], ['dance floor', 'neutral'], ['disco 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 was beautiful, I sat at the bar for two hours and eat oysters and had way too many martinis."], "output": "[['place', '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": ["The menu had some slight twists to conventional upscale Mexican."], "output": "[['menu', 'neutral'], ['Mexican', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 inexcpensive that you'd wonder about the sanity of the owners, if they weren't such good cooks."], "output": "[['owners', 'neutral'], ['cooks', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 came out cold and the waiter came and took it to the kitchen."], "output": "[['appetizer', '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": ["The food is delish, you just have to know the manners to consume, if you don't want to be frustrated with the service."], "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 food was served in small portions and my lamb was pure fat."], "output": "[['food', 'neutral'], ['portions', 'negative'], ['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": ["Invited by friends to discuss business, I checked out the bar first, and didn't give my nme which was known to the owners Scott Heather."], "output": "[['bar', '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": ["Bins of fresh bagels rest behind the counter, and there are always a few customers sitting at one of the few tables inside or on one of two wooden benches out front."], "output": "[['bagels', 'positive'], ['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 food makes up for it, though the quality has fallen victim to it's success."], "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": ["A hour passed until the waitress came over to give us menus and tell us she would be right back another hour later After trying to order fish she informed us that all fish entrees on the menu was sold out We took a minute to make a second choice and tried to order something else that we were told was also sold out."], "output": "[['waitress', 'negative'], ['menus', 'neutral'], ['fish 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 only dishes that were good were the chicken kebob (not hard to make) and the desserts, which were rice pudding."], "output": "[['dishes', 'positive'], ['desserts', 'negative'], ['rice pudding', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Raymunds dishes up the best Polish comfort food Ive ever had outside of my great-aunts kitchen."], "output": "[['dishes', 'neutral'], ['Polish comfort food', 'positive'], ['kitchen', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 took our waiter 10 mintues to get us a menu, 15 minutes to come back for our order, by the time we finally got our food it was almost 1 1/2 hour since getting there."], "output": "[['waiter', 'negative'], ['menu', '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": ["2 weeks ago, I decided to set up a birthday dinner in this establishment and was wary with the reviews I've read in City Search but it seems to be a perfect scene."], "output": "[['dinner', '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": ["While there's a strong Asian influence behind many of the plates, you can't pigeonhole the food into a single genre, as there are Thai, Chinese, Japanese, Italian and American dishes incorporated into this creative menu."], "output": "[['plates', 'neutral'], ['food', 'neutral'], ['Japanese', '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": ["Moules were excellent, lobster ravioli was VERY salty!"], "output": "[['Moules', '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": ["A little pricier than most veggie restaurants, but worth it if only for the dessert menu (as a wheat-sensitive, diabetic vegan, there aren't too many places I can even LOOK at desserts, and this may be the only one where I can actually EAT what they serve me."], "output": "[['veggie', 'neutral'], ['dessert menu', 'positive'], ['vegan', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 from the barbecued lamb at $13."], "output": "[['food', 'positive'], ['barbecued 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": ["Despite being the only people in the restaurant on an early sunday afternoon, the service felt as if there was a 2-hour wait on a friday night."], "output": "[['service', '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": ["For lunch, opt for an outstanding, triple-decker roast turkey club or brioche burger with skin-on fries."], "output": "[['lunch', 'neutral'], ['triple-decker roast turkey club', 'positive'], ['brioche burger', 'neutral'], ['skin-on 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 WAITRESS BROUGHT THE WRONG PIZZA, THE WRONG SALAD, AND FORGOT THE DRINKS."], "output": "[['WAITRESS', 'negative'], ['SALAD', '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": ["You'll find good curry dishes and their fries (made out of sweet potato) is to die for."], "output": "[['curry dishes', 'positive'], ['fries', 'positive'], ['sweet potato', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 Skip the menu and head for the restaurant's bountiful and ever-changing vegan buffet for an abundance of affordable servings."], "output": "[['Food', 'neutral'], ['menu', 'neutral'], ['servings', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 so fantastic that once we heard they were serving dinner we decided to go one night and try it out."], "output": "[['space', 'positive'], ['serving 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 don't want to wait 45 minutes for a table or a long time for service then don't go @ 9pm on a Friday or Saturday night."], "output": "[['table', '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 is quite substantial, with a number of chicken, beef, and seafood specialties not found at your typical chinese restaurant."], "output": "[['menu', '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": ["We initially ordered a bottle of wine and the waitress though we may not like it, so she offered us a taste."], "output": "[['waitress', '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 portions are small but being that the food was so good makes up for that."], "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": ["The ravioli was the better of the two, but the serving was tiny, and the skin a bit rubbery."], "output": "[['ravioli', 'positive'], ['serving', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 on 1st floor (street level) a bit noisy, 2nd floor has bed-style seating that is good for dessert drinks (do not attempt to have entree on the bed, what a mess it will be trying to eat rice dishes with sauce while half-lying down)."], "output": "[['dinner', 'neutral'], ['dessert drinks', 'positive'], ['rice 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 waiters have been there for YEARS and they know their steak is amazing."], "output": "[['waiters', '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": ["(I will say, the waitress was very sweet and did try to compensate for the chef and owner's poor beh- we gave her a big tip)."], "output": "[['waitress', 'positive'], ['chef', 'negative'], ['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": ["Amusing details distinguish desserts, from dulce de leche ice-cream profiteroles dotting a chocolate sauce tic-tac-toe board, to coconut custard surrounded by a sea of Malibu-rum gelee and poached pineapple."], "output": "[['desserts', 'positive'], ['dulce de leche ice-cream', 'neutral'], ['chocolate sauce tic-tac-toe', 'neutral'], ['poached pineapple', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 about a 1/2 block from Westway and when I want consistantly good food, big portions, great fast service and a step above your average diner food I go there!"], "output": "[['portions', 'positive'], ['service', 'positive'], ['diner 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 politely asked our server for the regular menu, but were told that for large parties they could only offer us the banquet menu (would have gone elsewhere had we known)."], "output": "[['server', 'negative'], ['banquet 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 never came back to get drink refills and we didn't get water until we were halfway through our dinner."], "output": "[['waitress', 'negative'], ['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": ["We were immediately seated (the restaurant was no where close to being packed, surprise, surprise) There are very few selections on the menu and the food is not that great and the dining experience at Butter is completely overrated."], "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": ["Our waiter never once asked how everything was, as I suspect he knew the kitchen was producing seriously average food."], "output": "[['waiter', 'negative'], ['kitchen', '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": ["Main courses we had (beef, lobster sukiyaki, black seabass, striped seabass) tasted too much like homestyle authentic Chinese food except for the sukiyaki."], "output": "[['beef', 'neutral'], ['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": ["I paid $12 including tax tip for a beef entree with salad, noodles, rice, a fried dumpling, many free appetizers and a glass of ice water."], "output": "[['tip', 'neutral'], ['beef entree with salad', 'neutral'], ['noodles', 'neutral'], ['rice', 'neutral'], ['fried dumpling', '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": ["Food was much better than the average Indian place in the area, and more interesting."], "output": "[['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": ["When I asked the manager to remove the coffee, she did so without question, but never asked why and never followed up on the issue (she was far too busy flirting with the male waiters)."], "output": "[['manager', 'negative'], ['coffee', 'neutral'], ['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": ["The waiter recommended I choose a bottle for the entire 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": ["The Food The menu lists affordable soul food and barbecue favorites."], "output": "[['menu', 'neutral'], ['soul 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 for the food, brunch was average, I would not get the same dish again, and they were slow to serve us."], "output": "[['brunch', '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": ["For example, we had ordered a 2nd bottle of red wine, the waitress gave me a new glass to taste the wine, but filled up my existing glass (mixing two different bottles in one glass)."], "output": "[['bottle of red 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": ["The Food Consulting Chef Douglas Rodriguez's forte is blending the diversity of traditional Latin cuisine with modern culinary chic: A celery sorbet cools the spicy-citrus bite of lobster; shrimp seviche and crunchy green plantains coat thick, juicy halibut resting on sweet plantain hash; and tart tomato escabeche moistens a chewy skirt steak."], "output": "[['Food', 'positive'], ['Chef', 'neutral'], ['traditional Latin cuisine', 'positive'], ['sorbet', 'positive'], ['shrimp seviche', 'positive'], ['green plantains coat', 'positive'], ['halibut resting', 'positive'], ['sweet', 'positive'], ['tart tomato escabeche', 'positive'], ['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": ["Next, follow up with another Cosmo and try the chicken fingers (not your lil brothers), Hawaiian rib eye, filet mignon, or trusty burger."], "output": "[['chicken', 'neutral'], ['Hawaiian rib', '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 waiter was very attentive and always kept the bread and drinks coming."], "output": "[['waiter', '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": ["However, another server kept hovering over our table, wanting to take our half-finished plates away."], "output": "[['server', '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": ["Their bagels have the perfect softness to them, but on the outside there's a bit of crispiness to give it a bit of texture."], "output": "[['bagels', 'positive'], ['texture', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 Server informed us that they wanted to make the soup their own and that she hopes we like it."], "output": "[['Server', '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": ["You need just witness the classic wall of celebrities, or the Sinatra playing over the speakers to know you're in an authentic pizza joint."], "output": "[['Sinatra', 'neutral'], ['pizza joint', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 ignored by our waiter we complained to the manager who assured us everything would improve."], "output": "[['waiter', '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": ["The hostess failed to give us menus, and we had to ask our waiter for them."], "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": ["I don't even think I would have minded waiting at the bar for over an hour if it weren't so crowded and if they had little tapas for the hungry people forced to wait!"], "output": "[['bar', 'neutral'], ['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": ["I have no complaints about the wait or the service but the pizza was not at all something to write home about."], "output": "[['wait', 'positive'], ['service', '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": ["Everything from the food to the service was enjoyable about this place, but I can't recommend the tempura shrimp roll with the lobster salad enough."], "output": "[['food', 'positive'], ['service', 'positive'], ['tempura shrimp roll', 'negative'], ['lobster salad enough', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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, I went down on a Wednesday night to see if they had a long wait and the hostess said they had a table to accomodate my party."], "output": "[['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": ["On Friday night the busboy was sulky verging on rude; he brought the fries (ordered for the entrees) twice before the appetizers came and then again the minute we'd finished them and looked put out to be asked to take the empty plates away."], "output": "[['busboy', '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": ["I always thought the food was decent, but not spectacular and the price fair, but no bargain."], "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": ["Watch out for the overworked, stressed out waitress who dumps tapa dishes on the table and leaves w/out announcing what it is."], "output": "[['waitress', 'negative'], ['dishes', '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": ["Fortunately the waitress was very ncie about this, and did not give me a hassle about taking the cake off the final bill."], "output": "[['waitress', '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 old menu items are gone, except for the rib appetizer, which is now bland and fatty, with little trace of the excellent mustard sauce."], "output": "[['menu items', 'neutral'], ['rib 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": ["The wait staff is slow, full of attitude and forgettful--often taking 20 minutes to bring another round of food and drinks."], "output": "[['wait staff', '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 inattentive throughout the meal, took nearly 3 hours for dinner."], "output": "[['waiter', 'negative'], ['meal', '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": ["In Short The much-copied look of hardwood floors, decorative stained glass, checked tablecloths, brass rails and walls filled with knickknacks has been a staple at this restaurant franchise."], "output": "[['stained glass', '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": ["Pair you food with the excellent beers on tap or their well priced wine list."], "output": "[['food', 'neutral'], ['beers on tap', 'positive'], ['priced 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": ["They were out of Hennessy, Alize, Mojitos, Pinot Grigio and the list goes on and on with at least 20 other liquors that they did not have, not to mention the drink list is very limited and does not include a wide selection of interesting drinks."], "output": "[['Mojitos', 'neutral'], ['Pinot', 'neutral'], ['drink list', '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']] "}