{"task_type": "generation", "dataset": "mams", "input": ["After a couple of drinks, the apps--I like the lobster/mango summer roll and the cripsy squid--go down great."], "output": "[['drinks', 'neutral'], ['roll', 'positive'], ['cripsy squid', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The basil pepper mojito was a little daunting in concept, but I was refreshed at the flavor."], "output": "[['basil pepper mojito', 'negative'], ['flavor', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Had to constantly ask the waiter to top up water glasses, but generally service was ok."], "output": "[['waiter', 'negative'], ['water glasses', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The portions were so small that we still wanted to eat after dinner."], "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 staff is very kind and well trained, they're fast, they are always prompt to jump behind the bar and fix drinks, they know details of every item in the menu and make excelent recomendations."], "output": "[['staff', 'positive'], ['bar', 'neutral'], ['drinks', '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": ["On the other hand, the soup was so clear and you taste no salt."], "output": "[['soup', 'positive'], ['salt', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 out on the town with the idea that we were going to mingle with the in crowd, you know, go to a place where you pay an outrageous cover charge, have to wear all black to fit in, and pay $12 for a watered-down martini, and if you're lucky, have a good time."], "output": "[['watered-down martini', '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 waiter had a slight attitude and brought our wine aprroximately 10 minutes into our appetizer."], "output": "[['waiter', 'negative'], ['attitude', 'negative'], ['wine', 'neutral'], ['appetizer', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Appetizers and entrees were merely adequate, but you can't beat the pool room for atmosphere."], "output": "[['Appetizers', '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": ["However for the price I paid to have dinner there, you would have thought I ate a horse."], "output": "[['price', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I called to confirm the reservations on the morning of the lunch and the hostess had the reservations set for 12:30pm which I quickly corrected."], "output": "[['lunch', 'neutral'], ['hostess', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The small bar is always packed with people, and you have to constantly contend with waiters asking you to move as they navigate through the crowd to make it to their tables."], "output": "[['bar', '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": ["Regardless of the amount of customers, the wait for food is insanely long."], "output": "[['wait', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the decor isn't quite like Shun Lee but the service will definitely make up for any shortcoming."], "output": "[['decor', 'negative'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["And there wasn't much room for the people at the bar to stand either, as the restaurant attempted to squeeze as many tables into the restaurant as they could, forcing those dining to have to shift in their chairs every time a waiter attempted to get by."], "output": "[['bar', 'neutral'], ['tables', 'neutral'], ['dining', 'neutral'], ['chairs', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In Short It's a bakery, takeout place and cafe all in one, and thanks to dishes prepared using the same ingredients stocked at famed gourmet food emporium, Zabar's, prices and quality are upscale."], "output": "[['place', 'neutral'], ['dishes', 'positive'], ['ingredients', 'neutral'], ['prices', '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": ["But it's the ambience that is the draw for me---sipping red wine and sitting under the red awning on a warm night."], "output": "[['ambience', 'positive'], ['red wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service was fine, out appitizers took forever to come out, and then they dumped the rest of the food on us, without giving us a chance to enjoy our appitizers."], "output": "[['service', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The servers, casual in their striped button-downs, anticipate and fulfill needs as if they were trained as mind readers."], "output": "[['servers', 'negative'], ['striped button-downs', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food did come out quickly and was good, but not worth the prices or the wait."], "output": "[['food', 'positive'], ['wait', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The fries were absolutly inedible, and the coldslaw tasted like it was straight out of a bucket from Sam's, and the friend shrimp had too much curry."], "output": "[['fries', 'negative'], ['shrimp', 'neutral'], ['curry', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["my one complaint is that when we were finished with our dinner, it took an abnormally long time for our waitress to get with the program and bring us our check."], "output": "[['dinner', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["But wait, it gets even better, the mussels were so fishy that I had the server try one since he had a hard time believing that this was true."], "output": "[['wait', 'neutral'], ['mussels', '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": ["This place happens to be beatifully designed, the atmosphere is relaxed (as opposed to the noisy community dining atmosphere in so many busy chinese reataurants - which can also be OK) the food is authentic Chinese as opposed to what they think Americans would like, the staff is friendly and unhurried."], "output": "[['community dining atmosphere', 'negative'], ['food', '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": ["Please have the SPINACH DIP, CAESAR SALAD, HAWAIIAN RIB-EYE and the BROWNIE for dessert."], "output": "[['SPINACH DIP', 'positive'], ['CAESAR SALAD', 'positive'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere is warmly dim and inviting - if you make a reservation, ask for a corner both for extra coziness!"], "output": "[['atmosphere', 'positive'], ['reservation', 'neutral'], ['corner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["but we waiting two hours to get it (we had reservations but it was late so we wanted to try to come in earlier)."], "output": "[['waiting', 'negative'], ['reservations', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitress at the bar was very nasty to me because she mistakenly took an order for thai ice tea from me when I asked for thai lemonade in a to-go cup."], "output": "[['waitress', 'negative'], ['bar', 'neutral'], ['thai lemonade', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 bi-level dining room, which resembles a bamboo-thatched hut, is a brightly-lit, wide-open space with high ceilings and laminated depictions of Indian village life."], "output": "[['bi-level dining room', 'neutral'], ['space', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Superfine is my preferred destination in the city when I'm looking for a casual, hip atmosphere, extraordinary food at decent prices and/or just a place to get a good drink, chat with the bartender and shoot some (free) pool."], "output": "[['atmosphere', 'positive'], ['food', 'positive'], ['prices', 'positive'], ['bartender', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["An otherwise fine meal was trashed when i realized that the dish i had ordered contained chicked, despite my asking for no chicken, no pork twice."], "output": "[['meal', 'positive'], ['dish', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food The key element to a proper British chip is fat, and the flabby, pale yellow specimens here come close to the ideal."], "output": "[['Food', 'neutral'], ['specimens', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The dinner menu looks like it has a more interesting selection of entrees, but if they are even the fraction of the quality of the items we ate for lunch, I whole-heartedly advise you to make it a point and dine at Creama--if not for the drinks, then definitely for the unique approach to mexican."], "output": "[['entrees', 'positive'], ['quality', 'positive'], ['lunch', 'neutral'], ['mexican', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We made a reservation for 5:30pm (20 people) and people were still arriving at 5:45 (over half the group was there) when the manager came over and literally yelled at us for not being on time saying it was a busy time for him, when in fact there were several empty tables throughout the restaurant."], "output": "[['reservation', 'neutral'], ['manager', 'negative'], ['tables', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When I went for sunday brunch, not only was the food bland and cold, they didn't even bother to clear the plates once they brought the bill."], "output": "[['brunch', 'neutral'], ['food', 'negative'], ['plates', 'neutral'], ['bill', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Wasa Waffle was different but when we spoke to the manager he inmediatly changed if for another dish (He suggested the Chocolate decadence French Toast."], "output": "[['Wasa', 'neutral'], ['manager', 'positive'], ['dish', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The pizza is thet always fresh and just made they hav an outdoor seating area that is partially covered they also have a full service restaurant on the premises they make everything on premises."], "output": "[['pizza', 'positive'], ['outdoor seating area', '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": ["Consistently satisfying versions of Thai staples like pad Thai and curry dishes arrive in generous portions."], "output": "[['Thai staples', 'positive'], ['pad Thai and curry dishes', 'neutral'], ['portions', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I naively thought dinner was served during the show, but the waiters don't come by once the shows start, so order your wine 30 mins before the show start time."], "output": "[['dinner', 'neutral'], ['served', 'neutral'], ['waiters', 'negative'], ['wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu is limited so I opted for the jalapeno potato soup and a romaine salad."], "output": "[['menu', 'negative'], ['romaine 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": ["Other guests enjoyed pizza, santa fe chopped salad and fish and chips."], "output": "[['pizza', 'positive'], ['santa fe chopped salad', 'positive'], ['fish and chips', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The items available during dimsum time were plentiful - the turnip cake was excellent."], "output": "[['dimsum', 'neutral'], ['turnip cake', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I would recommend going at off-times (before 7 perhaps) to avoid the crowds as it gets packed and there isn't much room by the bar."], "output": "[['crowds', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I mean no disrespect to the owner, just constructive criticism - improve the decor and dine-in service, but DON'T change the portions or the recipes."], "output": "[['decor', 'negative'], ['portions', 'neutral'], ['recipes', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 no point during our dinner were we left alone to simply enjoy our food."], "output": "[['dinner', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Waitress didn't know anything about the menu, but other than that I would recommend."], "output": "[['Waitress', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["With tacky kitsch as the decor's dominant motif and the obligatory grousing waiters hustling out brick-sized steaks and icy vodka to gussied-up regulars and tourists, an evening at Sammy's is both dinner and street theater."], "output": "[['decor', 'negative'], ['obligatory', 'negative'], ['waiters', 'negative'], ['vodka', '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": ["Handsome baritone Nordic waiters patrol the room, proffering fresh-squeezed juices and $4-a-person pots of French press coffee."], "output": "[['waiters', 'positive'], ['press 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": ["Although it was quite good, the small portions at this table of 4, including appetizers, did not constitute adequate sustenance."], "output": "[['portions', 'negative'], ['appetizers', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The green hair table and seating at the front window was tacky and gimmicky, but figured it's the food that counts."], "output": "[['green hair table', 'negative'], ['seating', 'negative'], ['front window', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was average: the almond crusted halibut was bland, while the sashimi appetizer was excellent."], "output": "[['almond crusted halibut', 'negative'], ['sashimi 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": ["First, the hostess gave us a nasty look when asked if we could eat at the bar, and then just swished her hand to indicate we could seat ourselves."], "output": "[['hostess', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Despite him not being my designated server, he basically took over for our inexperienced waiter the rest of the dinner."], "output": "[['server', 'positive'], ['waiter', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After requesting to be seated at an empty table, the waitress (who was so terribly burdened when we asked to move from the bar to the table to have dinner) asked us to get up from our seats and wait for a smaller table because a party of 3 just walked in."], "output": "[['waitress', 'negative'], ['bar', '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": ["Sat at the bar and orderd a few appetizers, the humus and cheese plates along with some calamari - all very tasty."], "output": "[['bar', 'neutral'], ['humus and cheese plates', 'positive'], ['calamari', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the hostess is rude as can be, the waiters can't stop to check in, the busboys are flinging stuff on your table, and that's true even when the restaurant is half empty!"], "output": "[['busboys', '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": ["Call it a bar with weak but tasty sangria and leave it at that."], "output": "[['bar', 'neutral'], ['sangria', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For $65, you will get a 5-6 course tasting menu encompassing a variety of raw fish, cooked fish, pastas, dessert, etc."], "output": "[['menu', 'positive'], ['raw fish', 'positive'], ['pastas', '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": ["Never on the menu or in my inquiry to the waitress was the word garlic mentioned."], "output": "[['menu', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["i was at opia january 5, 2006 we had some drinks, dinner, i have to say that we had me and my friend great time, the staff was listening, the manager knew what he was doing and the food better than ever!!"], "output": "[['drinks', 'neutral'], ['dinner', 'neutral'], ['staff', '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": ["It wasn't until we spoke with management that we were able to finish our meal and get out of the restaurant, but already one of our party had to leave early and the rest of us were late for our afternoon engagements."], "output": "[['management', 'negative'], ['meal', 'neutral'], ['engagements', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It is a must for lunch,dinner or anytime you have a big appetite and don't want to spend big bucks in the big Apple!"], "output": "[['lunch', 'neutral'], ['dinner', 'neutral'], ['Apple', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 it lacks in decor it more than makes up in the cuisine."], "output": "[['decor', 'negative'], ['cuisine', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Went for lunch the bartenders were great, also they had a DJ playing music during the day, there was a Huge screen tv playing music videos and a bunch of other tvs with all the sports you could look at."], "output": "[['lunch', 'neutral'], ['bartenders', 'positive'], ['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": ["The waitress encouraged to come for dinner and brunch, and I followed her recommandation."], "output": "[['waitress', 'positive'], ['dinner', 'neutral'], ['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": ["Our waiter was very prompt and friendly, but the worst part of the experience was actually after the meal when I was leaving."], "output": "[['waiter', '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": ["Me and my wife we go there at least once a month, the food they give you is amazing we only get one order of pasta and main course it is enough for both to share,we get full and satisfied, our favorite dish penne with pesto."], "output": "[['food', 'positive'], ['pasta', 'neutral'], ['main course', 'neutral'], ['dish', 'positive'], ['pesto', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 has always been outstanding and even when we didn't have a reservation they worked something out, where I agreed to keep our meal to just eating."], "output": "[['service', 'positive'], ['reservation', '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": ["the hostess wasn't sure until 3 hours later 10:28: Here we go Eggplant parmigiana fried grease an heavy duty Pollo dish covered with 1/4 of a pound of mozzarella."], "output": "[['dish', 'negative'], ['mozzarella', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Once we ordered, it took at least 30 minutes to get our food, with our server no where in site."], "output": "[['food', 'neutral'], ['server', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Thanks to waiter I learned so much about wine too."], "output": "[['waiter', 'positive'], ['wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Down right comfortable, pleasant, enormous portions, have lunch and bring home a doggie bag wth your dinner."], "output": "[['portions', 'positive'], ['lunch', 'neutral'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A couple of hints: 1) avoid going during peak lunch and dinner hours - everything is made fresh so it takes time, 2) definitely try their Concrete desert - my favorite is chocolate with bananas and hot fudge mixed in."], "output": "[['lunch', 'neutral'], ['dinner', 'neutral'], ['chocolate', 'positive'], ['bananas', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We felt the waiter and captain rushed us through our meal."], "output": "[['waiter', 'negative'], ['captain', '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 desserts are just as good as all the coffee shops around town but they charge more than anyone."], "output": "[['desserts', 'positive'], ['coffee', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["You might be lucky enough to hear your waiter say, May I take zee order from you, Pig Dog, while you're there."], "output": "[['waiter', 'negative'], ['Pig Dog', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Recommended to those who want to try a different setting for a diner."], "output": "[['setting', 'positive'], ['diner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Definitely one of the Slope's best bets for Chinese food -- or for vegetarians (there's an extensive veggy menu, as well as many meat dishes)."], "output": "[['Chinese food', 'positive'], ['menu', 'positive'], ['meat dishes', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In the main dining room, finding your waiter is Hell and aside from when they take your order and bring the bill, you'll rarely see them."], "output": "[['main dining room', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had a five-course dinner and none of the dishes really impressed except maybe the signature oysters and pearls."], "output": "[['five-course dinner', 'neutral'], ['dishes', 'negative'], ['signature oysters', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is pretty good, but the staff would rather be anywhere than waiting tables at Maison."], "output": "[['food', 'positive'], ['staff', 'positive'], ['waiting 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 went there for lunch on a quiet weekday afternoon and everything my friend and I ordered was immaculately presented and absolutely delicious-- I had moules frites and she had the salmon burger."], "output": "[['lunch', 'neutral'], ['weekday', 'positive'], ['moules frites', 'positive'], ['salmon burger', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the food is not nearly good enough to wait an hour before seeing your server, or wait another hour for the wrong entrees, or for the manager to make up for it by charging for everthing but giving us on the house shot glasses of watery margaritas."], "output": "[['food', 'negative'], ['server', 'negative'], ['entrees', '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": ["And although I've noticed that the prices have gone up a little since they opened, it's still a great menu."], "output": "[['prices', 'negative'], ['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": ["For dinner I recommend Carne Tampiquea (steak) And for brunch the Huaraches with meat and a couple eggs on top, a typical mexican hangover plate!"], "output": "[['dinner', 'neutral'], ['brunch', 'neutral'], ['eggs', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Even with reservation, it might take up to one hour to get a table and the staff might not even say a word about it."], "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": ["The food is above average, though the portions a tad small, even for tapas; but they more than make up for it with their wonderfull mojitos."], "output": "[['portions', 'negative'], ['mojitos', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["as for the people whom posted about the salad, I never had it, as for the person that had no sides with the steak, they must have made a mistake, everytime I go its come's with awesome potatoes."], "output": "[['salad', 'neutral'], ['steak', 'neutral'], ['potatoes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service was adequate though we did need to keep asking for water and the drinks from the bar took a long time- plus the restaraurant was not crowded."], "output": "[['service', 'negative'], ['drinks', 'neutral'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The arrogant maitre'd was annoyed when i asked about sitting down those tables are for other reservations low and behold those tables were still open as my wife and I finished dinner."], "output": "[['maitre', 'negative'], ['reservations', 'neutral'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have been here a few times and never had a boring meal!Food always fresh, service very civilized."], "output": "[['meal', '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": ["Over a period of time some restaurants tend to loose the quality of the taste of their food, but not Ray's."], "output": "[['quality', 'negative'], ['taste', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The manager very politely told the drunk man that he could leave and then gave everyone on the resturaunt a free glass of port for having to witness it."], "output": "[['manager', 'positive'], ['glass', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Save the $$ and go to to curry hill (just 2-3 blocks away) or spend the $$ at a midtown indian eatery  (Also: I commented to hostess prior to seating that there were a lot of tables empty when choosing my seat, and she snapped back that they had a lot of reservations coming in at one time."], "output": "[['hostess', 'neutral'], ['seating', 'neutral'], ['tables', 'negative'], ['reservations', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["An unfriendly hostess greeted us and placed us in the main room of the restaurant where the tables were so close together that it was impossible for guests and waiter to move without bumping you."], "output": "[['hostess', 'negative'], ['tables', '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": ["All in all the food was above average and I would return to see how they operate with four or less dinners."], "output": "[['food', 'positive'], ['dinners', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It took forever to seat us even though the restaurant was almost completely empty, then we had to ask to be waited on, it took another 15 minutes to get our drinks, and then another 30 minutes to get our salad and then even more time to get our pizza and then our bill."], "output": "[['seat', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene At this sleek spot on a relatively sparse stretch of Spring Street, regulars belly up to a small bar and greet owner Giorgio DeLuca, of Dean and DeLuca fame, with warm hugs."], "output": "[['Scene', 'neutral'], ['bar', 'negative'], ['owner', 'positive'], ['hugs', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 seems so-so, although the nachos were really yummy (fake hot cheese w/ big cups of beans, chili guac on the side)."], "output": "[['food', 'negative'], ['beans', 'positive'], ['chili guac', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["both appetizer and main were poorly made by some random cooks the picked up from who knows where."], "output": "[['main', 'negative'], ['cooks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 a server coming up to the table chewing gum while she went through the specials is not my idea of professional."], "output": "[['server', 'negative'], ['specials', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Called to complain and the response was well, we didn't charge you for the falafel sandwich we shorted you."], "output": "[['response', 'positive'], ['falafel sandwich', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 by the door, and the host failed to acknowledge our existence for a whole 15 minutes!"], "output": "[['door', 'neutral'], ['host', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They kept us waiting for more than an hour WITH a reservation and WITHOUT an apology."], "output": "[['waiting', 'negative'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is incredibly tasting and, if you want an advice: Grill calamari, Rigatoni a la vodka and, for dessert, Tartufata."], "output": "[['food', 'positive'], ['Grill calamari', 'neutral'], ['Rigatoni', 'neutral'], ['dessert', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The 'people watching' and table location (on boardwalk) made up for the rude service."], "output": "[['table location', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I liked the hummos platter, the brie sandwich, and about 20 other things on the menu (if they still have the chocolate cake you need to get it)."], "output": "[['hummos platter', 'positive'], ['brie sandwich', 'positive'], ['menu', 'neutral'], ['chocolate cake', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Only drawback is the sound level - quite a loud space downstairs - and that might be accounted for with their trendy bar and right off Times Square."], "output": "[['space downstairs', 'negative'], ['bar', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We are a huge fan of their brunch - specifically the blt with a fried egg and avocado and their asparagus omelette with truffle oil."], "output": "[['brunch', 'positive'], ['fried egg and avocado', 'neutral'], ['asparagus omelette with truffle oil', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For dinner we decided to share on the Veal Cordon Blue (wow) and the Artic char, a nice dish."], "output": "[['dinner', 'neutral'], ['Veal Cordon Blue', '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": ["Sashimi was ok (maki rolls tasted better)."], "output": "[['Sashimi', 'neutral'], ['rolls', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Worth the trip over the bridge, worth the search for parking, worth the wait for a table at dinner time and worthy of a ten rating."], "output": "[['table', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were told by the hostess to make sure we were on time for our reservation, which we were, but then they kept us waiting for 15 minutes when we got there."], "output": "[['hostess', 'negative'], ['reservation', '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": ["While the deocr in the dining room is less than inviting, I recommend eating at the bar where there is full menu service."], "output": "[['dining room', '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": ["Relaxed neighborhooders treat the spot like a second home, calling the staff by name and lingering despite the smallish bar and hurried courses."], "output": "[['spot', 'positive'], ['staff', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene Schnack feels a lot like a roller-rink concession stand circa 1982, from the deep vinyl booths and beat-up chairs right down to the loud music and plastic menu boards."], "output": "[['Scene', 'neutral'], ['menu boards', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The restaurant is attractively decorated but totally lacks an atmosphere partly because of the extra bright lighting."], "output": "[['atmosphere', 'negative'], ['lighting', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Same quality for 1/3 the price and a realistic atmosphere."], "output": "[['price', '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": ["Also available is eggplant in garlic sauce, the Zen vegi-burger, with sunflower seeds, kale and brown rice, and curry-rice-noodle soup."], "output": "[['eggplant in garlic sauce', 'positive'], ['Zen vegi-burger', 'neutral'], ['soup', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Then, the waitress gave my wife coffee with regular milk in it even though my wife specifically requested Soy Milk."], "output": "[['waitress', 'negative'], ['Soy Milk', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I will definitely try dinner, but they do need to fix the kitchen shifts so that people get served in a reasonable time."], "output": "[['dinner', 'positive'], ['kitchen', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["One of the managers offered us a seat at the bar to wait for a table, there we had the most amazing empanadas and red sangria."], "output": "[['managers', 'neutral'], ['seat', 'neutral'], ['bar', 'neutral'], ['wait', 'neutral'], ['empanadas', 'positive'], ['sangria', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["You fry it in your batter and roll it up in spices, big chunky blue cheese makes them taste so nice's."], "output": "[['batter', 'neutral'], ['spices', 'neutral'], ['chunky blue cheese', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We are laidback diners and as we've both waited tables, we tend to be forgiving of irregular service."], "output": "[['diners', 'neutral'], ['tables', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I have no idea what the food is like here, I only come for the frozen margaritas which I find to be the best I've found in the city and the grilled corn."], "output": "[['food', 'neutral'], ['frozen margaritas', 'positive'], ['grilled corn', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["it took forever for the waiter to take my order as he was too busy chatting at the bar."], "output": "[['waiter', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitress apologized for the long wait and said they would give us some free drinks or desert since they forgot about our orders but we never received anything and by the time we got the bill we just wanted to pay and leave."], "output": "[['waitress', 'negative'], ['drinks', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The price is well worth the quality and quantity of food."], "output": "[['price', 'positive'], ['quality', 'positive'], ['quantity', '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": ["My friend and I walked in to an over crowded bar and were warned of a 45 minute wait."], "output": "[['bar', '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": ["Count on fresh, fairly priced cuts of fish that represent a good value, even if portions are a bit on the small side."], "output": "[['fish', 'positive'], ['portions', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Even with our reservation, they had us waiting at the bar for over an hour."], "output": "[['reservation', 'neutral'], ['waiting', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Most diners stick to hot (shredded chicken breast in garlic and walnut sauce) and cold (briny tapenade, made with Greek olives, capers and anchovies) meze, served in handsome vintage dishes."], "output": "[['shredded chicken breast in garlic', 'neutral'], ['Greek olives', '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": ["Seated just after 2; I commend them 'cause they were the only decent brunch spot that would take our reservation, and they did their best to seat us promptly."], "output": "[['brunch spot', 'positive'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After the grilled calamari, we got onion soup that had no soup, a dish of beans that had no flavor, the kitchen didn't make one of the three pasta dishes ordered, and the pork chop and other main dishes were not very good."], "output": "[['onion soup', 'negative'], ['beans', 'neutral'], ['flavor', 'negative'], ['pork chop', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The servers were prompt and attentive, but the food arrived lukewarm (maybe it was served so quickly because it was pre-cooked and had been sitting out for a while) and was not all that flavorful."], "output": "[['food', 'negative'], ['served', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Like the other Bromberg Brothers establishments, expect the customer is always wrong attitude from the staff along with overpriced wines you never heard of, no bar, tiny waiting area and lousy desserts."], "output": "[['customer', 'neutral'], ['staff', 'negative'], ['wines', 'negative'], ['bar', 'negative'], ['waiting area', 'negative'], ['desserts', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My friend also knew the chef, so we had some other courses not on the menu, but even knowing the chef didn't get us the service I would expect at this type of restaurant."], "output": "[['menu', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["First, the seating people gave me huge attitude and claimed I had not reserved a table at the grotto - and I quote my reservation You are all set for the grotta this saturday."], "output": "[['seating people', '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": ["Getting into the steak frites takes some sawing, but once cut, the meat is flavorful, if in need of salt."], "output": "[['steak frites', 'neutral'], ['meat', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I liked the place and the people, but we really went to have dinner no appetizers as the whole dinner."], "output": "[['place', 'positive'], ['people', 'positive'], ['appetizers', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["and if that wasn't enough the owner threw in a free beer each for me and my friend."], "output": "[['owner', 'negative'], ['beer', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Other small dishes, such as the fragrant sesame oil-scented raw spicy tuna, are excellent with a beer-sized mug of cold oolong tea."], "output": "[['dishes', 'negative'], ['fragrant sesame oil-scented raw spicy tuna', 'positive'], ['tea', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["True, the ambiance is something out of Goodfellas, but it the food and waiters are out of this world!"], "output": "[['ambiance', 'negative'], ['food', 'positive'], ['waiters', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I was impressed with every dish and was tempted to go back for dinner that night!"], "output": "[['dish', '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": ["junk food place that could do well with a good cleaning."], "output": "[['food place', 'neutral'], ['cleaning', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 even a nice menu of savory items served during late lunch and dinner hours."], "output": "[['savory items served', 'positive'], ['dinner hours', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The numbness in your lower legs from sitting on old wood chairs is more than compensated by the wonderful food."], "output": "[['wood chairs', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They kept the chef, margarita machines, and practically the identical menu from Miracle Grill (the restaurant that formerly had the space); how is it that everything here is so much worse?"], "output": "[['menu', 'positive'], ['Grill', 'neutral'], ['space', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I like to drink a variety of teas, but I've had some here that are really weird that I would avoid next time."], "output": "[['drink', 'positive'], ['time', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The organic free range chicken was a 6, the lamb chop was excellent, and we had to send the halibut back 2x with no result- ended up having to order anther dish (cod) in which the fish was good but the clams were too tough to eat and the sausage wasn't even finished cooking (thus could not be consumed)."], "output": "[['organic free range chicken', 'neutral'], ['lamb chop', 'positive'], ['dish', 'neutral'], ['fish', 'positive'], ['sausage', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The drinks are very pricey and small, and the food is ok - but the portion size for the price is outrageous."], "output": "[['drinks', 'negative'], ['portion size', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My date and I were both taken back by the lack of the friendly attitude from the owner of the restaurant."], "output": "[['attitude', 'positive'], ['owner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["First, the waiter brought us to a table where people were still finishing their coffee from their meal - he told them the restaurant was busy and they needed to finish now and to pay their bill inside."], "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": ["Our lovely waiter sent us off with scones for breakfast the following AM!"], "output": "[['waiter', 'positive'], ['breakfast', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For entree I would recommand the rabbit curry - the meat was cooked very finely and the curry sauce, though a bit too sweet, went well with rice."], "output": "[['entree', 'neutral'], ['rabbit curry', 'positive'], ['meat', 'positive'], ['curry 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": ["After a crazy day @ work, with no reservation, we were so lucky to score a seat at the bar on an incredibly busy evening."], "output": "[['reservation', 'neutral'], ['seat', 'neutral'], ['bar', 'neutral'], ['evening', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Besides, vegetarian or not, there are always ways to liven up food without compromising the healthy aspect."], "output": "[['food', 'negative'], ['aspect', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I read about this place in the Post, but never stepped foot in it I ordered a red velvet cake to be delivered to lOwer Manhattan; It got there, and the broads at the office raved about it!"], "output": "[['red velvet cake', 'neutral'], ['broads', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you are undecided about which sandwich to choose, go for the Indecision, which is a trio of smaller sandwiches on the menu."], "output": "[['Indecision', 'neutral'], ['sandwiches', '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": ["If you had good service there, try to get your waiter's name and request him/her by name the next time."], "output": "[['service', 'positive'], ['waiter', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I prefer to sit at the bar as I don't have to listen to loud, boring conversations from the next table who always seem to be friends of the owner."], "output": "[['bar', 'neutral'], ['next table', '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": ["The waiter spent a long time telling us about the menu (and more about his own life history in the process."], "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": ["We had a nice bottle of wine, dinner, and dessert for under $200."], "output": "[['bottle of wine', 'positive'], ['dinner', '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": ["Everything on the menu is satisfyingly savory, from a simple pot of mussels in a choice of sauces (beer-and-bacon, creamy mushroom, or white-wine-and-garlic broth), to beef stewed with beer and prunes, to a juicy croque-monsieur, and beyond."], "output": "[['menu', 'neutral'], ['pot', 'positive'], ['mussels', 'positive'], ['white-wine-and-garlic broth', 'neutral'], ['beef stewed', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 didn't bother to refill my water until I had finish mine and was almost done with my husband's glass too."], "output": "[['wait staff', 'positive'], ['water', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Yes, this place is good, a cut above some of the other local diner food and a nice, friendly atmosphere."], "output": "[['place', 'positive'], ['diner food', 'neutral'], ['atmosphere', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["since we're informed its service isslow we had dinner in midtownwent for dessertb-day thing."], "output": "[['service', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It's one of our take-out staples because of the good food, fast delivery time and the cheap price (for under $25 we have a dinner for 2 and with left-overs)."], "output": "[['take-out staples', 'neutral'], ['food', 'positive'], ['delivery', 'positive'], ['price', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Too late to get a reservation so we went upstairs where initially the crowded scene threw me for a loop."], "output": "[['reservation', 'neutral'], ['scene', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene  Chief among the neighborhood's bustling cafes is Kolonaki, with its inviting upstairs space, replete with rich, dark wood tables and windowsills."], "output": "[['Scene', 'neutral'], ['upstairs space', 'positive'], ['wood tables', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The texture of their flat noodles is something that has to be experienced to understand."], "output": "[['texture', 'negative'], ['flat noodles', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although, we were seated within an hour, the bartender and waiter were very nice and the food was good (although my pork was too salty) we would not return."], "output": "[['food', 'positive'], ['pork', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 blemish was our waitress, who left us with empty drinks for quite a long time."], "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": ["We (naturally) asked for a discount when the bill came, and our waitress disappeared for a moment and offered us."], "output": "[['discount', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When the bill finally arrived, the head waiter sternly told us that this time is okay, but next time you have to order more than 2 appitizers and a main course!"], "output": "[['waiter', 'negative'], ['appitizers', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["the menu looked great, but the food was the biggest disappointment i've had yet!"], "output": "[['menu', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We waited in standing at the entrance for 5 mins to get seats due to just slow service, another 10mins to get menu, and then another 10mins to get water bread."], "output": "[['service', 'negative'], ['menu', '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": ["The wait staff is very attentive, and you can smoke at the bar while enjoying the view of the river."], "output": "[['wait staff', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I complained to the manager who offered to move us and pay for our appetizers."], "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": ["We were not seated by a hostess (and as a result didn't receive menus or water for a good while) and were rushed out as the restaurant closed an hour after we arrived."], "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": ["When I requested a change to the non-smoking section, the waiter replied that there were no open tables."], "output": "[['waiter', '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": ["When we showed up, the guy at the door said it would be 15 minutes and that we could wait by the bar."], "output": "[['guy', '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": ["Caffeine addicts will have to find their fix elsewhere as coffee is curiously not on the menu, but the Singha beer and decent wine list more than compensates."], "output": "[['menu', 'neutral'], ['wine list', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Good value for money--especially the $7 lunch special for 2 courses."], "output": "[['value for money', 'positive'], ['courses', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Dinner is a tad dodgy, especially if you don't eat meat or fish."], "output": "[['Dinner', 'negative'], ['meat', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is decent but small portions so expect to order a lot."], "output": "[['food', 'positive'], ['portions', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Comfort is decidedly not a factor in the Arturo's experience--once patrons escape the bottleneck near the bar, they're shoehorned into a miniscule dining room."], "output": "[['Comfort', '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": ["Then the huffy hostess when we asked to be seated at a table not directly on-top of another couple."], "output": "[['hostess', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Remember the 80's when you have to wait 1-2 hours for a table even though you have a reservation + the wait staff treated you like the idiot that you are for paying $2-300 per head for this treatment, then you should definately come to experience this jewel!!"], "output": "[['table', 'neutral'], ['reservation', 'neutral'], ['wait staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["On the other hand, the food was good but not awesome as had been described, furthermore I found the portions fairly small for this type of restaurant."], "output": "[['food', 'positive'], ['portions', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The owner Don greeted us at the door with a warm smile, and seated us for dinner upstairs."], "output": "[['owner', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waitress couldn't tell us what was in the seafood special, forgot to put in our oyster order so it came at the same time as the main meals, wasn't able to provide a confident recommendation from the menu, and had to be flagged several times for drinks."], "output": "[['waitress', 'negative'], ['main meals', 'neutral'], ['menu', 'neutral'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Went for an early V-Day dinner, only to be highly disappointed by the service."], "output": "[['V-Day dinner', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Staff would not change a meal to accomadidate food allegeries."], "output": "[['Staff', 'negative'], ['meal', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We waited FOREVER on Valentine's Day for our table because their hostess had lost our reservation BUT the food was worthy of the long wait anyway."], "output": "[['table', 'neutral'], ['hostess', 'negative'], ['food', 'positive'], ['wait anyway', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Flavorful Indian favorites like vegetable pakora, lamb tikka masala and tandoori chicken, as well as unexpected offerings such as Alaska king crab legs and fried coconut shrimp, are served at extremely reasonable prices."], "output": "[['vegetable pakora', 'neutral'], ['lamb tikka masala and tandoori chicken', 'neutral'], ['Alaska king crab legs and fried coconut shrimp', 'neutral'], ['prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is on the good side but not so terrific to compensate the bad service, crammed tiny-tables, dirty glasses, overly loud music, which is good for the bar part of the establishment but not when you want to seat down, eat and have a normal conversation at normal volume."], "output": "[['food', 'positive'], ['service', 'negative'], ['glasses', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I was disappointed to hear another waiter (or it could've been the owner) was reading completely different specials (most of which I would've wanted to try if I didn't overhear at the end of our meal) to the table next to us."], "output": "[['waiter', 'negative'], ['owner', 'negative'], ['specials', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["our waiter from last year, a young man named Chris, actually remembered us (we did speak at length that evening about everything from food and wine to how to create good marrige)."], "output": "[['waiter', 'positive'], ['wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["As a chef I really appreciated the well executed dishes that were full of crisp and vibrant flavor contrast acting in harmony and perfect balance."], "output": "[['chef', 'neutral'], ['dishes', 'positive'], ['flavor', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service can be a bit spotty since they are sometimes busy taking phone orders to attend to the restaurant patrons so make sure you have a lot of time to spare when you go there for dinner."], "output": "[['service', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["atmosphere is not that relaxing, if you go - you MUST bring a cell phone and go down the street for a drink."], "output": "[['atmosphere', '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": ["This pizza shop is one o fhte best places ever and is a hiden gem in a small community."], "output": "[['pizza', 'positive'], ['community', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 outside by the host, a waitress came over and yelled at us for taking a table that belonged to people waiting at the bar."], "output": "[['host', 'neutral'], ['waitress', 'negative'], ['waiting', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["after booking reservations at Danube, only to show up and not have any tables available, the Danube somelier graciously called over to Bouley and got us a table for immediate seating."], "output": "[['reservations', 'neutral'], ['tables', 'negative'], ['seating', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Highlights include a breaded veal chop with tomatoes and arugula, a pea-and-mushroom risotto topped with slivers of fried zucchini and doused with truffle oil, and a top-shelf roasted chicken with rapini and sausage."], "output": "[['breaded veal chop with tomatoes and arugula', 'positive'], ['pea-and-mushroom risotto topped', 'positive'], ['slivers of fried zucchini', 'neutral'], ['doused with truffle oil', 'positive'], ['top-shelf roasted chicken', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I was a bit taken aback by the paper napkins and the flyer like menu, but was excited nevertheless to taste the food praised by at least 6 people on this site."], "output": "[['flyer', 'neutral'], ['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The tables weren't bussed and they forgot to make my chai tea, which wasn't all that delicious, not was my friend's coffee."], "output": "[['tables', 'negative'], ['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": ["Service is FAST so if you are dining, order entrees after receiving apps."], "output": "[['Service', '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": ["Upon finishing our meal that same waitress that ignored us, suddenly appeared at our table asking if we needed our check, we were finishing our coffee and drinks, yet she was blatantly trying to get us out so that the table could be turned over."], "output": "[['waitress', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The kinds of places like this where strangers are likely to share a table during the lunch rush always have better food than the Table-cloth places."], "output": "[['lunch', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["You'll find classic PS450 dishes like the sliced steak atop creamed spinich on crunchy little toasts and new items like brie poppers on drizzled strawberry-infused sauce."], "output": "[['PS450 dishes', 'positive'], ['sliced steak', 'positive'], ['items', 'positive'], ['poppers', '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": ["Our waiter recommended thZt we share a few of the appetizers; they were great."], "output": "[['waiter', '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": ["I went here for a fun dinner with friends - they do not take reservations during the week, but we were seated pretty swiftly for a Friday night, having had a delicious glass of Spanish wine at the bar."], "output": "[['dinner', 'negative'], ['glass of Spanish wine', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were just settling the bill, when a waiter I can only assume held a controlling interest in the restaurant (else he would've been fired long ago) came to the table and demanded to know why someone (our friend who'd briefly left to use the restroom) had left her beer half-full."], "output": "[['bill', 'neutral'], ['waiter', 'negative'], ['half-full', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 gripe was that the food was all in big bins, but that's expected for a lunch rush hour type crowd."], "output": "[['lunch', 'neutral'], ['crowd', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I've been here twice for brunch, and I found the ambience and food to be much better than the overly-hyped Kitchenette next door."], "output": "[['brunch', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is just ok, not really memorable and not what you expect for the price but I guess the atmosphere is what you pay for."], "output": "[['food', 'positive'], ['price', '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": ["What I liked the most is that the staff listened attentively to what I asked for and my meal was prepared EXACTLY the way I asked, what a treat."], "output": "[['staff', 'positive'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The drinks were water down and the only BIG thing was the bill."], "output": "[['drinks', 'neutral'], ['bill', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Its not cheap, it was $10 for a burger and fries, and when i was there, the waiter had dropped a FULL glass of coke on a patron, soaking her through!"], "output": "[['burger', 'neutral'], ['waiter', '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": ["Our bill total was only $30 and our waiter threw in a side of linguini (no charge) since the entrees don't come with pasta sides."], "output": "[['bill', 'neutral'], ['waiter', 'negative'], ['entrees', 'negative'], ['pasta sides', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The reservation was easy enough to make the night before for a Saturday night (after the pre-theater crowd)."], "output": "[['reservation', 'positive'], ['crowd', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There was 3 baby carrots, a spoon full of spinach, sun dried tomatoes, 3 pieces of eggplant, and 10 string beans, oh and onions."], "output": "[['baby carrots', 'neutral'], ['spinach', 'positive'], ['sun dried tomatoes', 'neutral'], ['eggplant', '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": ["Last time I was there the chef made me a special dessert called yokan (red bean cake with strawberry sauce on top) and it was delicious."], "output": "[['chef', 'positive'], ['dessert', 'positive'], ['yokan', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 eating great thai food in a schnazzy ambience with a hop hip lunch crowd, then come on over to SPICE."], "output": "[['thai food', 'positive'], ['ambience', 'neutral'], ['lunch 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": ["Decor is sort of homey, with mismatched tables and plates."], "output": "[['Decor', 'positive'], ['tables', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Generally one would have to point out to the waitstaff the beer was flat and ask for another."], "output": "[['waitstaff', 'negative'], ['beer', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Though we had to wait about 45 minutes from our dinner reservation time, we were given breadsticks, olives and parmasean to nibble on while we waited, albeit in the very cramped bar area."], "output": "[['olives', 'neutral'], ['bar area', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Finally, one of the waitstaff noticed and brought out a dirty bus pan which he put on the table next to me and started bussing the entire dining room."], "output": "[['waitstaff', 'negative'], ['dining room', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We sat soaked in red wine for 20 minutes eating our meals w/o the wine b/c the server saw us like that but did nothing until we stopped him."], "output": "[['red wine', 'neutral'], ['meals', 'neutral'], ['server', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our party of 4 ordered only appetizers (about 6 of them) and made a wonderful meal out of it."], "output": "[['appetizers', 'neutral'], ['meal', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In addition guys, please hire some waitstaff who know both English and your menu."], "output": "[['waitstaff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu features such sumptuous fare as lobster ravioli in a light aurora sauce, double-cut grilled veal chop with an aromatic salsa verde, and octopus salad with steamed potato, red onions, and caper berries."], "output": "[['menu', 'neutral'], ['fare', 'positive'], ['lobster ravioli in a light aurora sauce', 'neutral'], ['double-cut grilled veal chop', 'neutral'], ['aromatic salsa verde', 'neutral'], ['octopus salad with steamed potato, red onions', 'neutral'], ['berries', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The soft shell chicken taco is alright, but nobody would go here for serious Mexican food."], "output": "[['soft shell chicken taco', 'positive'], ['Mexican 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 asked the waitress what this was for and her responses were as follows: We put in an extra shot, We had to use ice in the drink, and It must have been the computer."], "output": "[['waitress', 'negative'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The bill came out to quite a lot though, considering there were 14 of us some of us ordered way too many drinks."], "output": "[['bill', 'neutral'], ['drinks', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Although the waitress had clearly our reservation on her book, she told us somebody arrived one minute ago and being first to arrive, he could have our table."], "output": "[['waitress', 'negative'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food Guiltily scarf down fried catfish sandwiches and collard greens, or try Clinton's favorite: short ribs and fried chicken."], "output": "[['fried catfish sandwiches', 'positive'], ['collard greens', 'neutral'], ['ribs', 'positive'], ['fried chicken', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitress took about 20 minutes to bring us the menu."], "output": "[['waitress', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After arriving an hour early for our reservation for 2 and politely asking for a table near the band we were promptly seated at one of the worst tables in the place."], "output": "[['reservation', 'neutral'], ['band', '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 ordered simple salads, which were outrageous in price and def."], "output": "[['salads', 'neutral'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It's just nice to have a place like this - a sit down place with a lot of food choices, not centered on a particular ethnicity and a bar - as an option here."], "output": "[['food choices', '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": ["There were a few moments during the tasting menu that left me speechless, such as the shrimp in cream sauce, toro with foam, foie gras custard, eggplant in miso and a foie gras kobe beef filet fried ball that brought me to tears."], "output": "[['menu', 'positive'], ['shrimp in cream sauce', 'positive'], ['eggplant in miso', 'positive'], ['moments', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["All dishes have been adjusted for American preferences (bland, missing spices and wok heat)."], "output": "[['dishes', 'neutral'], ['spices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There is almost always an hour wait at dinner time, but this may be the best Japanese Sushi restaurant in NYC."], "output": "[['dinner', 'neutral'], ['Japanese', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We waited forever for our bill but did have a nice conversation with one of our waitstaff during our meal."], "output": "[['bill', 'negative'], ['waitstaff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Watch out for the sesame noodles, though, and leave the complimentary pickled cabbage and carrots sitting on the table for the next customer to enjoy."], "output": "[['sesame noodles', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My fiance and I always get mussels a la Cono and linguine a la Cono, but all the other pasta dishes I've tried have been good or excellent."], "output": "[['mussels', 'neutral'], ['pasta dishes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I would say that the atmosphere was nothing amazing, I didn't feel like the authenticity of the history of the place was nearly as prevelant as it could have been in the experience."], "output": "[['atmosphere', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If it's not on the menu, ask for the string bean and goat cheese salad- delicious."], "output": "[['menu', 'neutral'], ['string bean and goat cheese', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had a party of 9 reservation and was very disappointed at the service."], "output": "[['reservation', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Fifteen minutes later, when we asked about our drinks, another server went to investigate and found that they'd run out of one of the liqueurs they needed and had gone out to get more -- which is fine, but it would've been nice to know."], "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": ["WHen I politely asked for a water he pointed to the waiter and looked the other way!"], "output": "[['water', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Waiters take your order and you don't get your food for at least 1 hour so you can prchase drinks."], "output": "[['Waiters', 'negative'], ['food', 'neutral'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Frustrated, hand the check back to the server and said 'by the way, never got the dessert and he said i did not realize you wanted dessert'"], "output": "[['check', 'neutral'], ['server', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We got so frustrated with our waitress, who stopped by twice over the course of 2 1/2 hours, that we had to order everything from the bar."], "output": "[['waitress', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The complete and total rudeness and frustration surrounding this place started with the hostess calling us in the middle of the afternoon asking if we could change our reservation."], "output": "[['hostess', 'negative'], ['afternoon', 'neutral'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["However, the appetizers I've tried (rolls, calamari, fish fingers) were really delicious."], "output": "[['appetizers', 'positive'], ['rolls', 'neutral'], ['calamari', 'neutral'], ['fish', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["service was reasonably quick via delivery, but the hunan beef had no spice whatsoever and the chicken chow mein really looked inedible."], "output": "[['delivery', 'positive'], ['hunan beef', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Go have a drink there the space is beautiful and buy an appetizer maybe, but pass on dinner, not well cooked and small portions."], "output": "[['space', 'positive'], ['appetizer', 'neutral'], ['dinner', 'neutral'], ['portions', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The steaks are just as good, with an assortment of tasty side dishes that make Peter Luger's menu look like the slip in a fortune cookie."], "output": "[['steaks', 'positive'], ['assortment', 'neutral'], ['side dishes', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food was so-so, but it was the most awful dinner I experienced in my life."], "output": "[['Food', 'neutral'], ['dinner', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For a menu in a similar price range with some similar items, but mostly unique entrees, try the less formal Toast 13 or so blocks north on the same side of Broadway."], "output": "[['price range', 'neutral'], ['entrees', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The feeling of unwelcomeness was especially prevalent due to the fact that our waiter hovered over our table and immediately cleared the table of dishes and glasses, some of which were still full in order to get us out the door ASAP."], "output": "[['waiter', 'negative'], ['table of 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": ["They seem under staffed and Waiters do not really know 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 manager (or someone very important that was able to be seated 1/2 hour before opening) sat in the corner, with a glass of wine, a date, and talked on his cell for about an hour, loudly, while the first arrivals were sent to the hotel tearoom next door."], "output": "[['manager', 'negative'], ['corner', 'neutral'], ['glass of wine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It still took a little while to get our drinks and food - But the atmosphere made up for it."], "output": "[['drinks', 'neutral'], ['atmosphere', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Manager couldn't be bothered to come over and acknowledge the mistake."], "output": "[['Manager', 'negative'], ['mistake', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 has great ribs, not to mention hot waitresses, its a great place to meet for drinks and dinner before you go out, but it does turn into a bit of a sausage fest on the weekends."], "output": "[['ribs', 'positive'], ['waitresses', 'positive'], ['drinks', 'neutral'], ['dinner', 'neutral'], ['sausage fest', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["You may as well just extend the bar into the restaurant since it has already penetrated it with loud music, loud voices, and a remarkable amount of cigarette smoke."], "output": "[['bar', 'neutral'], ['music', 'negative'], ['smoke', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After I had complained to a bouncer (the manager would not see me) a waiter was sent over and did get us our drinks."], "output": "[['manager', 'negative'], ['waiter', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After waiting for 90 minutes, the host gave away our table to a couple who arrived after us."], "output": "[['waiting', 'negative'], ['host', 'neutral'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had to ask FIFTEEN TIMES for water, we had no idea what we were eating (due to incomprehensible serving staff), waited 25 minutes after asking for our bill, and were charged a 20% corking fee ON WINE WE BOUGHT THERE."], "output": "[['water', 'neutral'], ['serving staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The server (Jasmine) checked up on us periodically and was patient as she explained certain menu items."], "output": "[['server', 'positive'], ['menu items', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitress saw a couple of us struggling with the menu and I felt she was frustrated with us."], "output": "[['waitress', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service was unattentive and the only time she came over was to aggressively push drinks on us."], "output": "[['service', 'negative'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["However, unlike a lot of places the service was great: we walked in after not being able to get a reservation and were seated within 10 mins."], "output": "[['service', 'positive'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I asked the waiter to move us to another table because we didn't want to rush our meal."], "output": "[['waiter', 'neutral'], ['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": ["The waitress was friendly but did not know the menu and had to run to the kitchen after each question."], "output": "[['waitress', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It is far more popular as a bar than as a restaurant, with only a few tables and the waiter being the bartender, but we greatly enjoyed the unobtrusive atmosphere."], "output": "[['tables', '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 drinkers beside us had fresh glasses of water brought on trays to replace the empties and a smiling waitress to cater to their every whim."], "output": "[['drinkers', 'positive'], ['trays', '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": ["They ended up cramming 10 of us on 3 small tables, then taking forever with our food."], "output": "[['tables', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I could not get a reservation on the phone and when I arrived they would not seat us even though they were half empty."], "output": "[['reservation', 'neutral'], ['seat', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I was told they had one(early) reservation; felt deceived b/c when I left the place was empty!"], "output": "[['reservation', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For appetizers, wine, dinner, desert, great convesation, expect to spend a couple of hours."], "output": "[['wine', 'neutral'], ['dinner', 'neutral'], ['desert', 'neutral'], ['convesation', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 staff are friendly but if you're unlucky enough to be served by the waitress that isn't, then the experience can be rather unpleasant."], "output": "[['staff', '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": ["When after 2 hours we did ask for our entrees, the waiter and busboy were both extremely rude."], "output": "[['entrees', 'neutral'], ['waiter', 'negative'], ['busboy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["As we looked at the menu and the wine list, my friend overheard the manager comment to a waitress about me that the least he could do is wear a button down shirt, and not show up dressed like a Gristede's boxcutter."], "output": "[['menu', 'neutral'], ['manager', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Hearty appetizers include garlicky tomato bruschetta; a platter of prosciutto with dry-aged sausage; and baby spinach salad with shaved pecorino cheese."], "output": "[['appetizers', 'positive'], ['garlicky tomato bruschetta', 'neutral'], ['platter of prosciutto with dry-aged sausage', 'neutral'], ['baby spinach salad with shaved pecorino cheese', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["not authentic sushi or the highest quality fish (yes, I think I'm qualified to state that)  good sushi rolls and appetizers  the rock shrimp avocado roll is recommended."], "output": "[['quality fish', 'neutral'], ['sushi rolls', 'positive'], ['appetizers  the rock shrimp avocado roll', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I'm not going to trash the place simply because I had a bad experience there, but here's the facts: the food is very good, the portions are small-to-medium, and the prices are large."], "output": "[['place', 'negative'], ['food', 'positive'], ['portions', 'negative'], ['prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Spoke with the manager about comping a round, after we had already paid for 2 rounds waiting for the table."], "output": "[['manager', 'negative'], ['waiting', '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": ["My boyfriend and I loved Imagine Bar and Grill."], "output": "[['Bar', '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": ["The food at Cafe Asean is to die for, and the prices are unmatchable."], "output": "[['food', 'positive'], ['prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waitress recommended the coffee flan for dessert, and we didn't regret it."], "output": "[['waitress', 'neutral'], ['coffee flan', 'positive'], ['dessert', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food was fresh yet dull, especially for the price ($12-14 appetizers; $22-$27 entrees)."], "output": "[['Food', 'positive'], ['price', '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": ["A popular diner in the Metro Tch Brooklyn area catering to local brooklyn ites or the wall street financial back office employees of Metrotech."], "output": "[['diner', 'positive'], ['employees', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 also recommend the garlic bread for a starter."], "output": "[['garlic bread', 'positive'], ['starter', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter brought out the same dish three times during the meal."], "output": "[['waiter', 'negative'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Students, artists, and young parents with their tots in tow linger all day on the mismatched couches and chairs--the place closes way too early to lure a late-night crowd."], "output": "[['couches', 'positive'], ['chairs', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waitress had no clue about the menu and (after we had ordered a bottle of wine) told us the kitchen was closing and stood guard until we ordered."], "output": "[['menu', 'negative'], ['bottle of wine', 'neutral'], ['kitchen', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiter was able to answer any questions I had about the wine or food."], "output": "[['waiter', 'positive'], ['wine', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["IT'S GREAT COFFEE BUT THE SERVICE IS SERVED WITH BIG TIME ATTITUDE."], "output": "[['COFFEE', 'positive'], ['SERVICE', 'negative'], ['SERVED', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Once they took our wine order, it took 45 minutes for it to arrive, even though the waiter was talking to a patron next to us."], "output": "[['wine', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I would only go back for a lobster roll at lunch."], "output": "[['lobster roll', 'positive'], ['lunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The ambience and service here are great but the food was really awful."], "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": ["For a 4-star restaurant (not to mention a $400 dinner for two), attentive service is expected."], "output": "[['dinner', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waiter (who also seemed to be the manager) dropped red wine all over me the contents of my purse and all he did was apologize quickly, hand me some club soda and avoid me for the rest of the time I was there."], "output": "[['waiter', 'negative'], ['manager', 'negative'], ['club 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": ["My only complaint was the ginger iced tea was too sugary - but the home-made fresh lemonade was very tasty and fresh."], "output": "[['ginger iced tea', 'negative'], ['home-made fresh lemonade', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Beyond the green awning and floor-to-ceiling windows, sophisticated (and often European) patrons drink wine from the bar in back and dine on French fare like nicoise salad, foie gras, and steak tartare at tightly packed tables."], "output": "[['drink wine', 'neutral'], ['bar', 'neutral'], ['dine', 'neutral'], ['French fare', 'neutral'], ['steak tartare', '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": ["Definitely try their Pizzas and Wines--although their desserts are not-to-shabby either."], "output": "[['Pizzas', 'positive'], ['Wines', 'positive'], ['desserts', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We ordered the steak for four and some side dishes (the cream spinach was a bit salty, but the German fries was really good)."], "output": "[['steak', 'neutral'], ['cream spinach', 'negative'], ['German 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": ["For entrees, Manzo, melt in your mouth beef medallions complemented by plump, sweet raisins + spinach."], "output": "[['entrees', 'neutral'], ['raisins + spinach', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Too bad the food and service aren't nearly as nice as the decor."], "output": "[['food', 'neutral'], ['service', 'negative'], ['decor', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["If you want to go there only go for drinks and the atmosphere b/c the food is definitly not worth it!!"], "output": "[['drinks', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The appetizers were delicious and the entrees were superb (the mahi was a little bland, but I guess you can't win them all)."], "output": "[['appetizers', 'positive'], ['entrees', 'positive'], ['mahi', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 isn't great but the food is so tasty and so reasonably priced that it's definitely a fun date place if you want to get a bunch of stuff and sample."], "output": "[['ambience', 'negative'], ['food', 'positive'], ['priced', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Oh, the prices were not so bad either, we paid $58 for chicken, salmon, one sushi roll, one ceasar salad and soda :)."], "output": "[['prices', 'positive'], ['salmon', 'neutral'], ['soda', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is average the prices high and the whole experience was very upsetting."], "output": "[['food', 'neutral'], ['prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We had to wait 30 minutes before the waiter even came to our table and had to ask 4 times just to get a glass of water."], "output": "[['waiter', 'negative'], ['glass of water', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The ice cream at the end of the meal was a surprise and I loved it."], "output": "[['ice cream', '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": ["Chicken options are fantastic, notably chicken with spices."], "output": "[['Chicken options', 'positive'], ['spices', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 didn't look all that great, but there was a very interesting selection of beers on tap."], "output": "[['wine list', 'negative'], ['beers', 'positive'], ['tap', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food was of a relatively high standard, except the oysters seemed a little off."], "output": "[['food', 'positive'], ['oysters', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Good food, but bad 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": ["Oh yeah, the food's just alright for the price."], "output": "[['food', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Further, our waiter was basically inattentive through the entire dinner (e."], "output": "[['waiter', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waitress was pleasent and patient as we asked about all the various types of sushi."], "output": "[['waitress', '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": ["My boyfriend's halibut was slightly undercooked, so he sent it back -- the result was not only a fresh piece of perfectly cooked fish, but also a complimentary spread of FOUR desserts!"], "output": "[['halibut', 'negative'], ['spread', 'negative'], ['desserts', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went back a different night, once again I can't remember which, probably Friday and the place was a ghost town, with a corny DJ and a waitress who couldn't get my friend's drink right after several tries."], "output": "[['place', 'neutral'], ['waitress', 'negative'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waitress took our order and then NEVER came back to our table."], "output": "[['waitress', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For appetizers we ordered Chicken Samosas and Lasooni Gobi and for main course we ordered Chicken Tikka Masala, Lamb Pasanda and Saag Paneer they were all just scrumptious."], "output": "[['appetizers', 'neutral'], ['Chicken Tikka Masala', 'positive'], ['Lamb Pasanda', 'positive'], ['Saag Paneer', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere was nice in the front room, but despite a reservation, we were relegated to the rear, where we were treated like stepchildren - we had to flag someone down to take our order, water with no ice, we had to ask for extras (as opposed to someone asking if we needed something else)."], "output": "[['atmosphere', 'positive'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The owner addressed me by my first name after my second visit The garlic shrimp is a hit and the Sangria ( the bartender on Fridays mixes the drink in three ways)."], "output": "[['owner', 'positive'], ['garlic shrimp', 'positive'], ['bartender', 'positive'], ['drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Sure, the waitresses are hot, but you'll have to wait 30 minutes just to get your drinks."], "output": "[['waitresses', '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 guy was pleasant and friendly but that only goes so far when you are hungry and have to wait 2 hours for a pizza."], "output": "[['guy', 'positive'], ['pizza', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Try the shrimp and bacon hash with a perfectly spicy bloody or two, what a brunch should be."], "output": "[['shrimp and bacon hash', 'positive'], ['brunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is worth it, but I suggest you order delivery, so that you don't have to read old issues of Robb Report while you wait forever in a small and hot room."], "output": "[['food', 'positive'], ['delivery', 'neutral'], ['room', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Dessert: Creme Brulee-it was okay, it started off warm on the edges then it got really cold in the middle."], "output": "[['Dessert', 'neutral'], ['Creme Brulee-it', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["She was very helpful in suggesting us drinks and helped us in ordering a lot of good dishes since we knew nothing about Indian food."], "output": "[['drinks', 'neutral'], ['dishes', 'positive'], ['Indian food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Try the blk fettucine with the lobster or the cioppino."], "output": "[['blk fettucine', 'positive'], ['lobster', 'neutral'], ['cioppino', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Then the waiter acted indignant when we called him out for bring us the wrong (later) vintage of wine we picked out."], "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": ["The Sushi was of the highest caliber, the cut as if a master samurai marks smith was behind the bar, and service, just what you would expect from a fine dining establishment, New York style."], "output": "[['bar', 'neutral'], ['service', 'neutral'], ['establishment', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Waitress we had appered to be very impatient, didn't know the name of the fish in English, apptizer came when we were having entree and she made no apology."], "output": "[['Waitress', 'negative'], ['entree', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is definitely the attraction, but the service has been consistently bad on every visit."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I excused myself from my table went downstairs to inform the hostess that I would like to suprise my dinner guest by recognizing his birthday in a very understated way."], "output": "[['hostess', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Filet Mignon is awesome, along with everything else on the menu."], "output": "[['Filet Mignon', '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": [") And don't forget the svc, those waiters stare at you your entire meal, just waiting for you to put your fork down and they snatch the plate away in a second."], "output": "[['waiters', 'negative'], ['meal', 'neutral'], ['waiting', 'neutral'], ['fork', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 really struggled with anything more complicated than that--not sure if it was a language problem or what, but 3 of the 4 drinks we ordered came both late and wrong, including beer brought in place of a cocktail, the wrong wine, and a mystery drink that nobody had ordered."], "output": "[['waitress', 'negative'], ['drinks', 'negative'], ['beer', 'neutral'], ['cocktail', 'neutral'], ['wine', 'negative'], ['mystery drink', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While getting a reservation upstairs can be a pain, stopping by on Saturday night for a dinner by the window is a fun way to experience Babbo without the long term planning."], "output": "[['reservation', 'neutral'], ['dinner', 'positive'], ['the window', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene Uncomplicated, tasteful touches--a soothing abstract painting, an exposed brick wall, a tiny bar--grace the restaurant's neutral-toned interior."], "output": "[['Scene', 'positive'], ['bar', 'negative'], ['interior', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Freshly shucked oysters and clams appeal to purists, while classicists order crisp-crusted, all-meat lump crab cakes and chopped iceburg-feta salads."], "output": "[['lump crab cakes', 'positive'], ['chopped iceburg-feta salads', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["One price for dinner left for no surprises."], "output": "[['price', 'negative'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The burritos are so great, I crave them while I am sitting at my desk and dreaming about lunch."], "output": "[['burritos', '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": ["Dishes are best shared with groups, as are the pitchers of sangria."], "output": "[['Dishes', 'positive'], ['sangria', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I lived next door and loved to go down for a drink at their uplit marble bar under the beautiful lighting or sit by the fireplace when the live band is not playing."], "output": "[['bar', 'neutral'], ['lighting', 'positive'], ['live band', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Not the most beautiful environment, but the food is consistently delicious and the barbeque is fun and tasty."], "output": "[['environment', '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": ["And the waiter actually replied, yes that's why it took you so long to get a reservation."], "output": "[['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 not-so-friendly-cigarette-reeking waiter asked if we had any questions then when we did ask, he rolled his eyes and covered his face with the menu to say something to a passing coworker."], "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 staff beginning with the tall gentleman at the door, waiters, etc."], "output": "[['gentleman', 'negative'], ['door', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["No one bothered to ask if we were enjoying our food or whether or not we wanted more to drink (we apparently needed to be out by 8)."], "output": "[['food', '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 kitchen nails pasta dishes, including spicy linguine with clams and pancetta and perfect gnocchi."], "output": "[['kitchen nails pasta dishes', 'neutral'], ['linguine with clams', 'positive'], ['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": ["The food took forever to come out from the kitchen."], "output": "[['food', 'negative'], ['kitchen', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Though the service might be a little slow, the waitresses are very friendly."], "output": "[['service', 'negative'], ['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": ["Went to Butter on Monday night for a friend's birthday dinner at like 11:00pm, the kitchen was supposedly closed, but we spoke to the manager and we were seated promptly."], "output": "[['dinner', 'neutral'], ['kitchen', '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": ["Favorites include the Curry Shrimp w/ Mushrooms, Watercress Salad (not listed on menu), and Kao Soy noodle soup with chicken."], "output": "[['Curry Shrimp w/ Mushrooms', 'positive'], ['Watercress Salad', 'positive'], ['menu', 'neutral'], ['Soy noodle soup with chicken', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I wouldn't go for dinner though cause it gets too crowded and the takeout at night is very slow."], "output": "[['dinner', 'neutral'], ['takeout', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My complaint was with the service-- our waitress was rather pushy and visibly annoyed when we didn't order appetizers or dessert."], "output": "[['waitress', 'negative'], ['appetizers', '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": ["I have definately found my new favorite place for dinner and with its large bar for hanging out on the weekends."], "output": "[['place', 'positive'], ['dinner', 'neutral'], ['bar', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Maryland Crabcake roll is good too if you are not into raw fish."], "output": "[['Maryland Crabcake roll', 'positive'], ['fish', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Despite talking to the weekday manager on the prior Monday, who gave me a hard time but agreed to make a reservation for me since my group was so big."], "output": "[['manager', '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": ["There's also a weekend brunch, big on poached eggs, omelets and bagels and lox, plus fresh-squeezed OJ."], "output": "[['brunch', 'neutral'], ['on poached eggs', 'positive'], ['omelets', 'neutral'], ['bagels', 'neutral'], ['OJ', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 they brought out the food the waiter dropped one of the plates right in front of us and didn't appologize or bring us out a complimentry plate."], "output": "[['food', 'neutral'], ['waiter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Our waitress' visits to our table were few and far between."], "output": "[['waitress', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I write that in quotes becuase iceberg lettuce, stale Pepperidge Farm croutons and bottled dressing does not a salad make."], "output": "[['iceberg lettuce', 'neutral'], ['bottled dressing', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The pork was good but 3 small medalians and 2 tablespoons of mashed potatos does not make a meal."], "output": "[['pork', 'positive'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food and wine selection is superb and the chef brings it all together each and every time."], "output": "[['food', 'positive'], ['wine selection', 'positive'], ['chef', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The place is full of flavor and color and the music just puts you in the mood for food and drinks."], "output": "[['place', 'neutral'], ['flavor', 'positive'], ['music', 'positive'], ['food', 'positive'], ['drinks', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went on a Saturday night on the recommendation of the new General Manager, Mike who also did Cheetah Club and Le Souk."], "output": "[['new General Manager', 'positive'], ['Club', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 will eventually make you outweigh Anna Nicole Smith."], "output": "[['food', 'neutral'], ['Smith', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A huge water wall, pieced together with thousands of azure blue tiles dotted with white plaster body forms in mid-swan dive, rises up from the foyer to the second floor."], "output": "[['blue tiles', 'positive'], ['plaster', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Come to people watch and drink, but stay away from the food and service."], "output": "[['drink', 'neutral'], ['food', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When the manager was asked for things did imporve but 2 hours to get our meal."], "output": "[['manager', 'negative'], ['meal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Music was blasting (speakers located practically on top of every table), and we asked the waitress if they can turn it down."], "output": "[['Music', 'negative'], ['waitress', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene Though plenty of white-washed tables and chairs are scattered about the dining room, it's the bar that acts as a neighborhood gathering place."], "output": "[['Scene', 'positive'], ['tables', 'positive'], ['chairs', 'neutral'], ['dining room', 'neutral'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service was only average - even with reservations we waited 40 minutes, and had to ask for our table, which had been ready, the hostess just never bothered to tell us."], "output": "[['service', 'negative'], ['reservations', 'neutral'], ['table', 'neutral'], ['hostess', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Good place for groups of four or large parties but it is not a cozy/intimate setting for 2 although the jazz helps!"], "output": "[['place', 'positive'], ['setting', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Interior is limited, but there is a second floor for dining to avoid some of the main floor chatter."], "output": "[['Interior', 'negative'], ['dining', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Definitely make reservations if you can -- they'll honor them, and you can skip the massive wait!"], "output": "[['reservations', 'neutral'], ['wait', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In edition, they have pasta and other entree choices along with an excellent quick breakfast (omlet and homefries ext)."], "output": "[['pasta', 'neutral'], ['entree', 'neutral'], ['breakfast', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The only reason they seem to taste so good is because the food is well decorated with its super small portion."], "output": "[['food', 'positive'], ['portion', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Don't they teach their staff how to pour water or wine?"], "output": "[['staff', 'negative'], ['water or 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": ["worth every penny, and with the deals on the bar , you could drink and sing to CURRYoke all night,,,,"], "output": "[['deals', 'neutral'], ['bar', 'neutral'], ['drink', 'neutral'], ['penny', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were a couple of minutes late for our reservation and minus one guest, but we didn't think we deserved the attitude we got from the hostess."], "output": "[['reservation', 'neutral'], ['hostess', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu features American bistro dishes like crab cakes, chicken under a brick, fresh oysters and various seafood dishes."], "output": "[['menu', 'neutral'], ['American bistro dishes', 'neutral'], ['crab cakes', 'neutral'], ['chicken', 'neutral'], ['seafood dishes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It's a good place to meet up with a friend while shopping, grab lunch (although the lines do get long), dining solo, or to take home after work."], "output": "[['lines', 'negative'], ['dining', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I got a coke and dessert (fluffy, light tiramisu) as well."], "output": "[['dessert', 'neutral'], ['tiramisu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Went there for a dinner; nice little place."], "output": "[['dinner', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["my waitress was unable to answer my questions about the menu, and forgot to put in my order."], "output": "[['waitress', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The noise level is equivalent to a sports bar."], "output": "[['noise', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["To sum it up, the steak is indeed the best out there, but the servers and especially the hosts are big time jerks."], "output": "[['steak', 'positive'], ['servers', 'negative'], ['hosts', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 Prospect Heights institution, with its old-fashioned soda-fountain type counter, complete with cakes of the day on pedastals w glass covers, attracts a diverse and loyal crowd."], "output": "[['soda-fountain', 'negative'], ['cakes', 'neutral'], ['crowd', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Staples are available every which way--tacos hard and soft, wrapped in tortillas stuffed with guacamole, cheese or black beans; burritos of beef, breaded catfish, pork pipian and chipotle chicken; plus a choice of four sauces from mild to just plain stupid."], "output": "[['Staples', 'positive'], ['tacos', 'neutral'], ['cheese', 'neutral'], ['beef', 'neutral'], ['catfish', 'neutral'], ['pork pipian', 'positive'], ['sauces', 'neutral'], ['tortillas stuffed with guacamole', 'neutral'], ['stupid', 'neutral'], ['chipotle chicken', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["For appetizers, I'd recommend the soft shell crab, spicy New Zealand mussels, calamari and anything from the sushi bar."], "output": "[['appetizers', 'neutral'], ['soft shell crab', 'positive'], ['spicy New Zealand mussels', 'positive'], ['calamari', 'positive'], ['sushi bar', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["A cute restaurant and average food (with a small menu)."], "output": "[['food', 'neutral'], ['menu', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The staff was accomodating towards our daughter and nice enough to check up on her after they served dinner (I was a little concerned about the spices and they suggested a dish)."], "output": "[['staff', 'positive'], ['served dinner', 'neutral'], ['spices', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food was good although menu was a little limited(still plenty to chose from)."], "output": "[['Food', 'positive'], ['menu', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The manager then comes over to the table and asks us to leave - to help him out because there were people waiting!"], "output": "[['manager', 'negative'], ['waiting', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The service was good enough for a crowded place."], "output": "[['service', '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": ["So we left, the menu looked decent but you have to go when you can get one of the 2 or 3 tables."], "output": "[['menu', '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": ["Don't forget to order a raspberry lemonade or your brunch will not be complete!"], "output": "[['raspberry lemonade', 'positive'], ['brunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The guacamole at $7 is a small portion served with a stack of Si!Ortega flat taco shells."], "output": "[['guacamole', 'neutral'], ['portion', 'negative'], ['shells', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went there for a late dinner last night with a friend and the service was aweful."], "output": "[['dinner', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["As for their pasta, the tomato sauce, not the tomato basil; it's got a tang I didn't like."], "output": "[['pasta', 'neutral'], ['the tomato sauce', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There were sesame seeds on the outside (it's pizza dough not a hamburger bun), barely any sauce, VERY thin slices of mozzarella sparingly applied and topped with lots of herbs."], "output": "[['sesame', 'neutral'], ['hamburger bun', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 might have made a reservation, but you will end up waiting for about an hour anyway, so hopefully you'll get a seat at the bar and won't have to stand around."], "output": "[['reservation', 'neutral'], ['waiting', 'negative'], ['seat', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Then the waitress became upset when she returned with the drinks and we didn't stop our conversations quick enough to remind her who had ordered what only 5 minutes prior."], "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": ["Sit at the bar and eat here regularly and the sushi chef who is also the owner will hook you up the best cuts of fish."], "output": "[['bar', 'neutral'], ['sushi chef', 'positive'], ['owner', 'positive'], ['fish', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["maybe we ordered the wrong items because the food was not spectacular, with the exception of the poppy-seeded sweet beet ravioli appetizer."], "output": "[['food', 'negative'], ['beet ravioli 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": ["I'm from Italy and i felt home great and fresh food ,good pizza,i been there few times and i always go with the special or seafood, about dessert try the profitterol."], "output": "[['pizza', 'positive'], ['special', 'neutral'], ['seafood', '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": ["We poked our heads in for a few bottles of wine, some good hot onion soup and a few hot appetizers to warm us up after a seeing a show."], "output": "[['hot onion soup', 'positive'], ['hot 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": ["That being said, they do have a nice lounge area downstairs where you can just hang out, have a seat, and relax (no more waiting out in the cold or at the crowded bar)."], "output": "[['waiting', 'negative'], ['bar', 'negative'], ['lounge area', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food  Most restaurants with more than 250 items on the regular menu don't do any of them particularly well."], "output": "[['Food', 'neutral'], ['regular 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": ["Patrons can choose to be seated in the front room with a little more activity and more of a bar feel or in one of the 2 back rooms which both offer slightly quieter, more relaxed environments."], "output": "[['bar', 'neutral'], ['back rooms', 'neutral'], ['environments', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["When you go, you should ask for help from the wait staff in deciding what to order since the menu can be daunting."], "output": "[['wait staff', 'neutral'], ['menu', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The whole fish was excellent--not overcooked and served in a light tomato broth."], "output": "[['whole fish', 'positive'], ['served', 'neutral'], ['light tomato broth', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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 decor but would not recommend sitting in the communal tables unless its a very big group, much more fun getting a table and people watch while you chomp on your $20 palm sized truffle pizza."], "output": "[['decor', 'positive'], ['sized truffle pizza', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I prefer to sit in the lounge area or at the bar, as the service is quicker and the space is more attractive."], "output": "[['bar', 'neutral'], ['service', 'positive'], ['space', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I went back to telly's because i heard that they changed the Chef and the food was again, after a very very small break, was excellent again."], "output": "[['Chef', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It's really great to go in here and be able to get a creative cheap drink (they have things like blueberry mohitos for $4), a $4 plate of veggie spring rolls, and be able to joke with the bartender."], "output": "[['drink', 'positive'], ['blueberry mohitos', 'neutral'], ['veggie spring rolls', 'neutral'], ['bartender', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Tension filled the air as the chief yelled at a waiter in the middle of the bar while in uniform and drinking."], "output": "[['Tension', 'negative'], ['air', 'neutral'], ['waiter', '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": ["For dessert, the oversized bread pudding can't be beat."], "output": "[['dessert', 'neutral'], ['oversized bread 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": ["I don't have much to say about the cafe itself; you can order out from the family-run cafe in the front, or take a seat in the back, which opens up to the outdoors and can offer a less seedy and more homey atmosphere."], "output": "[['seat', '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": ["from the sandwich wraps and hot italian dishes to the creative pizzas."], "output": "[['sandwich wraps', 'neutral'], ['italian dishes', 'positive'], ['pizzas', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food While there are plenty of meat dishes, including the sweet and spicy Curry Ga with humongous slices of chicken mixed with eggplant, onions and coconut milk, and Bo Sate with sauteed beef, pineapple and crushed peanuts, seafood and vegetarian dishes make up most of the menu."], "output": "[['meat dishes', 'positive'], ['onions and coconut milk', 'neutral'], ['beef', 'neutral'], ['pineapple', 'neutral'], ['peanuts', 'neutral'], ['seafood', 'neutral'], ['vegetarian 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": ["95 all-you-can-eat lunch is tooted as a good deal but a the ambiance is dreadful and you can get a terrific meal, also kosher vegetarian, in peace with service just around the corner for $2 more."], "output": "[['meal', 'positive'], ['vegetarian', 'neutral'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Good atmosphere, the service is so-so and there is a long wait if you don't have reservations."], "output": "[['atmosphere', 'positive'], ['wait', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Even a modest bottle of wine was accurately described by the wait staff and pleasing."], "output": "[['bottle of wine', '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": ["I definitely liked the vibe in the restaurant - the food is good with enough variety to please everyone - i'd say the portions were quite skimpy where it counts - meat whether fish or steak- and for those prices this is very irksome."], "output": "[['vibe', 'neutral'], ['food', 'positive'], ['portions', 'negative'], ['fish', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["went there for dinner over the weekend and was treated rudely right away by what I think was a manager who was doing anything but managing."], "output": "[['dinner', 'neutral'], ['manager', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Come-as-you-are atmosphere, jukebox, value and James behind the bar work as a magnet."], "output": "[['atmosphere', 'positive'], ['jukebox', 'neutral'], ['value', '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": ["Our waiter never once came by the table to ask us how our meal was."], "output": "[['waiter', 'negative'], ['table', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["My dinner partner ordered the angel hair with seafood - the portion was easily big enough for two."], "output": "[['dinner', 'neutral'], ['hair', 'neutral'], ['portion', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After waiting almost an hour for a table (with resies) our waiter told us that they don't have a sommelier because no steakhouse has a sommelier (patently false), and finished with the notion that he had absolutely no idea about any of the wines on the list."], "output": "[['waiting', 'neutral'], ['waiter', 'negative'], ['wines', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Great food as usual, the paella valenciana our fave and oooh those coconut mojitos ahh!"], "output": "[['food', 'positive'], ['paella', 'neutral'], ['coconut 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": ["waitstaff was more into pushing the sparkling water than give me a wine menu."], "output": "[['waitstaff', 'negative'], ['water', 'neutral'], ['wine menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["There was a nice atmosphere except for the few pompous patrons who looked way too gaudy or a lunch time meal, but overall its a great place to eat."], "output": "[['atmosphere', 'positive'], ['lunch', '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": ["The place is huge, but it's always packed with people waiting to be seated because they made the mistake of not making a reservation!"], "output": "[['place', 'positive'], ['reservation', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I had to ask the waiter a couple of times to clear our empty glasses."], "output": "[['waiter', 'negative'], ['glasses', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The place was empty (my boyfriend and I were the only one's there other than the potty-mouthed patron's at the bar) yet the service was slow."], "output": "[['place', 'negative'], ['bar', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["It looks like a dive but serves up fresh authentic Mexican fare you won't normally find in your average Tex-Mex style restaraunt."], "output": "[['Mexican fare', 'positive'], ['restaraunt', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all 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- we had a reservation, they took forever to seat us and when they did we didn't see a waiter for about 15 minutes and he acted as if we were at some drive thru, rushing us and then ignoring our table (actually we hardly saw him at all) throughout the night."], "output": "[['reservation', 'neutral'], ['seat', 'negative'], ['waiter', 'negative'], ['night', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": [") Howver, we didn't expect to be bumped by waiters a few times during our dinner."], "output": "[['waiters', '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 momos (dumplings) are tiny with paper-thin dough, the shitake pancakes are to die for, the steamed greens (I forgot the name of the dish) is delicious as a vegetarian entry or with sauteed salmon."], "output": "[['momos (dumplings)', 'positive'], ['dough', 'positive'], ['shitake pancakes', 'positive'], ['steamed greens', 'positive'], ['dish', 'neutral'], ['salmon', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The food is undeniably good -- but not worth the wait."], "output": "[['food', 'positive'], ['wait', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Had an after-work drink at the bar with a date, loved the place so much we came back for brunch the next morning."], "output": "[['drink', 'neutral'], ['bar', 'neutral'], ['place', 'positive'], ['brunch', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["You have to be comfortable eating with your hands, sharing the same plate with your friends and be able to handle spicy food (not as spicy as some thai dishes though)."], "output": "[['plate', 'neutral'], ['thai 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": ["Last night was our second time dining here and we are still amazed with the food."], "output": "[['dining', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The cod was very good but a bit soupy in vegetable juices."], "output": "[['cod', 'positive'], ['vegetable juices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 not going to win any awards for its decor, but the food is good, the portions are big, and the prices are low."], "output": "[['decor', 'negative'], ['food', 'positive'], ['portions', 'positive'], ['prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Later, as our large party began filtering out, I overheard our waiter discussing the menu mixup to about 5 members of the staff, blaming us."], "output": "[['menu', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Atmosphere, I'd give to Rosa or Maya, but Mexican fare at Zarela is tops."], "output": "[['Atmosphere', 'negative'], ['Mexican fare', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The manager never came to our table and the restaurant didn't offer anything to compensate for the error (they could have taken the two cocktails off the check )."], "output": "[['manager', 'negative'], ['cocktails', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I've heard all the complaints about food and staff at this place, and perhaps some people have had an unfortunate encounter with the host or a cranky waiter."], "output": "[['food', 'negative'], ['staff', 'negative'], ['waiter', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["for the prices that are on the regular menu we were expecting something more upscale and less generic."], "output": "[['prices', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Ok the manager did stand at the bar the whole time looking like his wife left him, he lost all his money at the track and had been drinking the rest of the day."], "output": "[['manager', 'negative'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waitress recommended four courses, not three, given their tiny size."], "output": "[['waitress', 'neutral'], ['courses', 'neutral'], ['size', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["We were the only two people sitting out front and the waiter was unable to provide us with attentive service OR our dinner."], "output": "[['service', 'positive'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["no need for reservation) you'd expect the crew to be alittle more attentive."], "output": "[['reservation', 'neutral'], ['crew', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["While I love this place, I do recommend going here mostly for lunch or an early dinner because the crowd and long wait can be annoying."], "output": "[['lunch', 'neutral'], ['dinner', 'neutral'], ['wait', 'negative'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Service wasn't great - they accidentally gave us our neighbors' entrees, and there was a good 40-minute wait between appetizers and main courses - but the food was overall very good, particularly the desserts."], "output": "[['Service', 'positive'], ['main courses', 'neutral'], ['food', 'positive'], ['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 Scene Strictly Roots, which opened more than a decade ago as a dietary alternative to Harlem's more cholesterol- and fat-heavy fare, wears its philosophy on its facade: We serve nothing that crawls, walks, swims or flies."], "output": "[['Scene', 'neutral'], ['fare', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The presentation was clever, and the food tasty however the service that accompanied it was so slow it made us feel neglected."], "output": "[['presentation', 'positive'], ['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 menu prices are a bit expensive for what you get in quality and portion size."], "output": "[['menu prices', 'negative'], ['quality', 'neutral'], ['portion size', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Mom's cooking without the meat, the not-terribly-diverse but tempting nonetheless dinner menu is both filling and comforting, and the modest outer-boroughs price tag makes this place a definite return visit, particularly since it's only one train stop outside the city."], "output": "[['cooking', 'positive'], ['meat', 'neutral'], ['dinner menu', 'positive'], ['price tag', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Food is okay for the price, however there is definitely better thai restaurants!!"], "output": "[['Food', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In Short Though it's more of a takeout and delivery operation than a sit-down restaurant, Risotteria does offer eight small tables for those who want to savor their risotto hot off the stove."], "output": "[['delivery', 'neutral'], ['tables', 'negative'], ['risotto', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The manager came out very defensively and insisted that it was a 2 lb lobster."], "output": "[['manager', 'negative'], ['lobster', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The waiters were rude, and the appetizer dip had bits of bread in it from someone else's dinner."], "output": "[['waiters', 'negative'], ['appetizer', '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": ["Marisol at the front desk is serviceable; our sommelier, though not French, knew his Bordeaux, and our server was delightful."], "output": "[['sommelier', 'neutral'], ['server', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["After dinner we ordered a hookah and after 20 minutes waitress comes by and tried to take it away because she claims our table is reserve for another group in 10 minute."], "output": "[['dinner', 'neutral'], ['waitress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Other than making the grill flame at the beginning our hibatchi chef didnt put on much of a show - no flipping stuff into is hat or our plates - so if that is your thing go to Benihani."], "output": "[['chef', '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": ["The scene is pretty cool and the drinks are OK, but the food and service were pretty weak."], "output": "[['scene', 'positive'], ['drinks', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Once the food came, we could not eat because we did not have the little plates for the soy sauce."], "output": "[['food', 'neutral'], ['plates', 'neutral'], ['soy 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": ["Russ Pizza serves up the best lasagna I have ever tasted (sorry mom!"], "output": "[['Russ Pizza', 'neutral'], ['lasagna', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The menu is divided up into several sections, and most of the dishes are smallish plates, like tapas."], "output": "[['dishes', 'neutral'], ['plates', 'positive'], ['tapas', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Gia Lam I' s service is not much better but the food was."], "output": "[['service', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["i went in one day asking for a table for a group and was greeted by a very rude hostess."], "output": "[['table', 'neutral'], ['hostess', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food Former Chef of Washington Park Daniel Eardley leans heavily on seasonal ingredients: An autumn appetizer of duck salad bursts with ripe pomegranate seeds; tender grilled octopus with peppers and turnips is a starter must for every table."], "output": "[['ingredients', 'positive'], ['appetizer', 'neutral'], ['ripe pomegranate seeds', 'neutral'], ['grilled octopus', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at 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 guest from Montana wanted to get a NY Strip Steak while she was here, and New York magazine wrote up Monkey Bar as a good place."], "output": "[['Steak', 'neutral'], ['Bar', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Scene Petite Abeille is ideal for a lazy lunch, a restorative brunch or light dinner."], "output": "[['Scene', 'positive'], ['lunch', 'neutral'], ['brunch', 'neutral'], ['dinner', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["They bring over your favorite beverage before you sit down and while dining you listen to a killer jukebox."], "output": "[['dining', 'neutral'], ['jukebox', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["Don't let the decor fool you because you will miss out in some of the best food you ever eaten."], "output": "[['decor', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["In Short A dark, narrow takeout area gives way to small tables in a cozy space decorated to resemble a Bedouin tent."], "output": "[['takeout', 'negative'], ['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": ["Spinache rolls have lots of garlic."], "output": "[['rolls', 'neutral'], ['garlic', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["I use to always get the turkey club, until recently where I have gotten more bread than turkey."], "output": "[['turkey club', 'neutral'], ['bread', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The decor is worth a mention, with plush seating areas that range from bar stools to table/chair combos to full sofa areas."], "output": "[['decor', 'positive'], ['bar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect term and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The decor is not special at all but their food and amazing prices make up for it.\"  Output: [['decor', 'negative'], ['food', 'positive'], ['prices', 'positive']] "}
{"task_type": "generation", "dataset": "mams", "input": ["The Food The menu is better suited to the snacking at the long bar than dining in the compact dining area."], "output": "[['Food', 'positive'], ['snacking', '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": ["Another favorite is the hanger steak which is always cooked to perfection and served with a generous amount of arugula and a balsamic vinegar reduction served as a sauce."], "output": "[['hanger steak', 'positive'], ['amount of arugula', 'positive'], ['a balsamic vinegar reduction served', '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']] "}