{"task_type": "generation", "dataset": "semeval-2014", "input": ["The portions are small but being that the food was so good makes up for that."], "output": "{'aspect_term': [['portions', 'negative'], ['food', 'positive']], 'aspect_category': [[None, 'negative'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The service is ok but could be better."], "output": "{'aspect_term': [['service', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Ambiance is barely romantic but management tries."], "output": "{'aspect_term': [['Ambiance', 'negative'], ['management', 'positive']], 'aspect_category': [[None, 'negative'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The first time I went, and was completely taken by the live jazz band and atmosphere, I ordered the Lobster Cobb Salad."], "output": "{'aspect_term': [['live jazz band', 'positive'], ['atmosphere', 'positive'], ['Lobster Cobb Salad', 'neutral']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The food's dazzling flavors overwhelm the palate, truly embracing the beauty of authentic Thai cuisine."], "output": "{'aspect_term': [['food', 'positive'], ['Thai cuisine', 'positive'], ['flavors', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["What an amazing meal and experience!"], "output": "{'aspect_term': [['meal', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The Yellowtail was particularly good as well."], "output": "{'aspect_term': [['Yellowtail', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["This place has the best interior I have seen anywhere in the northside of W'burg, and will impress whoever you bring there."], "output": "{'aspect_term': [['interior', 'positive'], ['place', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Wait staff is blantently unappreciative of your business but its the best pie on the UWS!"], "output": "{'aspect_term': [['Wait staff', 'negative'], ['pie', 'positive']], 'aspect_category': [[None, 'negative'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["We a menu that rearely changes,e xcept for one or two specials, the quality and care they put in thier food in evident."], "output": "{'aspect_term': [['quality', 'positive'], ['care', 'positive'], ['food', 'positive'], ['specials', 'neutral']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The location is perfect."], "output": "{'aspect_term': [['location', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The menu was impressive with selections ranging from a burger, to steak, to escargot."], "output": "{'aspect_term': [['menu', 'positive'], ['burger', 'neutral'], ['steak', 'neutral'], ['escargot', 'neutral']], 'aspect_category': [[None, 'positive'], [None, 'neutral'], [None, 'neutral'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The wine is always good, the tapas are always yummy, especially with the warm pita bread."], "output": "{'aspect_term': [['wine', 'positive'], ['tapas', 'positive'], ['pita bread', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["at night, but it's hard to hear your own conversation with everyone else competing for that same luxury - the music playing in the background is also voluminous."], "output": "{'aspect_term': [['music', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Fish was overdone."], "output": "{'aspect_term': [['Fish', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The fish is fresh but the variety of fish is nothing out of ordinary."], "output": "{'aspect_term': [['fish', 'positive'], ['variety of fish', 'negative']], 'aspect_category': [[None, 'positive'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["My fish was delicious in an incredible curry sauce."], "output": "{'aspect_term': [['fish', 'positive'], ['curry sauce', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The plain slice is great and if you get toppings, the whole slice is topped with them, not sparsely sprinkled on like some places."], "output": "{'aspect_term': [['plain slice', 'positive'], ['toppings', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The fish was adequate, but inexpertly sliced."], "output": "{'aspect_term': [['fish', 'conflict']], 'aspect_category': [[None, 'conflict']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Even with the prix fixe pricing, this restaurant is not worth it."], "output": "{'aspect_term': [['prix fixe pricing', 'conflict']], 'aspect_category': [[None, 'conflict']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["skip dessert."], "output": "{'aspect_term': [['dessert', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["If you want a casual neighborhood bistro that has great food and excellent service, this is the place."], "output": "{'aspect_term': [['food', 'positive'], ['service', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The service is fantastic."], "output": "{'aspect_term': [['service', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The strong scents coming from the left and right of me negatively affected my taste buds."], "output": "{'aspect_term': [['scents', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["More important, the sushi rivals the best in Tokyo."], "output": "{'aspect_term': [['sushi', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["one of the best Chicken Tikka Masala."], "output": "{'aspect_term': [['Chicken Tikka Masala', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["And it all comes at a very reasonable price (congee, noodles, and rice dishes are no more than $3-6 each)."], "output": "{'aspect_term': [['price', 'positive'], ['congee', 'neutral'], ['noodles', 'neutral'], ['rice dishes', 'neutral']], 'aspect_category': [[None, 'positive'], [None, 'neutral'], [None, 'neutral'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The view is spectacular, and the food is great."], "output": "{'aspect_term': [['view', 'positive'], ['food', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["To be completely fair, the only redeeming factor was the food, which was above average, but couldn't make up for all the other deficiencies of Teodora."], "output": "{'aspect_term': [['food', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Service was also very good."], "output": "{'aspect_term': [['Service', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["After we got our sashimi order, I could not believe how small the portions were!"], "output": "{'aspect_term': [['sashimi', 'neutral'], ['portions', 'negative']], 'aspect_category': [[None, 'neutral'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The corned beef and pastrami are excellent, much less fatty than those big tourist places around Times Square."], "output": "{'aspect_term': [['corned beef', 'positive'], ['pastrami', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Frites were delicious if a bit on the thick side."], "output": "{'aspect_term': [['Frites', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["A cheap eat for NYC, but not for dosa."], "output": "{'aspect_term': [['dosa', 'negative'], ['eat', 'positive']], 'aspect_category': [[None, 'negative'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["We ate out in the back patio, which is worth it as it's cool and the music is hear well there."], "output": "{'aspect_term': [['back patio', 'positive'], ['music', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["They pray to their Food Gods to make them into a good pizza like VT's."], "output": "{'aspect_term': [['pizza', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Food is excellent."], "output": "{'aspect_term': [['Food', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["So, a little inconsistency there but either way, both pizzas were really good."], "output": "{'aspect_term': [['pizzas', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I recently went to this restaurant with some co-workers for lunch and had an amazing time."], "output": "{'aspect_term': [['lunch', 'neutral']], 'aspect_category': [[None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["It is kinda nosiy and the tables are close together but it's still a beautiful place to enjoy a nice dinner."], "output": "{'aspect_term': [['tables', 'negative'], ['dinner', 'positive'], ['place', 'positive']], 'aspect_category': [[None, 'negative'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Obv caviar is top of the line but the rest of the menu is so diverse it gives you a chance to taste so manydifferent varietys."], "output": "{'aspect_term': [['Obv caviar', 'positive'], ['menu', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["After my 3rd time the manager remembered me and treated me like an usual customer."], "output": "{'aspect_term': [['manager', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["One of my favorites though was the Angry Lobster, a cold lobster salad that was magnificent."], "output": "{'aspect_term': [['Angry Lobster', 'positive'], ['cold lobster salad', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The vibe is very relaxed and cozy, service was great and the food was excellent!"], "output": "{'aspect_term': [['vibe', 'positive'], ['service', 'positive'], ['food', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["While the place is not a hotspot hangout, the drinks are unique and pack a lot of bang for the buck."], "output": "{'aspect_term': [['drinks', 'positive'], ['place', 'negative']], 'aspect_category': [[None, 'positive'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I ate here a week ago and found most dishes average at best and too expensive."], "output": "{'aspect_term': [['dishes', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Not the greatest sushi place, but excellent for a $19.95 all you can eat."], "output": "{'aspect_term': [['sushi place', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Pizza here is consistently good."], "output": "{'aspect_term': [['Pizza', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Whenever you need a Sushi fix, Mizu will be there with quality fish and great service."], "output": "{'aspect_term': [['fish', 'positive'], ['service', 'positive'], ['Sushi fix', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I had Filet Mignon with garlic mash."], "output": "{'aspect_term': [['Filet Mignon with garlic mash', 'neutral']], 'aspect_category': [[None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The food itself was just ok - nothing spectacular - but the service was awful."], "output": "{'aspect_term': [['food', 'neutral'], ['service', 'negative']], 'aspect_category': [[None, 'neutral'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Service was devine, oysters where a sensual as they come, and the price can't be beat!!!"], "output": "{'aspect_term': [['Service', 'positive'], ['oysters', 'positive'], ['price', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Terrible, terrible management - deserves to be shut-down."], "output": "{'aspect_term': [['management', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["This is a wonderful place on all stand points especially value ofr money."], "output": "{'aspect_term': [['value ofr money', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Definite go if you're used to good Indian restaurant food from abroad."], "output": "{'aspect_term': [['Indian restaurant food', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["THe Pizza and wine were excellent-the service too--but what really MADE this place was the backyard dining area."], "output": "{'aspect_term': [['Pizza', 'positive'], ['wine', 'positive'], ['service', 'positive'], ['backyard dining area', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Pizza and garlic knots are great as well, I order from them quite often and the delivery is always super quick!"], "output": "{'aspect_term': [['Pizza', 'positive'], ['delivery', 'positive'], ['garlic knots', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The steak is good, the fish is good and the sushi was surprisingly great."], "output": "{'aspect_term': [['steak', 'positive'], ['fish', 'positive'], ['sushi', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Decor leaves something to be desired."], "output": "{'aspect_term': [['Decor', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["sandwiches tho pricey are over stuffed - can serve 2 persons easily thus cost effective!"], "output": "{'aspect_term': [['sandwiches', 'conflict']], 'aspect_category': [[None, 'conflict']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Delicate spices, onions, eggs and a kick-ass roti."], "output": "{'aspect_term': [['spices', 'positive'], ['onions', 'positive'], ['eggs', 'positive'], ['roti', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The atmosphere is nothing special, but it feels like a Sushi establishment in Tokyo."], "output": "{'aspect_term': [['atmosphere', 'neutral']], 'aspect_category': [[None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Once for dinner and once for brunch."], "output": "{'aspect_term': [['dinner', 'neutral'], ['brunch', 'neutral']], 'aspect_category': [[None, 'neutral'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The food was terrific and the service classy, attentive, without being overbearing."], "output": "{'aspect_term': [['food', 'positive'], ['service', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["We were seated outside and the waiter spilled red wine and hot tea on myself and my date."], "output": "{'aspect_term': [['waiter', 'negative'], ['red wine', 'neutral'], ['hot tea', 'neutral'], ['outside', 'neutral']], 'aspect_category': [[None, 'negative'], [None, 'neutral'], [None, 'neutral'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The table next to us asked if he crushed the grapes himself when their long overdue bottle of wine finally arrived."], "output": "{'aspect_term': [['bottle of wine', 'neutral'], ['grapes', 'neutral']], 'aspect_category': [[None, 'neutral'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["even the wine by the glass was good."], "output": "{'aspect_term': [['wine by the glass', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["We've only eaten in the restaurant once, but we have ordered many times for dinner."], "output": "{'aspect_term': [['dinner', 'neutral']], 'aspect_category': [[None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The last time I went we were seated at a table in a corridor next to the kitchen."], "output": "{'aspect_term': [['table', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Had 1 appetizer, 2 entrees and 2 cokes and the bill was ~$55.00, not including tip."], "output": "{'aspect_term': [['appetizer', 'neutral'], ['entrees', 'neutral'], ['cokes', 'neutral'], ['bill', 'neutral']], 'aspect_category': [[None, 'neutral'], [None, 'neutral'], [None, 'neutral'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Decor is nice though service can be spotty."], "output": "{'aspect_term': [['Decor', 'positive'], ['service', 'negative']], 'aspect_category': [[None, 'positive'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Order the panang duck, it's fantastic."], "output": "{'aspect_term': [['panang duck', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Went there and had a combination of different seafood dishes and appetizers."], "output": "{'aspect_term': [['seafood dishes', 'neutral'], ['appetizers', 'neutral']], 'aspect_category': [[None, 'neutral'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["delicious bagels, especially when right out of the oven."], "output": "{'aspect_term': [['bagels', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["If you want Americanized Chinese food with your usual watery, generic white sauce, this is your place."], "output": "{'aspect_term': [['white sauce', 'negative'], ['Chinese food', 'neutral']], 'aspect_category': [[None, 'negative'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The food is great, service is ok."], "output": "{'aspect_term': [['food', 'positive'], ['service', 'neutral']], 'aspect_category': [[None, 'positive'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The service is fine and they allow you to enjoy the view."], "output": "{'aspect_term': [['service', 'positive'], ['view', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["While there are plenty of places to go for a good corned beef sandwich, Katz's has a charm about it."], "output": "{'aspect_term': [['corned beef sandwich', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Best of all is the warm vibe, the owner is super friendly and service is fast."], "output": "{'aspect_term': [['vibe', 'positive'], ['owner', 'positive'], ['service', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["That is a problem since we paid about 20 bucks a dish, and had to order 5 dishes to get a decent taste."], "output": "{'aspect_term': [['dish', 'negative'], ['taste', 'neutral'], ['dishes', 'negative']], 'aspect_category': [[None, 'negative'], [None, 'neutral'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["This is the best sushi in new york city - hands down."], "output": "{'aspect_term': [['sushi', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The sushi is also great!"], "output": "{'aspect_term': [['sushi', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Great service, great food."], "output": "{'aspect_term': [['service', 'positive'], ['food', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I LOVED THE SHOWS."], "output": "{'aspect_term': [['SHOWS', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Saul is pretty good, but definitely not great."], "output": "{'aspect_term': [['Saul', 'neutral']], 'aspect_category': [[None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The food came out wrong, the waiter was no where to be found and the wine showed up at the end of the meal."], "output": "{'aspect_term': [['food', 'negative'], ['waiter', 'negative'], ['wine', 'negative'], ['meal', 'neutral']], 'aspect_category': [[None, 'negative'], [None, 'negative'], [None, 'negative'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Great Indian food and the service is incredible."], "output": "{'aspect_term': [['Indian food', 'positive'], ['service', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Even after getting pushed out by the no-class Famous Ray's, Sal has risen again to carry on his father's uncle's legacies with a smile, true love for his community, and let's not forget the Outstanding Pizza!"], "output": "{'aspect_term': [['Pizza', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I don't know who they think they are but they have no respect for the residents of the neighborhood ever since they opened their cabaret next door and blasts loud music till three in the morning every weekend during the summer."], "output": "{'aspect_term': [['music', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The sandwhiches are out-of-this world!"], "output": "{'aspect_term': [['sandwhiches', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The food is terrible and overall, I would have to say avoid at all costs."], "output": "{'aspect_term': [['food', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The Halibut was too salty, dessert was so so (don't waste any of your calories) and service was poor."], "output": "{'aspect_term': [['Halibut', 'negative'], ['dessert', 'neutral'], ['service', 'negative']], 'aspect_category': [[None, 'negative'], [None, 'neutral'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The pesto pizza was excellent, thin-crust pizza with a nice amount of spicy Italian cheese that I'd never heard of before."], "output": "{'aspect_term': [['pesto pizza', 'positive'], ['Italian cheese', 'positive'], ['thin-crust pizza', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Forget the rush and the wait and the noise (which isn't actually that bad), I mean please, who goes to a steakhouse to be coddled and romantic?"], "output": "{'aspect_term': [['wait', 'conflict'], ['noise', 'conflict'], ['rush', 'conflict']], 'aspect_category': [[None, 'conflict'], [None, 'conflict'], [None, 'conflict']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["This place is incredibly tiny."], "output": "{'aspect_term': [['place', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The fillings may be unconventional but the dosa batter is definitely authentic and the combinations very tasty."], "output": "{'aspect_term': [['fillings', 'neutral'], ['dosa batter', 'positive']], 'aspect_category': [[None, 'neutral'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Other apetizers and food"], "output": "{'aspect_term': [['apetizers', 'neutral'], ['food', 'neutral']], 'aspect_category': [[None, 'neutral'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The food is authentic Italian - delicious!"], "output": "{'aspect_term': [['food', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I had a late dinner at Lucky Stike, a great name for a joint if ever I saw one."], "output": "{'aspect_term': [['dinner', 'neutral']], 'aspect_category': [[None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["My friend's food was also the complete opposite of what it's supposed to taste like (aND look like)."], "output": "{'aspect_term': [['food', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Though you will undoubtedly be seated at a table with what seems like barely enough room (no matter what the size of your party), the warm atomosphere is worth the cramped quarters- you'll have fun and forgot about the tight spot you're in."], "output": "{'aspect_term': [['table', 'negative'], ['atomosphere', 'positive'], ['room', 'negative'], ['spot', 'negative']], 'aspect_category': [[None, 'negative'], [None, 'positive'], [None, 'negative'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["We were in search of food and stumbled on this block of Indian restaurants on East Sixth Street."], "output": "{'aspect_term': [['food', 'neutral']], 'aspect_category': [[None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Best Reuben sandwich ever!"], "output": "{'aspect_term': [['Reuben sandwich', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Food was OK - fish was cooked well."], "output": "{'aspect_term': [['Food', 'neutral'], ['fish', 'positive']], 'aspect_category': [[None, 'neutral'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Lived in Shanghai most of my life and thought the food was comparable to the flagship Green Bo restaurant there."], "output": "{'aspect_term': [['food', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["From the terrible service, to the bland food, not to mention the unaccommodating managers, the overall experience was horrible."], "output": "{'aspect_term': [['service', 'negative'], ['food', 'negative'], ['managers', 'negative']], 'aspect_category': [[None, 'negative'], [None, 'negative'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["My husband had the mesclun, salmon, and ice cream and he enjoyed all 3 courses."], "output": "{'aspect_term': [['mesclun', 'positive'], ['salmon', 'positive'], ['ice cream', 'positive'], ['courses', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The workers there also absolutely load the bagel with cream cheese (gets a little messy)."], "output": "{'aspect_term': [['workers', 'neutral'], ['bagel', 'neutral'], ['cream cheese', 'neutral']], 'aspect_category': [[None, 'neutral'], [None, 'neutral'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The food was great."], "output": "{'aspect_term': [['food', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I would definitely go back for a very special occasion, but not for regular fine dining."], "output": "{'aspect_term': [['dining', 'neutral']], 'aspect_category': [[None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The sangria was pretty tasty and good on a hot muggy day."], "output": "{'aspect_term': [['sangria', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The hot dogs were cold in the middle and the buns were stale."], "output": "{'aspect_term': [['hot dogs', 'negative'], ['buns', 'negative']], 'aspect_category': [[None, 'negative'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["While the $20 entree range is not overly expensive, in New York City, there is definitely better food in that range, and so Sapphire, despite it's lovely atmosphere, will most likely not be a restaurant to which I will return."], "output": "{'aspect_term': [['food', 'negative'], ['atmosphere', 'positive'], ['entree range', 'positive']], 'aspect_category': [[None, 'negative'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Then, get ripped on free box wine."], "output": "{'aspect_term': [['box wine', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Its an excellent place to relax and the food is one of the best in the city of New York."], "output": "{'aspect_term': [['place', 'positive'], ['food', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["We had crawfish boiled and despite making a mess, it was a ton of fun and quite tasty as well."], "output": "{'aspect_term': [['crawfish boiled', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I recommend getting a reservation even though we saw people seated without one."], "output": "{'aspect_term': [['reservation', 'neutral']], 'aspect_category': [[None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Went there with my wife and we had to wait for a table even though you could see there many that were empty with not reservation sigh on them."], "output": "{'aspect_term': [['reservation sigh', 'neutral'], ['table', 'negative']], 'aspect_category': [[None, 'neutral'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Unfortunately, the food is outstanding, but everything else about this restaurant is the pits."], "output": "{'aspect_term': [['food', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Service was very prompt but slightly rushed."], "output": "{'aspect_term': [['Service', 'conflict']], 'aspect_category': [[None, 'conflict']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I didn't complain, I liked the atmosphere so much."], "output": "{'aspect_term': [['atmosphere', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Plus they made a perfect martini."], "output": "{'aspect_term': [['martini', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The chicken pot pie is excpetiona, the cheeseburger huge and delictable, and the service professional wan warm."], "output": "{'aspect_term': [['The chicken pot pie', 'positive'], ['cheeseburger', 'positive'], ['service', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The wine selection (by the glass and bottle) is wonderful and I always recommend that friends make a reservation if they're going to be in town."], "output": "{'aspect_term': [['wine selection', 'positive'], ['reservation', 'neutral']], 'aspect_category': [[None, 'positive'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["This is definitely an  excellent date spot because of the ambiance and on the weekends the  night scene is more than alive."], "output": "{'aspect_term': [['ambiance', 'positive'], ['night scene', 'positive'], ['spot', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["both are very reasonably priced (around $8 for dinner and $5 for lunch), and are delicious and filling."], "output": "{'aspect_term': [['priced', 'positive'], ['dinner', 'positive'], ['lunch', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Their whitefish salad is excellent--all whitefish with a little mayo."], "output": "{'aspect_term': [['whitefish salad', 'positive'], ['whitefish', 'positive'], ['mayo', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I fell in love with the egg noodles in the beef broth with shrimp dumplings and slices of BBQ roast pork."], "output": "{'aspect_term': [['egg noodles in the beef broth with shrimp dumplings and slices of BBQ roast pork', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["It's also attached to Angel's Share, which is a cool, more romantic bar..."], "output": "{'aspect_term': [['bar', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The freshest, best variety, and the fastest delivery."], "output": "{'aspect_term': [['variety', 'positive'], ['delivery', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The staff is accomodating, the ambiance is exciting and yet relaxed, and the food is out of this world!"], "output": "{'aspect_term': [['staff', 'positive'], ['ambiance', 'positive'], ['food', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I also ordered for delivery and the restaurant forgot half the order."], "output": "{'aspect_term': [['delivery', 'negative'], ['order', 'negative']], 'aspect_category': [[None, 'negative'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The photobook menu was a cute touch, certainly helped my group and I pick the fried chicken, pork chop, and noodle dishes that we all ordered."], "output": "{'aspect_term': [['menu', 'positive'], ['fried chicken', 'neutral'], ['pork chop', 'neutral'], ['noodle dishes', 'neutral']], 'aspect_category': [[None, 'positive'], [None, 'neutral'], [None, 'neutral'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["There are other people waiting!"], "output": "{'aspect_term': [['waiting', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I didn't expect to like Nosh as much as I did, but the pastrami on challah sandwich I had was otherworldly, the soups are like Mom's, and the knishes give Yonah Schimmel's a run for its money."], "output": "{'aspect_term': [['pastrami on challah sandwich', 'positive'], ['soups', 'positive'], ['knishes', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["all the food was excellent - considering the quality of food in most moderately priced restaurants is mediocre this was slightly more pricey and well worth it."], "output": "{'aspect_term': [['food', 'positive'], ['quality of food', 'positive'], ['priced', 'neutral']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The food was absolutely amazing!!"], "output": "{'aspect_term': [['food', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["There was a long wait for a table outside, but it was a little too hot in the sun anyway so our insde table was very nice."], "output": "{'aspect_term': [['table', 'neutral'], ['insde table', 'positive'], ['wait', 'negative']], 'aspect_category': [[None, 'neutral'], [None, 'positive'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["When we sat, we got great and fast service."], "output": "{'aspect_term': [['service', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The all-Italian staff is warm and engaging from the start."], "output": "{'aspect_term': [['staff', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Light, refreshing summer rolls (not fried) remind me of Vietnamese places in Paris."], "output": "{'aspect_term': [['summer rolls', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The second you walk through the heavy vault like door, with people anticipating your arrival you get the sense that you are going to have the dining ride of a lifetime."], "output": "{'aspect_term': [['door', 'neutral']], 'aspect_category': [[None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Raga stands out with an interesting fusion of French and Indian cooking."], "output": "{'aspect_term': [['fusion of French and Indian cooking', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["With the exception of our lemon salad that had so much pepper on it that our eyes started watering, the food here was decent, not great."], "output": "{'aspect_term': [['food', 'neutral'], ['lemon salad', 'negative'], ['pepper', 'negative']], 'aspect_category': [[None, 'neutral'], [None, 'negative'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["We laughed when he finally offered us a dessert menu and we left a 10 percent tip, which was generous, I feel."], "output": "{'aspect_term': [['dessert menu', 'neutral'], ['tip', 'positive']], 'aspect_category': [[None, 'neutral'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Every course was better than the next."], "output": "{'aspect_term': [['course', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Barbecued codfish was gorgeously moist - as if poached - yet the fabulous texture was let down by curiously bland seasoning - a spice rub might have overwhelmed, however herb mix or other sauce would have done much to enhance."], "output": "{'aspect_term': [['Barbecued codfish', 'positive'], ['seasoning', 'negative'], ['texture', 'conflict'], ['spice rub', 'negative'], ['herb mix', 'negative'], ['sauce', 'negative']], 'aspect_category': [[None, 'positive'], [None, 'negative'], [None, 'conflict'], [None, 'negative'], [None, 'negative'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["They are the best bagels I've had."], "output": "{'aspect_term': [['bagels', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The ambience is authentic and relaxing and we have always received attentive and prompt service."], "output": "{'aspect_term': [['ambience', 'positive'], ['service', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Stay away from the two specialty rolls on the menu, though- too much avocado and rice will fill you up right quick."], "output": "{'aspect_term': [['rolls', 'negative'], ['menu', 'neutral'], ['avocado', 'negative'], ['rice', 'negative']], 'aspect_category': [[None, 'negative'], [None, 'neutral'], [None, 'negative'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["First went here to enjoy their garden terrace."], "output": "{'aspect_term': [['garden terrace', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["They have a huge selection of different cream cheeses and all of their salads are great."], "output": "{'aspect_term': [['cream cheeses', 'positive'], ['salads', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["All of the pizzas are terrific and the price is even better!"], "output": "{'aspect_term': [['pizzas', 'positive'], ['price', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Especially liked chicken tikka and the naan, and the dals."], "output": "{'aspect_term': [['chicken tikka', 'positive'], ['naan', 'positive'], ['dals', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["It's like they took leftover chicken, poured oil and sprinkled pepper powder over it (the sauce was translucent and red)."], "output": "{'aspect_term': [['chicken', 'negative'], ['oil', 'neutral'], ['pepper powder', 'neutral'], ['sauce', 'negative']], 'aspect_category': [[None, 'negative'], [None, 'neutral'], [None, 'neutral'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Other than the crappy service from two individuals, it's great."], "output": "{'aspect_term': [['service', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I wasn't there for the Half-Price Saturday Night Special, but Tuesday Night."], "output": "{'aspect_term': [['Half-Price Saturday Night Special', 'neutral']], 'aspect_category': [[None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The Thali was small, thoroughly unremarkable, and $14.95."], "output": "{'aspect_term': [['Thali', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The menu may be small, but everything on it is delicious."], "output": "{'aspect_term': [['menu', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["they were able to squeeze me in at 6 after i called the night before my anniversary for a friday night reservation and told me they'd treat us well for the occasion."], "output": "{'aspect_term': [['reservation', 'neutral']], 'aspect_category': [[None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["being a fan of spicy ethnic foods, indian included, i made friends with this place long ago."], "output": "{'aspect_term': [['spicy ethnic foods', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The only possible drawback to this last point is that as of the date of this posting, the additional menu items are only written in Chinese."], "output": "{'aspect_term': [['menu items', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["For authentic Thai food, look no further than Toons."], "output": "{'aspect_term': [['Thai food', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Sauce was watery and the food didn't have much flavor."], "output": "{'aspect_term': [['Sauce', 'negative'], ['food', 'negative'], ['flavor', 'negative']], 'aspect_category': [[None, 'negative'], [None, 'negative'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["They do cater to American palates, but if you like it hot let them know and they are more than willing to oblige!"], "output": "{'aspect_term': [['cater', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Not a typical pizza joint, but good for a low key and fairly cheap nice sit down dinner."], "output": "{'aspect_term': [['dinner', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Highly recommended is the Spicy Fried Clam Rolls and Spider Rolls."], "output": "{'aspect_term': [['Spicy Fried Clam Rolls', 'positive'], ['Spider Rolls', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I recommend the meatballs and caprese salad and the beans on toast were a wonderful start to the meal!"], "output": "{'aspect_term': [['meatballs', 'positive'], ['caprese salad', 'positive'], ['beans on toast', 'positive'], ['meal', 'neutral']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Overall, the best bagel in town."], "output": "{'aspect_term': [['bagel', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The $300 bill was a bit steep, but the experience was great."], "output": "{'aspect_term': [['bill', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["While the food was good (certainly no Il Mulino) the service was horrendous."], "output": "{'aspect_term': [['food', 'positive'], ['service', 'negative']], 'aspect_category': [[None, 'positive'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I was in love with Pongsri on 48th, but compared to Suan it is slow in service and overpriced."], "output": "{'aspect_term': [['service', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["My wife and I always enjoy the young, not always well trained but nevertheless friendly, staff, all of whom have a story."], "output": "{'aspect_term': [['staff', 'conflict']], 'aspect_category': [[None, 'conflict']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["It is also extremely well priced."], "output": "{'aspect_term': [['priced', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["we did notice however, that some tables had what looked like pita instead of naan."], "output": "{'aspect_term': [['pita', 'negative'], ['naan', 'negative']], 'aspect_category': [[None, 'negative'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["As far as the service goes, the waitresses were not particularly friendly, but they got the job done."], "output": "{'aspect_term': [['service', 'conflict'], ['waitresses', 'conflict']], 'aspect_category': [[None, 'conflict'], [None, 'conflict']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Excellent atmosphere, delicious dishes good and friendly service."], "output": "{'aspect_term': [['atmosphere', 'positive'], ['dishes', 'positive'], ['service', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I was really disappointed ant wanted to tell everyone not to go eat or even take out food from there."], "output": "{'aspect_term': [['food', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Great food (spinach and corn dumplings and massamman curry), very friendly and no nonsense service and a clean and funky bathroom."], "output": "{'aspect_term': [['food', 'positive'], ['spinach and corn dumplings', 'positive'], ['service', 'positive'], ['bathroom', 'positive'], ['massamman curry', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I found the variety of the sashimi plate to be satisfying - fresh and yummy."], "output": "{'aspect_term': [['sashimi plate', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The staff is no nonsense."], "output": "{'aspect_term': [['staff', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The sandwiches are dry, tasteless and way overpriced."], "output": "{'aspect_term': [['sandwiches', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I highly recommend Cafe St. Bart's for their food, the ambience and wonderful service."], "output": "{'aspect_term': [['food', 'positive'], ['ambience', 'positive'], ['service', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["It's the perfect restaurant for NY life style, it got cool design, awsome drinks and food and lot's of good looking people eating and hanging at the pink bar..."], "output": "{'aspect_term': [['design', 'positive'], ['drinks', 'positive'], ['food', 'positive'], ['bar', 'neutral']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["great wine list (italian), good food, service was INITIALLY fine."], "output": "{'aspect_term': [['wine list', 'positive'], ['food', 'positive'], ['service', 'conflict']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'conflict']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The food there is so good that even to order out the wait is incredible."], "output": "{'aspect_term': [['food', 'positive'], ['wait', 'negative']], 'aspect_category': [[None, 'positive'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["And at the conclusion of this culinary nightmare the check was given to our table by knocking over a glass of water."], "output": "{'aspect_term': [['check', 'neutral'], ['table', 'neutral'], ['glass of water', 'neutral']], 'aspect_category': [[None, 'neutral'], [None, 'neutral'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["No gimmicks here -- the food speaks for itself in its freshness and preparation."], "output": "{'aspect_term': [['food', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["This big draw is the all you can sushi here for $19.95!"], "output": "{'aspect_term': [['sushi', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["great place to go for a drink too because they have 100 kinds of beer."], "output": "{'aspect_term': [['kinds of beer', 'positive'], ['drink', 'neutral']], 'aspect_category': [[None, 'positive'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["All of my co-workers stated that the food was amazing and wondered why they hadn't heard about this place."], "output": "{'aspect_term': [['food', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["My husband and I enjoy Sangria."], "output": "{'aspect_term': [['Sangria', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I have eaten there 3-4 times and the food was always good."], "output": "{'aspect_term': [['food', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["otherwise, good stuff for late nite eats."], "output": "{'aspect_term': [['stuff', 'positive'], ['eats', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I choose to go with one of the special, the braised lamb shank in red wine, which was excellent."], "output": "{'aspect_term': [['braised lamb shank in red wine', 'positive'], ['special', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The staff has been nice, but they seemed really stressed and the unisex bathroom needs to be cleaned more often."], "output": "{'aspect_term': [['staff', 'conflict'], ['bathroom', 'negative']], 'aspect_category': [[None, 'conflict'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I must warn the reader that the portions sizes are very small (especially the appetizers), so if you plan to eat until you are full and do not intend to order the chef's special tasting menu, prepare to order and pay for an appetizer (1 dish for each person because the portions are not for sharing), a main entree, and the cold udon at the end of the meal."], "output": "{'aspect_term': [['portions', 'negative'], ['appetizers', 'negative'], ['appetizer', 'negative'], ['main entree', 'neutral'], ['cold udon', 'neutral'], ['chef', 'positive'], ['menu', 'positive'], ['dish', 'negative'], ['portions', 'negative']], 'aspect_category': [[None, 'negative'], [None, 'negative'], [None, 'negative'], [None, 'neutral'], [None, 'neutral'], [None, 'positive'], [None, 'positive'], [None, 'negative'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["This restaurant is a wonderful place to go many times and it is reasonably priced."], "output": "{'aspect_term': [['priced', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["We made early dinner reservations and were thoroughly impressed, reminds me of my grandfather, its old school Italian scenery with lots of fun stuff to admire."], "output": "{'aspect_term': [['scenery', 'positive'], ['dinner reservations', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I have lived in Japan for 7 years and the taste of the food and the feel of the restaurant is like being back in Japan."], "output": "{'aspect_term': [['food', 'positive'], ['feel', 'positive'], ['taste', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Despite the fact that the space is large, they've overcrowded the floor with tables."], "output": "{'aspect_term': [['space', 'positive'], ['tables', 'negative']], 'aspect_category': [[None, 'positive'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The cream cheeses are out of this world and I love that coffee!!"], "output": "{'aspect_term': [['cream cheeses', 'positive'], ['coffee', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Service is not exactly five star, but thats not really a big deal."], "output": "{'aspect_term': [['Service', 'conflict']], 'aspect_category': [[None, 'conflict']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Our family never expected such incredible entertainment in a restaurant."], "output": "{'aspect_term': [['entertainment', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Their tuna tartar appetizer is to die for."], "output": "{'aspect_term': [['tuna tartar appetizer', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Nevertheless the food itself is pretty good."], "output": "{'aspect_term': [['food', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Tasty steak, pork loin, the works."], "output": "{'aspect_term': [['steak', 'positive'], ['pork loin', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["instead ordered an ice cold beer which to me works with indian."], "output": "{'aspect_term': [['beer', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["We were looking forward to nice glass of Sangria when we arrived."], "output": "{'aspect_term': [['glass of Sangria', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["if you're looking for perfect traditional sushi, go here - if you're looking for interesting combinations, try sushi of gari's (east side)."], "output": "{'aspect_term': [['sushi', 'positive'], ['sushi', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Pick a bagel has the best bagels in the city."], "output": "{'aspect_term': [['bagels', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["We had the pot-stickers which were great and a tempura dish that was great."], "output": "{'aspect_term': [['pot-stickers', 'positive'], ['tempura dish', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["But, they were too big for the bun."], "output": "{'aspect_term': [['bun', 'neutral']], 'aspect_category': [[None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["It looked like shredded cheese partly done - still in strips."], "output": "{'aspect_term': [['shredded cheese', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Try the green curry!!!"], "output": "{'aspect_term': [['green curry', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Also, if you don't want to sit at a certain table, you don't have to!"], "output": "{'aspect_term': [['table', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["You are paying for the atmosphere, which is nice, but can be had in numerous places in Bay Ridge."], "output": "{'aspect_term': [['atmosphere', 'conflict']], 'aspect_category': [[None, 'conflict']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Service was on par but not wonderful."], "output": "{'aspect_term': [['Service', 'conflict']], 'aspect_category': [[None, 'conflict']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The sushi was awful!"], "output": "{'aspect_term': [['sushi', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Consequently, their burgers fell apart in their hands and made such a mess that they did'nt feel like finishing them."], "output": "{'aspect_term': [['burgers', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["A cool place to hang with your friends for a couple of healthy drinks and desserts."], "output": "{'aspect_term': [['place', 'positive'], ['drinks', 'positive'], ['desserts', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Their coffee is quite good too!"], "output": "{'aspect_term': [['coffee', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["For the price, you cannot eat this well in Manhattan."], "output": "{'aspect_term': [['price', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I like Mamoun's food as well, but side by side, Kati Rolls just produce tastier food hands down."], "output": "{'aspect_term': [['food', 'positive'], ['food', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The food however, is what one might expect."], "output": "{'aspect_term': [['food', 'neutral']], 'aspect_category': [[None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The owner is very friendly and a great guy, go try his pizza, you'll like it!"], "output": "{'aspect_term': [['owner', 'positive'], ['pizza', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["They showed up 15 minutes after the tuna melt."], "output": "{'aspect_term': [['tuna', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["This place has realy fresh sushi and a nice large menu of Japanese classic cuisine."], "output": "{'aspect_term': [['sushi', 'positive'], ['menu', 'positive'], ['Japanese classic cuisine', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Not only was the food outstanding, but the little 'perks' were great."], "output": "{'aspect_term': [['food', 'positive'], ['perks', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Our friendly server made great food suggestions and also sent both the sommelier and the fromager to the table to help suggest different pairings for wine and cheese."], "output": "{'aspect_term': [['food suggestions', 'positive'], ['server', 'positive'], ['sommelier', 'positive'], ['fromager', 'positive'], ['wine', 'neutral'], ['cheese', 'neutral']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive'], [None, 'positive'], [None, 'neutral'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["So, the menu is written in chalk above your head and it all sounds delicious."], "output": "{'aspect_term': [['menu', 'neutral']], 'aspect_category': [[None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["But for whatever reason, prices are about twice as high."], "output": "{'aspect_term': [['prices', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["First of all, this place is *not* romantic, as claimed by Citysearch's editorial review."], "output": "{'aspect_term': [['place', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The decor is very simple but comfortable."], "output": "{'aspect_term': [['decor', 'conflict']], 'aspect_category': [[None, 'conflict']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["If you can handle that, it's a great place for a business dinner, fun with friends or simply a table for 2."], "output": "{'aspect_term': [['business dinner', 'positive'], ['table', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["When family came in he gave them apps to test their palets, and then ordered for them."], "output": "{'aspect_term': [['apps', 'neutral']], 'aspect_category': [[None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["In reality (to maximize potential diners) they were still taking phone reservations and reallocating tables of those waiting in the lobby."], "output": "{'aspect_term': [['diners', 'neutral'], ['reservations', 'negative'], ['tables', 'negative'], ['lobby', 'neutral'], ['waiting', 'negative']], 'aspect_category': [[None, 'neutral'], [None, 'negative'], [None, 'negative'], [None, 'neutral'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Baluchi's has solid food and a nice decor at reasonable prices."], "output": "{'aspect_term': [['food', 'positive'], ['decor', 'positive'], ['prices', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["While the ambiance and atmosphere were great, the food and service could have been a lot better."], "output": "{'aspect_term': [['ambiance', 'positive'], ['atmosphere', 'positive'], ['food', 'negative'], ['service', 'negative']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'negative'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I was back-to-back with the diner at the table behind me and wait staff had to hoist trays over our heads as they squeezed past us again and again."], "output": "{'aspect_term': [['diner', 'neutral'], ['wait staff', 'negative'], ['table', 'negative']], 'aspect_category': [[None, 'neutral'], [None, 'negative'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The servers give you some sample slices of your order while you wait (shortly I might add)."], "output": "{'aspect_term': [['servers', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Try the hot dogs too, they're snappy and delicious."], "output": "{'aspect_term': [['hot dogs', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Great roofdeck, nice group of 30 somethings, but no music, kind of quiet."], "output": "{'aspect_term': [['roofdeck', 'positive'], ['music', 'negative']], 'aspect_category': [[None, 'positive'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Coming from Boston this place is like Emma's Pizza in Kendall Square in Cambridge (although they have more funky toppings!)"], "output": "{'aspect_term': [['toppings', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The service is descent even when this small place is packed."], "output": "{'aspect_term': [['service', 'positive'], ['place', 'negative']], 'aspect_category': [[None, 'positive'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The pizza is yummy and I like the atmoshpere."], "output": "{'aspect_term': [['pizza', 'positive'], ['atmoshpere', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Good, because hey, it's more food, but bad because dim sum is supposed to be smaller portions so you can try out more dishes and smaller so that each dish is cheap."], "output": "{'aspect_term': [['dim sum', 'negative'], ['food', 'positive'], ['portions', 'negative'], ['dishes', 'neutral'], ['dish', 'neutral']], 'aspect_category': [[None, 'negative'], [None, 'positive'], [None, 'negative'], [None, 'neutral'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["VT is what baby pizzas hope to be when they grow up."], "output": "{'aspect_term': [['baby pizzas', 'neutral']], 'aspect_category': [[None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Best dish is nori-wrapped tuna."], "output": "{'aspect_term': [['nori-wrapped tuna', 'positive'], ['dish', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The food was just awful, ATROCIOUS actually."], "output": "{'aspect_term': [['food', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["While the room is not particularly comfortable, once you're seated you'll forget about everything except what's on your plate."], "output": "{'aspect_term': [['room', 'negative'], ['plate', 'positive']], 'aspect_category': [[None, 'negative'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Really cool stauff inside."], "output": "{'aspect_term': [['stauff', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The dinner was ok, nothing I would have again."], "output": "{'aspect_term': [['dinner', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["they didn't disappoint, service from the second i arrived at the door was extremely pleasant and attentive with almost one server per table."], "output": "{'aspect_term': [['service', 'positive'], ['server', 'positive'], ['table', 'neutral']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Really though, where's the seasoning?"], "output": "{'aspect_term': [['seasoning', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The food was amazing, and the service was prompt and helpful, but not over-bearing or rushed."], "output": "{'aspect_term': [['food', 'positive'], ['service', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The spicy tuna roll was unusually good and the rock shrimp tempura was awesome, great appetizer to share!"], "output": "{'aspect_term': [['spicy tuna roll', 'positive'], ['rock shrimp tempura', 'positive'], ['appetizer', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Be sure to try the seasonal, and always delicious, specials."], "output": "{'aspect_term': [['specials', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Great vibe, lots of people."], "output": "{'aspect_term': [['vibe', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["In addition, the food is very good and the prices are reasonable."], "output": "{'aspect_term': [['food', 'positive'], ['prices', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["With the great variety on the menu , I eat here often and never get bored ."], "output": "{'aspect_term': [['menu', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Our favorite meal is a pesto pizza, the house salad, and a good bottle of wine."], "output": "{'aspect_term': [['pesto pizza', 'positive'], ['house salad', 'positive'], ['bottle of wine', 'positive'], ['meal', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Given the incredible architecture surrounding it, this place has no character."], "output": "{'aspect_term': [['architecture', 'positive'], ['place', 'negative']], 'aspect_category': [[None, 'positive'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Could be pricey without a prix fixe meal."], "output": "{'aspect_term': [['prix fixe meal', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The makhani was OK --the korma was bland."], "output": "{'aspect_term': [['makhani', 'neutral'], ['korma', 'negative']], 'aspect_category': [[None, 'neutral'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["My friend got the mushroom pizza which tasted better."], "output": "{'aspect_term': [['mushroom pizza', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["However, they've got the most amazing pastrami and the soups hit the spot."], "output": "{'aspect_term': [['pastrami', 'positive'], ['soups', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Good spreads, great beverage selections and bagels really tasty."], "output": "{'aspect_term': [['spreads', 'positive'], ['beverage selections', 'positive'], ['bagels', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["They are served with a free appetizer and the portions are perfect for lunch."], "output": "{'aspect_term': [['appetizer', 'positive'], ['portions', 'positive'], ['served', 'neutral'], ['lunch', 'neutral']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'neutral'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The signs, the specials menus, food, and even all the waitstaff are ALL TOTALLY Japanese."], "output": "{'aspect_term': [['signs', 'positive'], ['specials menus', 'positive'], ['food', 'positive'], ['waitstaff', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["In an area sadly lacking in decent Thai food, this is one of the best spots."], "output": "{'aspect_term': [['Thai food', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Another plus is most of the entrees are approx."], "output": "{'aspect_term': [['entrees', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The whole set up is truly unprofessional and I wish Cafe Noir would get some good staff, because despite the current one this is a great place."], "output": "{'aspect_term': [['staff', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Even better, they know how to cook French classics like Steak au Poivre and Onglet without burning it to death or overcooking it."], "output": "{'aspect_term': [['Steak au Poivre', 'positive'], ['Onglet', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The Italian food has flavor (that can be sort of surprising on the UES), and the service turns from a nightmare to attentive,they sort of remind me of the NY Yankees of the late 90's, no matter how bad it look, you knew that there was a rally just around the corner..."], "output": "{'aspect_term': [['Italian food', 'positive'], ['service', 'conflict']], 'aspect_category': [[None, 'positive'], [None, 'conflict']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The place wasn't too hard to find, but it was kind of packed, as soon as my boyfriend and I got our food, the line reached the door."], "output": "{'aspect_term': [['place', 'conflict'], ['food', 'neutral']], 'aspect_category': [[None, 'conflict'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I particularly love their yellowfun tuna and their mussel selection."], "output": "{'aspect_term': [['yellowfun tuna', 'positive'], ['mussel selection', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I have never had cheescake like this."], "output": "{'aspect_term': [['cheescake', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I had the duck breast special on my last visit and it was incredible."], "output": "{'aspect_term': [['duck breast special', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The only weird thing was if we got a bottle, the waitress would have simply multiplied the glass price X4, which makes no sense whatsoever."], "output": "{'aspect_term': [['bottle', 'neutral'], ['waitress', 'negative'], ['price', 'negative']], 'aspect_category': [[None, 'neutral'], [None, 'negative'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["My wife and I also enjoyed the spinach, the Shanghai low mein, and other attractions."], "output": "{'aspect_term': [['spinach', 'positive'], ['Shanghai low mein', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I love when restaurants think using fancy expensive ingrediants makes the food fine cuisine, even with no idea how to use them."], "output": "{'aspect_term': [['ingrediants', 'positive'], ['cuisine', 'positive'], ['food', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["It was nice and fresh, but I can't give it high scores on being authentic thai."], "output": "{'aspect_term': [['thai', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["good music, great food, speedy service affordable prices."], "output": "{'aspect_term': [['music', 'positive'], ['food', 'positive'], ['service', 'positive'], ['prices', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Service is not what one would expect from a joint in this price category."], "output": "{'aspect_term': [['Service', 'negative'], ['price category', 'negative']], 'aspect_category': [[None, 'negative'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The lox is always fresh too."], "output": "{'aspect_term': [['lox', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["It was like the servers forgot that they actually worked there and instead wanted to hang out and be cool."], "output": "{'aspect_term': [['servers', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Thius is a must for anyone who loves Shabu-Shabu."], "output": "{'aspect_term': [['Shabu-Shabu', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["From the complimentary chef app of a delicate butternut squash ravioli in a delicious truffle sauce to an amazing buttery and tender langostine entree to a dessert that I can't remember because of the fabulous Cakebread Cabernet we were drinking -- the whole evening was amazing."], "output": "{'aspect_term': [['chef app', 'positive'], ['delicate butternut squash ravioli in a delicious truffle sauce', 'positive'], ['buttery and tender langostine entree', 'positive'], ['dessert', 'neutral'], ['Cakebread Cabernet', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive'], [None, 'neutral'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["They wouldnt even let me finish my glass of wine before offering another."], "output": "{'aspect_term': [['glass of wine', 'neutral']], 'aspect_category': [[None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Its location is good and the fact that Hutner College is near and their prices are very reasonable, makes students go back to Suan again and again."], "output": "{'aspect_term': [['location', 'positive'], ['prices', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The lobster sandwich is good and the spaghetti with Scallops and Shrimp is great."], "output": "{'aspect_term': [['lobster sandwich', 'positive'], ['spaghetti with Scallops and Shrimp', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Prices are higher to dine in and their chicken tikka marsala is quite good."], "output": "{'aspect_term': [['Prices', 'negative'], ['chicken tikka marsala', 'positive']], 'aspect_category': [[None, 'negative'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Mizu is home to creative and unique rolls not to found anywhere else."], "output": "{'aspect_term': [['rolls', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The best burger I have had in the Village."], "output": "{'aspect_term': [['burger', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Little Tonino's is just awesome, our favorite delivery place in Kennsington, honestly the best Gnochi I have ever had!"], "output": "{'aspect_term': [['Gnochi', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Turned out there was full service upstairs and sat down."], "output": "{'aspect_term': [['service', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["This is the only Thai place I go too in NYC, it's wonderful, and live relaxed Jazz on certain nights."], "output": "{'aspect_term': [['Jazz', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I think I've had some the best meals of my life at minnow."], "output": "{'aspect_term': [['meals', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The menu changed, portions were even smaller than before, a lentil dish was salty beyond edibility, a basmati rice dish lacked flavor."], "output": "{'aspect_term': [['menu', 'negative'], ['portions', 'negative'], ['lentil dish', 'negative'], ['basmati rice dish', 'negative'], ['flavor', 'negative']], 'aspect_category': [[None, 'negative'], [None, 'negative'], [None, 'negative'], [None, 'negative'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["We were on our way back to NJ, and since I am in NY, we figured why not grab some food?"], "output": "{'aspect_term': [['food', 'neutral']], 'aspect_category': [[None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["When asked about how a certain dish was prepared in comparison to a similar at other thai restaurants, he replied this is not Mcdonald's, every place makes things differently While it is understandable that every place is indeed different, there was not a need to be uncourteous to customers and downright rude."], "output": "{'aspect_term': [['dish', 'neutral']], 'aspect_category': [[None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Bartender was unable to tear himself away from friends at bar."], "output": "{'aspect_term': [['Bartender', 'negative'], ['bar', 'neutral']], 'aspect_category': [[None, 'negative'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Prices too high for this cramped and unappealing resturant."], "output": "{'aspect_term': [['Prices', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["It might have been a little too spicy for my friend, which you can couteract with eat more rice and keeping water on hand."], "output": "{'aspect_term': [['rice', 'neutral'], ['water', 'neutral']], 'aspect_category': [[None, 'neutral'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Besides, when you have bad service, that's less money you have to tip."], "output": "{'aspect_term': [['service', 'negative'], ['money', 'negative'], ['tip', 'negative']], 'aspect_category': [[None, 'negative'], [None, 'negative'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["If you're looking for a great meal at a decent price, go to Del Frisco's!"], "output": "{'aspect_term': [['meal', 'positive'], ['price', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["One of us actually liked the expresso - that's it."], "output": "{'aspect_term': [['expresso', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The most annoying thing, though, is the fact that the servers seem to be trained to drive revenue."], "output": "{'aspect_term': [['servers', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["It's constantly open, catering to the Pakistani cabbies lined up on Crosby St., so there's more turnover with the food than you'd expect (i.e., surprisingly fresh)."], "output": "{'aspect_term': [['food', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I will recommend Scopa to all of my friends for a place to go for wonderful Italian food."], "output": "{'aspect_term': [['Italian food', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Oh, but wait, we were out of drinks (which were also delightfully overpriced)."], "output": "{'aspect_term': [['drinks', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["at taj, vegetarians can rejoice-all the dishes are manna from heaven."], "output": "{'aspect_term': [['dishes', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Its worth the wait though."], "output": "{'aspect_term': [['wait', 'conflict']], 'aspect_category': [[None, 'conflict']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["bottles of wine are cheap and good."], "output": "{'aspect_term': [['bottles of wine', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["We had the scallops as an appetizer and they were delicious and the sauce was wonderful."], "output": "{'aspect_term': [['scallops', 'positive'], ['appetizer', 'positive'], ['sauce', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Three of us arrived for dinner about 5:30 on a week night without reservations."], "output": "{'aspect_term': [['dinner', 'neutral'], ['reservations', 'neutral']], 'aspect_category': [[None, 'neutral'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["We always have a delicious meal and always leave feeling satisfied."], "output": "{'aspect_term': [['meal', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I have been about 4 times and have always had a great meal."], "output": "{'aspect_term': [['meal', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Well, their deliveries take for ever and the food is usually cold."], "output": "{'aspect_term': [['deliveries', 'negative'], ['food', 'negative']], 'aspect_category': [[None, 'negative'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The waitress suggested glasses of wine that went very well with the food."], "output": "{'aspect_term': [['waitress', 'positive'], ['food', 'neutral'], ['glasses of wine', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'neutral'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["This is an amazing place to try some roti rolls."], "output": "{'aspect_term': [['roti rolls', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Friendly staff that actually lets you enjoy your meal and the company you're with."], "output": "{'aspect_term': [['staff', 'positive'], ['meal', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["And even with it's Pub atmosphere they were great to my kids too!"], "output": "{'aspect_term': [['Pub atmosphere', 'conflict']], 'aspect_category': [[None, 'conflict']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["We went to eat at the Jekyll and Hyde restaurant on Friday night and really enjoyed the fun atmosphere and good food."], "output": "{'aspect_term': [['atmosphere', 'positive'], ['food', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Delicious food, excellent service, and a pretty atmosphere make this a great choice for dinner and the $5.99 lunch buffet makes it an even better choice for lunch!"], "output": "{'aspect_term': [['food', 'positive'], ['service', 'positive'], ['atmosphere', 'positive'], ['lunch buffet', 'positive'], ['dinner', 'positive'], ['lunch', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive'], [None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The wine list is also really nice."], "output": "{'aspect_term': [['wine list', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["No you're going to go back because the food was good."], "output": "{'aspect_term': [['food', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The place is so cool and the service is prompt and curtious."], "output": "{'aspect_term': [['service', 'positive'], ['place', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["We've never had any problems with the staff but maybe we've been lucky?"], "output": "{'aspect_term': [['staff', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["All the money went into the interior decoration, none of it went to the chefs."], "output": "{'aspect_term': [['interior decoration', 'positive'], ['chefs', 'negative']], 'aspect_category': [[None, 'positive'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Sure, the setting is nice."], "output": "{'aspect_term': [['setting', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["For the location, the prices are very reasonable."], "output": "{'aspect_term': [['prices', 'positive'], ['location', 'neutral']], 'aspect_category': [[None, 'positive'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Yes, the prices are high, but I felt it was worth it."], "output": "{'aspect_term': [['prices', 'conflict']], 'aspect_category': [[None, 'conflict']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Tuk Tuk is one of those comfortable neighborhood joints where you know you will always have a good meal at a fair price."], "output": "{'aspect_term': [['meal', 'positive'], ['price', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Stick to dimsum, not super overpriced noodles."], "output": "{'aspect_term': [['noodles', 'neutral'], ['dimsum', 'positive']], 'aspect_category': [[None, 'neutral'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Decor is minimalist and clean - nothing to distract or commend."], "output": "{'aspect_term': [['Decor', 'neutral']], 'aspect_category': [[None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The entire dining experience was wonderful!"], "output": "{'aspect_term': [['dining experience', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["You can certainly find restaurants that offer a superior fine dining experience, but for superb food at reasonable prices, La Villa can't be beat."], "output": "{'aspect_term': [['food', 'positive'], ['prices', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The food was exceptional."], "output": "{'aspect_term': [['food', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["And I say snacking because it really is not set up to be a proper dinner."], "output": "{'aspect_term': [['dinner', 'negative'], ['snacking', 'neutral']], 'aspect_category': [[None, 'negative'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The rest of the menu is limited by everything is good eats."], "output": "{'aspect_term': [['menu', 'conflict'], ['eats', 'positive']], 'aspect_category': [[None, 'conflict'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["My GF and I still choose to eat there a lot because of diverse cocktails, the chill decor, and the decent sushi."], "output": "{'aspect_term': [['cocktails', 'positive'], ['decor', 'positive'], ['sushi', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The place is small and cramped but the food is fantastic."], "output": "{'aspect_term': [['place', 'negative'], ['food', 'positive']], 'aspect_category': [[None, 'negative'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["This restaurant used to be our regular Thursday night dinner location."], "output": "{'aspect_term': [['dinner location', 'neutral']], 'aspect_category': [[None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I come from a family of pizzeria owners, and I'm almost ashamed to say that the pizza in Fornino's blows my families receipies away."], "output": "{'aspect_term': [['pizza', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The photos of the restaurant in its web site are way better than the real look."], "output": "{'aspect_term': [['look', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["good selection of wines ranging from affordable to high end."], "output": "{'aspect_term': [['selection of wines', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["We were very surprised by how good the food was on our first visit here on a Sunday night."], "output": "{'aspect_term': [['food', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The place itself is beautiful the bar scene seems to be happening."], "output": "{'aspect_term': [['place', 'positive'], ['bar scene', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Largest and freshest pieces of sushi, and delicious!"], "output": "{'aspect_term': [['pieces of sushi', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["My fiance took me to Scopa last week for my birthday and I couldn't believe the food."], "output": "{'aspect_term': [['food', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["When my dessert came, there was a candle in it - not because anyone asked for one - but because the waiter must have seen me opening my birthday card and gift, and said he knew it was a special occassion of some sort."], "output": "{'aspect_term': [['dessert', 'neutral'], ['waiter', 'positive']], 'aspect_category': [[None, 'neutral'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The staff ignored my friends and I the entire time we were there."], "output": "{'aspect_term': [['staff', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I don't like Indian food too much and this was delicious, however you want to factor that into the equation."], "output": "{'aspect_term': [['Indian food', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The food was great and the service was even better."], "output": "{'aspect_term': [['food', 'positive'], ['service', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I went here with a friend on a whim, we went someplace else first and couldn't get a table."], "output": "{'aspect_term': [['table', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["There's something smooth about sipping sake upper east side style."], "output": "{'aspect_term': [['sake', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Delicious food at a great price but do not go here on a cold day and sit by the front door."], "output": "{'aspect_term': [['food', 'positive'], ['price', 'positive'], ['front door', 'neutral']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I went at 6:00 PM specifically for the pre-theater menu ($19.95 for roasted tomato soup with chevre, steak frites, creme brulee) and it was marvelous."], "output": "{'aspect_term': [['pre-theater menu', 'positive'], ['roasted tomato soup with chevre', 'positive'], ['steak frites', 'positive'], ['creme brulee', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["this little place has a cute interior decor and affordable city prices."], "output": "{'aspect_term': [['interior decor', 'positive'], ['prices', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["My biggest complaint was the un-tasty food although presented well."], "output": "{'aspect_term': [['food', 'conflict']], 'aspect_category': [[None, 'conflict']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I am reluctant to write because I would not want my jem of a pizza place to become overcrowded."], "output": "{'aspect_term': [['pizza', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["There is usually a wait but it is well worth it."], "output": "{'aspect_term': [['wait', 'conflict']], 'aspect_category': [[None, 'conflict']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The seating was if they were trying to get the maximum amount of people into the restaurant, so be nice to your neighbor when you dine here."], "output": "{'aspect_term': [['seating', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The food was very good, a great deal, and the place its self was great."], "output": "{'aspect_term': [['food', 'positive'], ['place', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["They couldn't even make a salad that was appealing."], "output": "{'aspect_term': [['salad', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["There is also very limited seating and there can be a substantial wait in getting food at peak times."], "output": "{'aspect_term': [['seating', 'negative'], ['food', 'neutral'], ['wait', 'negative']], 'aspect_category': [[None, 'negative'], [None, 'neutral'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Over the years the host, Vittorio, and his crew, have always treated me as family--although with all the business this not-so-little gem does, it amazing he's even able to remember a consistent but not-so-frequent visitor."], "output": "{'aspect_term': [['crew', 'positive'], ['host', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The duck confit is always amazing and the foie gras terrine with figs was out of this world."], "output": "{'aspect_term': [['foie gras terrine with figs', 'positive'], ['duck confit', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Everything looks great, the drinks, the decor, the food, even the people."], "output": "{'aspect_term': [['drinks', 'positive'], ['decor', 'positive'], ['food', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Just stick with the small dishes!"], "output": "{'aspect_term': [['dishes', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["(Always ask the bartender for the SEASONAL beer!!!"], "output": "{'aspect_term': [['SEASONAL beer', 'positive'], ['bartender', 'neutral']], 'aspect_category': [[None, 'positive'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Good food."], "output": "{'aspect_term': [['food', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The Singapore Mai Fun had NO curry flavor whatsoever."], "output": "{'aspect_term': [['Singapore Mai Fun', 'negative'], ['curry flavor', 'negative']], 'aspect_category': [[None, 'negative'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The waitstaff are all very busy, it's not outstanding service, but I've never been dealt with rudely."], "output": "{'aspect_term': [['waitstaff', 'negative'], ['service', 'conflict']], 'aspect_category': [[None, 'negative'], [None, 'conflict']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The pizza was delivered cold and the cheese wasn't even fully melted!"], "output": "{'aspect_term': [['pizza', 'negative'], ['cheese', 'negative']], 'aspect_category': [[None, 'negative'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The wait staff is very friendly, if not overly efficient."], "output": "{'aspect_term': [['wait staff', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Your money could easily be better spent elsewhere (Anywhere)."], "output": "{'aspect_term': [['money', 'neutral']], 'aspect_category': [[None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["While this is a pretty place in that overly cute French way, the food was insultingly horrible."], "output": "{'aspect_term': [['place', 'positive'], ['food', 'negative']], 'aspect_category': [[None, 'positive'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The food has been consistant for years and it never lets you down."], "output": "{'aspect_term': [['food', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Check it out, it won't hurt your stomach or your wallet."], "output": "{'aspect_term': [['stomach', 'positive'], ['wallet', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The food is so cheap and the waiters are nice."], "output": "{'aspect_term': [['food', 'positive'], ['waiters', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["We asked to be moved (which took half an hour), and then were seated in a high traffic area in the back, even though the rest of the room was practically empty."], "output": "{'aspect_term': [['room', 'neutral'], ['area', 'negative']], 'aspect_category': [[None, 'neutral'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The ingredients taste fresher, the crust is thinner and crispier, the slice is less oily, and it's never burnt like it occasionally is at Joe's."], "output": "{'aspect_term': [['ingredients', 'positive'], ['crust', 'positive'], ['slice', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Same owner as the guy who owns Typhoon, which is just down the street on St. Marks and 1st Ave."], "output": "{'aspect_term': [['owner', 'neutral']], 'aspect_category': [[None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Everything is always cooked to perfection, the service is excellent, the decor cool and understated."], "output": "{'aspect_term': [['service', 'positive'], ['decor', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["All the desserts the group tried got favorable reviews."], "output": "{'aspect_term': [['desserts', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Really tasty spring rolls and noodles for a good price though."], "output": "{'aspect_term': [['spring rolls', 'positive'], ['noodles', 'positive'], ['price', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The pizza was great."], "output": "{'aspect_term': [['pizza', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The overall price tag was very very expensive, something I did expect."], "output": "{'aspect_term': [['price tag', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["May, the owner always has a smile on her and will warmly greet you."], "output": "{'aspect_term': [['owner', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The fish is fresh and each piece is sliced to perfection and seasoned by the sushi chef (usually with a little fresh wasabi and soy sauce but also sometimes with some sea salt)."], "output": "{'aspect_term': [['fish', 'positive'], ['sushi chef', 'positive'], ['wasabi', 'positive'], ['soy sauce', 'positive'], ['sea salt', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Warm, comfortable surroundings, nice appointments (witness the etched glass and brickwork separating the dining rooms)."], "output": "{'aspect_term': [['surroundings', 'positive'], ['dining rooms', 'neutral']], 'aspect_category': [[None, 'positive'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["If I wanted to deal with a crappy scene and annoying customers I'd go out in Manhattan."], "output": "{'aspect_term': [['scene', 'negative'], ['customers', 'negative']], 'aspect_category': [[None, 'negative'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Great sushi experience."], "output": "{'aspect_term': [['sushi', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The best pad thai i've ever had."], "output": "{'aspect_term': [['pad thai', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The miso soup lacked flavor and the fish was unfortunately not as well prepared as in the past."], "output": "{'aspect_term': [['miso soup', 'negative'], ['fish', 'negative'], ['flavor', 'negative']], 'aspect_category': [[None, 'negative'], [None, 'negative'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The staff was very attentive, the ambience lovely, and the food superb."], "output": "{'aspect_term': [['staff', 'positive'], ['ambience', 'positive'], ['food', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Since my first dinner I have had the chance to have brunch at Orsay 3x."], "output": "{'aspect_term': [['dinner', 'neutral'], ['brunch', 'neutral']], 'aspect_category': [[None, 'neutral'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Since it literally is a complete hole in the wall, it's a bit intimidating at first, but you get over that very quickly as soon as the friendly staff welcomes you - don't hesitate to ask for help with what to get."], "output": "{'aspect_term': [['staff', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Unlike other places in NYC where the sandwiches you want only come as a triple-decker, here you can get what you want in a reasonably-sized portion (and price)."], "output": "{'aspect_term': [['sandwiches', 'negative'], ['price', 'positive'], ['portion', 'positive']], 'aspect_category': [[None, 'negative'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Truly the mark of an attentive waiter."], "output": "{'aspect_term': [['waiter', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The flavors robust and subtle."], "output": "{'aspect_term': [['flavors', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Everything, from the soft bread, soggy salad, and 50 minute wait time, with an incredibly rude service to deliver below average food."], "output": "{'aspect_term': [['bread', 'negative'], ['salad', 'negative'], ['service', 'negative'], ['food', 'negative'], ['wait', 'negative']], 'aspect_category': [[None, 'negative'], [None, 'negative'], [None, 'negative'], [None, 'negative'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["We also ordered two hot dogs thinking they would be pretty good since there is a whole section on the menu devoted to them."], "output": "{'aspect_term': [['hot dogs', 'neutral'], ['menu', 'neutral']], 'aspect_category': [[None, 'neutral'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["great food, lt's of it, more then one person can eat!"], "output": "{'aspect_term': [['food', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Lahore is a great place to duck into late-night when you need some really tasty food on the cheap -- you'll likely have trouble finishing the amount of food you get for FOUR DOLLARS."], "output": "{'aspect_term': [['food', 'positive'], ['food', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["From the incredible food, to the warm atmosphere, to the friendly service, this downtown neighborhood spot doesn't miss a beat."], "output": "{'aspect_term': [['food', 'positive'], ['atmosphere', 'positive'], ['service', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["I stumbled upon this second floor walk-up two Fridays ago when I was with two friends in town from L.A. Being serious sushi lovers, we sat at the sushi bar to be closer to the action."], "output": "{'aspect_term': [['sushi', 'neutral'], ['sushi bar', 'neutral']], 'aspect_category': [[None, 'neutral'], [None, 'neutral']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The hostess and the waitress were incredibly rude and did everything they could to rush us out."], "output": "{'aspect_term': [['hostess', 'negative'], ['waitress', 'negative']], 'aspect_category': [[None, 'negative'], [None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The atmosphere is great if your looking for a laid back scene and an inexpensive way to spend a weekend afternoon."], "output": "{'aspect_term': [['atmosphere', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Admittedly some nights inside the restaurant were rather warm, but the open kitchen is part of the charm."], "output": "{'aspect_term': [['open kitchen', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The food is great."], "output": "{'aspect_term': [['food', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The restaurant is dark and not very attractive and then you have spot lights shining on you putting you in the worst light possible, reaching for sunglasses."], "output": "{'aspect_term': [['spot lights', 'negative']], 'aspect_category': [[None, 'negative']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["The service was attentive."], "output": "{'aspect_term': [['service', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}
{"task_type": "generation", "dataset": "semeval-2014", "input": ["Toons has recently been redone, so it's now a very attractive space."], "output": "{'aspect_term': [['space', 'positive']], 'aspect_category': [[None, 'positive']]}", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms , their aspect categories and their corresponding sentiment polarities in a dict. Input: A sentence. Output: a dict with keys: aspect_term and aspect_category , separate extraction a list of 2-tuples(aspect term , its corresponding sentiment polarity) and a list of 2-tuples(aspect category, its corresponding sentiment polarity). Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"The Pad Thai is excellent here, as well.\"  Output: {'aspect_term': [['Pad Thai', 'positive']], 'aspect_category': [[None, 'positive']]} "}