{"task_type": "generation", "dataset": "semeval-2014", "input": ["It is far more popular as a bar than as a restaurant, with only a few tables and the waiter being the bartender, but we greatly enjoyed the unobtrusive atmosphere."], "output": "{'aspect_term': [['bar', 'positive'], ['tables', 'negative'], ['waiter', 'neutral'], ['bartender', 'neutral'], ['atmosphere', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'negative'], [None, 'neutral'], [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 food was very well prepared."], "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 food is great and authentic."], "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": ["They are tasty, but I suggest only eating one with meat because they tend not to mesh that well with the average American digestive system."], "output": "{'aspect_term': [['meat', '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 went there for lunch and it was not as good as I expected from the reviews I read."], "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": ["One of the earlier people commenting on the restaurant did not get the that some experimenting is going on with the menu in a positive way."], "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": ["Good food at the restaurant (a bit expensive, but great if you want to impress your date)."], "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 ambience was so fun, and the prices were great, on top of the fact that the food was really tasty."], "output": "{'aspect_term': [['ambience', 'positive'], ['prices', '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": ["Service was decent, but not as smooth as I would expect from a place with these prices and reputation."], "output": "{'aspect_term': [['Service', 'conflict'], ['prices', 'negative'], ['reputation', 'positive']], 'aspect_category': [[None, 'conflict'], [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 food looked very appetizing and delicious since it came on a variety of fancy plates."], "output": "{'aspect_term': [['food', 'positive'], ['plates', '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 waiter was attentive."], "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 hot and sour soup was unbearably hot and tasted of only pepper and nothing else."], "output": "{'aspect_term': [['soup', 'negative'], ['pepper', '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": ["Decent wine at reasonable prices."], "output": "{'aspect_term': [['wine', '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": ["I'd call it an 'italian 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 pizza was really 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": ["We've been following chef Lyle's food around New York for 15 years and while remaining classic, his innovations with bistro fare have made us return and return."], "output": "{'aspect_term': [['bistro fare', 'positive'], ['chef', '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": ["Slightly above average wines start at $70+ with only one selection listed at $30+."], "output": "{'aspect_term': [['wines', '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 good authentic Thai this place is not the place to go."], "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": ["The food was just OK, I would never go back."], "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 only positive was the wait staff, which was prompt, knowledgable, and likeable."], "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": ["Interesting selection, good wines, service fine, fun decor."], "output": "{'aspect_term': [['wines', 'positive'], ['service', 'positive'], ['decor', '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 can't believe people complain about no cheese sticks?"], "output": "{'aspect_term': [['cheese sticks', '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": ["very good breads as well."], "output": "{'aspect_term': [['breads', '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 is delicious - they use fresh mozzarella instead of the cheap, frozen, shredded cheese common to most pizzaria's."], "output": "{'aspect_term': [['pizza', 'positive'], ['fresh mozzarella', 'positive'], ['cheese', 'negative']], 'aspect_category': [[None, 'positive'], [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 sushi seemed pretty fresh and was adequately proportioned."], "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": ["Get your food to go, find a bench, and kick back with a plate of dumplings."], "output": "{'aspect_term': [['food', 'neutral'], ['plate of dumplings', '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": ["I have known about this secret for the last 13 years, Emilio(the Godfather) has continued to serve food and wine for the gods at mortal prices."], "output": "{'aspect_term': [['food', 'positive'], ['wine', '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": ["The Thai ice tea was amazingly smooth and yummy!"], "output": "{'aspect_term': [['Thai ice tea', '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": ["As we were sitting eating the subpar food the manager proceeded to berate a couple of his employees for putting out the wrong containers for condiments and explained to them how expensive these containers were."], "output": "{'aspect_term': [['food', 'negative'], ['employees', 'negative'], ['containers for condiments', 'negative'], ['containers', 'neutral'], ['manager', 'negative']], 'aspect_category': [[None, 'negative'], [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": ["From the appetizers we ate, the dim sum and other variety of foods, it was impossible to criticize the food."], "output": "{'aspect_term': [['appetizers', 'positive'], ['dim sum', 'positive'], ['foods', 'positive'], ['food', '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": ["My wife and I will usually only order one primi and one secondi and split them, as they tend to offer large portions."], "output": "{'aspect_term': [['primi', 'positive'], ['secondi', 'positive'], ['portions', '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": ["We love the food, drinks, and atmosphere!"], "output": "{'aspect_term': [['food', 'positive'], ['drinks', 'positive'], ['atmosphere', '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": ["But they've done a really nice job of offering all the typical pizzeria faves plus some terrific specials like the Godmother pizza (a sort of traditional flat pizza with an olive oil-brushed crust and less tomato sauce than usual)."], "output": "{'aspect_term': [['Godmother pizza (a sort of traditional flat pizza with an olive oil-brushed crust and less tomato sauce than usual)', 'positive'], ['specials', '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 do suggest to ask to be seated upstairs if you are looking to be a little cozy."], "output": "{'aspect_term': [['upstairs', '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 spot, whether looking for a couple of drinks or quiet dinner."], "output": "{'aspect_term': [['drinks', 'positive'], ['dinner', '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": ["They don't walk around with the trays of Dim Sum."], "output": "{'aspect_term': [['trays of Dim Sum', '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": ["What I didn't like was how the food came right after it was ordered."], "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 shrimp scampi was excellent and the antipasti were plentiful."], "output": "{'aspect_term': [['shrimp scampi', 'positive'], ['antipasti', '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": ["You don't go to Mizu for excellent service, you go for the large amounts of food, the amiable atmosphere, and the hole-in-the-wall feeling of the place."], "output": "{'aspect_term': [['service', 'negative'], ['food', 'positive'], ['atmosphere', '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": ["The food is decent at best, and the ambience, well, it's a matter of opinion, some may consider it to be a sweet thing, I thought it was just annoying."], "output": "{'aspect_term': [['food', 'neutral'], ['ambience', 'conflict']], 'aspect_category': [[None, 'neutral'], [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": ["also make sure you pay attention to the music being piped in - quite a weird selection."], "output": "{'aspect_term': [['music', '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": ["We ordered the chicken casserole, but what we got were a few small pieces of chicken, all dark meat and on the bone."], "output": "{'aspect_term': [['chicken casserole', 'negative'], ['chicken', 'negative'], ['meat', '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 service was attentive, yet discreet."], "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": ["Overall, the ingredients and technique are there and I am encouraged enough to return at lunch or dinner to see whether the boldness of the flavour palette improves."], "output": "{'aspect_term': [['ingredients', 'positive'], ['technique', 'positive'], ['lunch', 'neutral'], ['dinner', '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 place was real empty but that was because this was the first Sunday they ever opened."], "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": ["I have had so many dinners here and it's always been perfect - on a date with my husband, with my mom, with girlfriends and larger groups."], "output": "{'aspect_term': [['dinners', '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 delicious (I had a halibut special, my husband had steak), and the service was top-notch."], "output": "{'aspect_term': [['food', 'positive'], ['halibut special', 'positive'], ['steak', 'positive'], ['service', '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": ["less wait time for me!"], "output": "{'aspect_term': [['wait time', '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": ["Joya used to be a cool spot with decent food and a colorful - if not relaxed - atmosphere."], "output": "{'aspect_term': [['food', 'positive'], ['atmosphere', '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": ["You order from a menu, so you leave feeling like you missed the full experience."], "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": ["I must say it's a little pricey for the food because it was not as spectacular as the view."], "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": ["After a seafood craving, i checked citysearch and chose to go to Fish based on a previous review and the citysearch info."], "output": "{'aspect_term': [['seafood', '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": ["Outstanding Bagels, but you get what you pay for."], "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 bar is very well stocked with interesting beers and well priced wines."], "output": "{'aspect_term': [['bar', 'positive'], ['beers', 'positive'], ['wines', 'positive'], ['priced', '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 was prompt and courteous."], "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": ["He has visited Thailand and is quite expert on the cuisine."], "output": "{'aspect_term': [['cuisine', '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 a nice restaurant if you are looking for a good place to host an intimate dinner meeting with business associates."], "output": "{'aspect_term': [['dinner meeting', '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": ["Have frequented 'ino for several years and the food remains 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": ["honestly the worst sushi my husband and i had in our entire lives."], "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": ["Their sake martini is wonderful."], "output": "{'aspect_term': [['sake 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 prices were fantastic."], "output": "{'aspect_term': [['prices', '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 establishment scores big points in presentation and style."], "output": "{'aspect_term': [['establishment', '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 was quiet and delightful."], "output": "{'aspect_term': [['place', '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 owners and employees are friendly and their pizza is fantastic."], "output": "{'aspect_term': [['owners', 'positive'], ['employees', 'positive'], ['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": ["The takeout is great too since they give high quality tupperware as well."], "output": "{'aspect_term': [['takeout', '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": ["Ambience is so cute and quaint, good for business although we were there on vacation."], "output": "{'aspect_term': [['Ambience', '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": ["Price no more than a Jersey deli but way better."], "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": ["The food is outstanding and the service is quick, friendly and very professional."], "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": ["All we received was an apology as we left to see our show without 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": ["Not sure where the previous reviewer, lonk, dined, but Saul is in a great neighborhood and has great food!"], "output": "{'aspect_term': [['neighborhood', '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 was very expensive (we spent $160 for lunch for two) but extremely tasty."], "output": "{'aspect_term': [['food', 'conflict'], ['lunch', '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": ["The scallion pancakes and fried dumplings were nothing out of the ordinary."], "output": "{'aspect_term': [['scallion pancakes', 'neutral'], ['fried dumplings', '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": ["All in all the food was above average and I would return to see how they operate with four or less dinners."], "output": "{'aspect_term': [['food', 'positive'], ['dinners', '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 could rate the people this place would be off the charts - unfortunately - the pizza, sorry - not the best in NYC."], "output": "{'aspect_term': [['people', 'positive'], ['pizza', '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 menu prices are a bit expensive for what you get in quality and portion size."], "output": "{'aspect_term': [['menu prices', 'negative'], ['quality', 'negative'], ['portion size', '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": ["Monday nights are a bargain at the $28 prix fix - this includes a three course meal plus *three* glasses of wine paired with each course."], "output": "{'aspect_term': [['prix fix', 'positive'], ['three course meal', 'positive'], ['glasses of wine', 'positive'], ['course', '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 food is great and reasonably priced."], "output": "{'aspect_term': [['food', 'positive'], ['priced', '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 ambience is pretty and nice for conversation, so a casual lunch here would probably be best."], "output": "{'aspect_term': [['ambience', 'positive'], ['lunch', '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 garlic shrimp, okra (bindi), and anything with lamb."], "output": "{'aspect_term': [['garlic shrimp', 'positive'], ['lamb', 'positive'], ['okra (bindi)', '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": ["Did I mention the wine?"], "output": "{'aspect_term': [['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": ["LOVE the atmosphere - felt like I was in Paris."], "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": ["We began with the cheese fondue (the artisanal blend) and added apples and kielbasa to dip."], "output": "{'aspect_term': [['cheese fondue', 'neutral'], ['kielbasa', 'neutral'], ['apples', '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": ["I LOVE their spicy scallop roll, and my boyfriend consistently gets the sesame chicken."], "output": "{'aspect_term': [['scallop roll', 'positive'], ['sesame chicken', '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": ["those rolls were big, but not good and sashimi wasn't fresh."], "output": "{'aspect_term': [['rolls', 'conflict'], ['sashimi', '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": ["The website and rating makes this place look wonderful but in reality it was very disappointing."], "output": "{'aspect_term': [['place', '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": ["This is my first time writing a review for a restaurant because the food and service was excellent."], "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 pizza was pretty good and huge."], "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": ["But they don't have a toaster, which is strange."], "output": "{'aspect_term': [['toaster', '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": ["Fabulous service, fantastic food, and a chilled out atmosphere and environment."], "output": "{'aspect_term': [['service', 'positive'], ['food', 'positive'], ['atmosphere', 'positive'], ['environment', '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": ["Aside from the rushed service, we were very impressed with the food and the drinks."], "output": "{'aspect_term': [['service', 'negative'], ['food', 'positive'], ['drinks', '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": ["For all of you new to Indian food, try the Paneer Roll, it is a piece of heaven."], "output": "{'aspect_term': [['Indian food', 'positive'], ['Paneer Roll', '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 the menu isn't especially groundbreaking, everything I've tried so far has been well-executed and tasty."], "output": "{'aspect_term': [['menu', '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 relatively new to the area and tried Pick a bgel on 2nd and was disappointed with the service and I thought the food was overated and on the pricey side."], "output": "{'aspect_term': [['service', '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 staff is also attentive and friendly."], "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 rice was poor quality and was cooked so badly it was hard."], "output": "{'aspect_term': [['rice', 'negative'], ['quality', 'negative'], ['cooked', '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 garlic mashed potatoes are hands down the best in the city!"], "output": "{'aspect_term': [['garlic mashed potatoes', '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 was pretty much full after our fondue appetizer."], "output": "{'aspect_term': [['fondue appetizer', '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 pizza is good though."], "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 had to share my table with a loud group of kids and the service was rude an unattentive."], "output": "{'aspect_term': [['service', 'negative'], ['table', '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": ["Yeah, sometimes the service can be slow."], "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": ["The staff isn't the friendliest or most competent, and I am stickler for service, but everything else about this place makes up for it."], "output": "{'aspect_term': [['staff', 'negative'], ['service', '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": ["Yes, they use fancy ingredients, but even fancy ingredients don't make for good pizza unless someone knows how to get the crust right."], "output": "{'aspect_term': [['ingredients', 'positive'], ['ingredients', 'positive'], ['pizza', 'negative'], ['crust', 'neutral']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [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 sides were ok and incredibly salty."], "output": "{'aspect_term': [['sides', '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 is not consistently excellent -- just decent."], "output": "{'aspect_term': [['service', '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": ["A wonderful place!"], "output": "{'aspect_term': [['place', '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- friendly and 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": ["This place, however, has a lot less pretension than Joya and the Thai food is still above-average."], "output": "{'aspect_term': [['place', 'positive'], ['Thai 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 sauces used are also not that exciting."], "output": "{'aspect_term': [['sauces', '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 have never better enjoyed humble root vegetables or a mushroom consomme - and this chef accomplishes without fats."], "output": "{'aspect_term': [['root vegetables', 'positive'], ['mushroom consomme', 'positive'], ['chef', '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 food is yummy, especially their cooked-to-perfection mussels in spicy tomato sauce and their shoestring crispy fries."], "output": "{'aspect_term': [['food', 'positive'], ['mussels in spicy tomato sauce', 'positive'], ['fries', '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 would highly recommend this place to anyone who is looking for a fine Indian dining experience that is definitely a value for your dollar."], "output": "{'aspect_term': [['Indian 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": ["We went around 9:30 on a Friday and it had died down a bit by then so the service was great!"], "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": ["They are often crowded on the weekends but they are efficient and accurate with their service."], "output": "{'aspect_term': [['service', 'positive'], ['crowded', '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": ["Great food, great lay out and awesome service."], "output": "{'aspect_term': [['food', 'positive'], ['lay out', '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": ["Meat dishes now adorn the selections, although there's still a large number of vegetarian-friendly choices."], "output": "{'aspect_term': [['Meat dishes', 'neutral'], ['vegetarian-friendly choices', '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": ["All the food was hot tasty."], "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": ["It's not mind-blowing, but to me, thai food never is and never will be."], "output": "{'aspect_term': [['thai 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": ["My husband said the portions were very small, but if my main course was good to eat the portion would've been fine for me."], "output": "{'aspect_term': [['portions', 'negative'], ['portion', 'positive'], ['main course', 'negative']], 'aspect_category': [[None, 'negative'], [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": ["During the course of the past 3 months, the chef and staff changed and it was not for the better."], "output": "{'aspect_term': [['chef', 'negative'], ['staff', '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": ["Service here was great, food was fantastic."], "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": ["$160 for 2 filets, 2 sides, an appetizer and drinks."], "output": "{'aspect_term': [['filets', 'neutral'], ['sides', 'neutral'], ['appetizer', 'neutral'], ['drinks', '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": ["Deliveries often take up to an hour and the prices are higher than most other pizzerias in the area."], "output": "{'aspect_term': [['Deliveries', 'negative'], ['prices', '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": ["Staff is very accomodating."], "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 buffet had a nice selection."], "output": "{'aspect_term': [['buffet', 'positive'], ['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": ["Made my dining experience uncomfortable."], "output": "{'aspect_term': [['dining experience', '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": ["When we were finally seated our waitress came by twice-1 for our order and 2-for our check."], "output": "{'aspect_term': [['waitress', 'negative'], ['check', '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": ["We took advanatage of the half price sushi deal on saturday so it was well worth it."], "output": "{'aspect_term': [['half price sushi deal', '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 their eggs benedict for brunch, which were the worst in my entire life, I tried removing the hollondaise sauce completely that was how failed it was."], "output": "{'aspect_term': [['eggs benedict', 'negative'], ['hollondaise sauce', 'negative'], ['brunch', 'neutral']], 'aspect_category': [[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": ["Le Pere Pinard has a $15 pre-theater menu that is outstanding."], "output": "{'aspect_term': [['pre-theater 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": ["No dress codes, no attitudes, plenty of comfort companionship, a great place to relax in an always busy Midtown."], "output": "{'aspect_term': [['dress codes', 'positive'], ['attitudes', 'positive'], ['place', '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": ["Great wine list, reasonably priced.--Sara"], "output": "{'aspect_term': [['wine list', 'positive'], ['priced', '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": ["Spice is sleek, modern and cool with a menu that will not hurt your wallet."], "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": ["They need a kick out of it but until then the sushi is pretty good and the place is consistent."], "output": "{'aspect_term': [['sushi', '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": ["Pizza - the only pizza in NYC that should not have additional toppings - the crust tastes like the best, freshly baked bread!"], "output": "{'aspect_term': [['Pizza', 'positive'], ['crust', 'positive'], ['pizza', 'positive'], ['toppings', 'neutral'], ['bread', '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": ["The production is a symphony, alot of fun to experience.The food sublime for the most part."], "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": ["Took my mom for Mother's Day, and the maitre d' was pretty rude."], "output": "{'aspect_term': [[\"maitre d'\", '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 used shredded cheese on top!"], "output": "{'aspect_term': [['shredded cheese', '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": ["Compared to Ess-a, Tal offers a less doughy bagel!"], "output": "{'aspect_term': [['bagel', '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 only is the cuisine the best around, the service has always been attentive and charming."], "output": "{'aspect_term': [['cuisine', '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 was poor, restaurant poorly lit, staff not very attentive and I would have rather eaten at a Mcdonald's than this joint."], "output": "{'aspect_term': [['service', 'negative'], ['staff', '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": ["I tend to judge a sushi restaurant by its sea urchin, which was heavenly at sushi rose."], "output": "{'aspect_term': [['sea urchin', '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 spectacular caviar to the hospitable waitstaff, I felt like royalty and enjoyed every second of it."], "output": "{'aspect_term': [['caviar', 'positive'], ['waitstaff', '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 was attentive and her suggestions of menu items was right on the mark."], "output": "{'aspect_term': [['service', 'positive'], ['menu items', '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 finish off such a delightful dinner experience you must have dessert, especially the White Chocolate Bread Pudding with Gelato and hot chocolate."], "output": "{'aspect_term': [['dessert', 'positive'], ['White Chocolate Bread Pudding with Gelato and hot chocolate', 'positive'], ['dinner', '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": ["Cozy romantic atomosphere with only around 15 tables at most."], "output": "{'aspect_term': [['atomosphere', 'positive'], ['tables', '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": ["Why make a reservation if you aren't going to keep it?"], "output": "{'aspect_term': [['reservation', '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": ["Get the soup and a nosh (pastrami sandwich) for $8 and you're golden."], "output": "{'aspect_term': [['soup', 'positive'], ['nosh (pastrami sandwich)', '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 been disappointed but their true strength lays in their amazingly delicious and cheap lunch specials."], "output": "{'aspect_term': [['lunch 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": ["When we notified him that he didn't mention the specials, he didn't apologize but let us know that we made a very good decision regardless."], "output": "{'aspect_term': [['specials', '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": ["this is the best secret place in midtown', I heard that from the bartender, after having brilliant food ( try steak with portobello mushrooms) and drinks on the bar last Tuesday."], "output": "{'aspect_term': [['bartender', 'neutral'], ['food', 'positive'], ['drinks', 'positive'], ['steak with portobello mushrooms', 'positive'], ['bar', 'neutral']], 'aspect_category': [[None, 'neutral'], [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 secret is the lunch menu which offers a complimentary appetizer with every entree ordered."], "output": "{'aspect_term': [['lunch menu', 'positive'], ['appetizer', 'positive'], ['entree', '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": ["These innovators of french indian fusion do a great job of making dishes as interesting as possible while still being accessible."], "output": "{'aspect_term': [['french indian fusion', 'positive'], ['dishes', '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 had the Pad Thai and the noodles were sticky."], "output": "{'aspect_term': [['Pad Thai', 'negative'], ['noodles', '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": ["Don't go alone---even two people isn't enough for the whole experience, with pickles and a selection of meats and seafoods."], "output": "{'aspect_term': [['pickles', 'positive'], ['selection of meats and seafoods', '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": ["Luckily we saved room for the BBQ Salmon, Sea Bass and Crispy Duck."], "output": "{'aspect_term': [['BBQ Salmon', 'positive'], ['Sea Bass', 'positive'], ['Crispy Duck', '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": ["Had we been stalling I could understand where they were coming from, but we had been there less than an hour and they hadn't even brought us a check yet!"], "output": "{'aspect_term': [['check', '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 cafe itself was really nice with comfortable outdoor chairs and tables, but the service could have been better."], "output": "{'aspect_term': [['cafe', 'positive'], ['outdoor chairs', 'positive'], ['tables', 'positive'], ['service', 'negative']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [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": ["At 5 dumplings for $1, you just cannot go wrong."], "output": "{'aspect_term': [['dumplings', '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": ["While the prices are nothing special, the portions are huge."], "output": "{'aspect_term': [['prices', 'neutral'], ['portions', '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 makes you feel at home, the food is great and the atmosphere is WONDERFUL!"], "output": "{'aspect_term': [['staff', 'positive'], ['food', 'positive'], ['atmosphere', '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 is charming."], "output": "{'aspect_term': [['Decor', '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 was the friendliest that have seen in New York."], "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 'kamasutra' and 'bombay cosmopolitan' are excellent and will have you tipsy in no time."], "output": "{'aspect_term': [['kamasutra', 'positive'], ['bombay cosmopolitan', '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": ["Food-awesome."], "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": ["we came here on a crowded saturday night and were seated right away despite being 15 minutes late for our reservation."], "output": "{'aspect_term': [['reservation', 'neutral'], ['seated', '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": ["We even had a visit from the Manager who wanted to make sure we were enjoying ourselves."], "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": ["Moules were excellent, lobster ravioli was VERY salty!"], "output": "{'aspect_term': [['Moules', 'positive'], ['lobster ravioli', '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": ["It took half an hour to get our check, which was perfect since we could sit, have drinks and talk!"], "output": "{'aspect_term': [['drinks', 'neutral'], ['check', '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": ["Indoor was very cozy and cute."], "output": "{'aspect_term': [['Indoor', '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 okay and the prices here are mediocre."], "output": "{'aspect_term': [['food', 'neutral'], ['prices', '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 had a girls' night dinner here for restaurant week."], "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": ["Authentic Pakistani food."], "output": "{'aspect_term': [['Pakistani 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": ["just got back from lunch at Tamarind and it was excellent."], "output": "{'aspect_term': [['lunch', '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've read some of the previews reviews - people are either not New Yorkers or have more appreciation for ambience then food."], "output": "{'aspect_term': [['ambience', '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": ["Patroon features a nice cigar bar and has great staff."], "output": "{'aspect_term': [['cigar bar', 'positive'], ['staff', '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": ["Try the Pad Se-Ew or Chicken with Cashew Nuts for a memorable and repeatable experience."], "output": "{'aspect_term': [['Pad Se-Ew', 'positive'], ['Chicken with Cashew Nuts', '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 wonderful, tasty and filling, and the service is professional and friendly."], "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": ["Bagels are ok, but be sure not to make any special requests!"], "output": "{'aspect_term': [['Bagels', '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 grew up on these bagels."], "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": ["Nothing fancy but really good food with pretty reasonable price."], "output": "{'aspect_term': [['food', '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": ["Both times we waited well over a half hour for a table (even though we had reservations)."], "output": "{'aspect_term': [['table', 'negative'], ['reservations', '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": ["I'm happy to have Nosh in the neighborhood and the food is very comforting."], "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": ["For years, I thought Tuscan cuisine was the best, but Salvatore converted me to the hearty Neapolitan fare on my first visit."], "output": "{'aspect_term': [['Tuscan cuisine', 'conflict'], ['Neapolitan fare', '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": ["I am happy i did the food was awsome."], "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": ["But don't ever order bacon late at nite (either platter or in sandwiches, for that matter don't from any take out place) as it is from the morning frying turns out hard almost like bacos, hurt my molars."], "output": "{'aspect_term': [['bacon', 'negative'], ['platter', 'negative'], ['in sandwiches', 'negative'], ['frying', 'negative'], ['bacos', '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": ["I've had the lunch buffet at Chennai a couple of times, when I have been in the neighborhood."], "output": "{'aspect_term': [['lunch buffet', '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 keep my fingers crossed the whole subway ride hoping that there will be a table I can sit at by myself and not have to share with the rice congee soup people."], "output": "{'aspect_term': [['table', 'neutral'], ['rice congee soup', '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": ["It is a lot of fun with live entertainment and all kinds of Disney type special effects."], "output": "{'aspect_term': [['live entertainment', 'positive'], ['special effects', '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": ["If you live in new york city, you'll find better food at small restaurants outside of time square and spend half the amount."], "output": "{'aspect_term': [['food', 'negative'], ['amount', '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": ["I would highly recommand requesting a table by the window."], "output": "{'aspect_term': [['table by the window', '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": ["Some baby pizzas get their wish."], "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": ["Staffs are not that friendly, but the taste covers all."], "output": "{'aspect_term': [['Staffs', 'negative'], ['taste', '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 quail was fantastic and unique and the pastas were full of flavor."], "output": "{'aspect_term': [['quail', 'positive'], ['pastas', 'positive'], ['flavor', '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": ["We figured we never had Argentinian Pizza before so we grabbed our lunch there, sharing a large Pelligrino, a pizza of two of their specials, one was goat cheese the other blue cheese, and both were excellent."], "output": "{'aspect_term': [['Argentinian Pizza', 'neutral'], ['lunch', 'neutral'], ['Pelligrino', 'positive'], ['pizza', 'positive'], ['goat cheese', 'positive'], ['blue cheese', 'positive']], 'aspect_category': [[None, 'neutral'], [None, 'neutral'], [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 menu choices are similar but the taste lacked more flavor than it looked."], "output": "{'aspect_term': [['taste', 'negative'], ['menu choices', 'neutral'], ['flavor', '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 food was not fresh, the sauces were bland and very oily."], "output": "{'aspect_term': [['food', 'negative'], ['sauces', '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 staff."], "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 best Chicken pad tai, I've ever had."], "output": "{'aspect_term': [['Chicken pad tai', '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 rest of the dim sum, though pricey by Chinatown standards, is worth it."], "output": "{'aspect_term': [['dim sum', '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 food is delicious - from the specials to the regular menu-fare, the dishes are never a disappointment."], "output": "{'aspect_term': [['food', 'positive'], ['dishes', 'positive'], ['specials', 'positive'], ['regular menu-fare', '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": ["But after last night, Spice Grill is the only place I'm eating indian cuisine."], "output": "{'aspect_term': [['indian cuisine', '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 only took about five or so minutes to get an empty table, but standing up wasn't too bad."], "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": ["The service was ok."], "output": "{'aspect_term': [['service', '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 soup is pretty good too."], "output": "{'aspect_term': [['soup', '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 tuna and wasabe potatoes are excellent."], "output": "{'aspect_term': [['tuna', 'positive'], ['wasabe potatoes', '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 was the only thing good about this restaurant."], "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": ["What is even better, is that the prices are very affordable as well, and the food is really good."], "output": "{'aspect_term': [['prices', '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": ["Acceptable prices."], "output": "{'aspect_term': [['prices', '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": ["Nice restaurant overall, with classic upscale Italian decor."], "output": "{'aspect_term': [['Italian decor', '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 not curry in a slurry crap, and regular run of the mill food."], "output": "{'aspect_term': [['curry', '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": ["Super friendly and knowledgable staff, fabulous bistro fare and a wonderful jazz brunch with great live jazz (the chilaquiles were awesome!"], "output": "{'aspect_term': [['staff', 'positive'], ['bistro fare', 'positive'], ['chilaquiles', 'positive'], ['jazz brunch', 'positive'], ['live jazz', '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": ["The waitresses are nice--also you can just get counter service sit."], "output": "{'aspect_term': [['waitresses', 'positive'], ['counter 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": ["Great place to grab a hot bagel on the way to work."], "output": "{'aspect_term': [['hot 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": ["Service was slow, but the people were friendly."], "output": "{'aspect_term': [['Service', 'negative'], ['people', '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 bread at the beginning is super tasty and makes you want more - the pizza is delicious and comes in personal sizes, however be warned that the Peter's Favourite pizza with prosciutto and baby arugula is actually a margarite pizza with cold prosciutto and baby arugula on top, like a salad."], "output": "{'aspect_term': [['bread', 'positive'], ['pizza', 'positive'], ['margarite pizza with cold prosciutto and baby arugula on top', 'neutral'], ['salad', 'neutral'], [\"Peter's Favourite pizza with prosciutto and baby arugula\", 'neutral']], 'aspect_category': [[None, 'positive'], [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 filet mignon dish was superb!"], "output": "{'aspect_term': [['filet mignon dish', '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 restuarant itself is not large, but seems to have several round tables to accomodate large groups hoping to save a buck to eat authentic Taiwanese."], "output": "{'aspect_term': [['round tables', 'positive'], ['Taiwanese', '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 always been friendly without seeming grating, and the chef has greeted us on a couple of occasions."], "output": "{'aspect_term': [['staff', 'positive'], ['chef', '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": ["head and shoulders above its neighboors on east 6 st, taj mahal is also very comparable, in food quality, to the much overpraised (and underdeserving) baluchi's."], "output": "{'aspect_term': [['food quality', '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": ["Much more reasonably priced too!"], "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": ["Food was very good, but not what I would consider out of this world."], "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": ["Why do people rave about the ambience."], "output": "{'aspect_term': [['ambience', '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 had been a regular due to the consistently good food and ease of getting a table."], "output": "{'aspect_term': [['food', 'positive'], ['getting a 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": ["Still, any quibbles about the bill were off-set by the pour-your-own measures of liquers which were courtesey of the house..."], "output": "{'aspect_term': [['bill', 'conflict'], ['measures of liquers', '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": ["I would highly recommend Nina's to anyone who wants to have a romantic dinner in a heart warming surrounding filled with candles and family pictures."], "output": "{'aspect_term': [['candles', 'positive'], ['dinner', 'positive'], ['surrounding', 'positive'], ['pictures', '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": ["BUt their best dish is thh Thai spiced curry noodles with shrimp - a dish that would cost $23.95 is most places, but it is $16 here."], "output": "{'aspect_term': [['dish', 'positive'], ['Thai spiced curry noodles with shrimp', 'positive'], ['dish', 'positive'], ['cost', '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 food was undercooked-the sauce watery, and the vegetables raw."], "output": "{'aspect_term': [['food', 'negative'], ['vegetables', 'negative'], ['sauce', '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": ["First the wrong bread came out with the appetizer, then when i tried to order a second glass of wine for my main course..."], "output": "{'aspect_term': [['bread', 'negative'], ['appetizer', 'neutral'], ['glass of wine', 'neutral'], ['main course', '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": ["Service was quick."], "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": ["It's a great place to pick up a cheap lunch or dinner."], "output": "{'aspect_term': [['lunch', 'positive'], ['dinner', '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 smell like they stuff them with old canned vegetables like the spinach mushroom calzone."], "output": "{'aspect_term': [['spinach mushroom calzone', 'negative'], ['canned vegetables', '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": ["Service and food is what any one would expect when spending that type of money."], "output": "{'aspect_term': [['Service', '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": ["It's simply the best meal in NYC."], "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": ["Faan's got a great concept but a little rough on the delivery."], "output": "{'aspect_term': [['delivery', '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've waited over one hour for 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": ["I have tried to make reservations, but both times, the hostess didn't have my name."], "output": "{'aspect_term': [['reservations', 'neutral'], ['hostess', '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 food is consistently wonderful - I've been coming here for years, and the owner has always been accomodating and friendly."], "output": "{'aspect_term': [['food', 'positive'], ['owner', '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 came out over cooked and the cheese was almost non existant."], "output": "{'aspect_term': [['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": ["if this happens, just ask for real naan."], "output": "{'aspect_term': [['naan', '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": ["Yeah Shanghai is also great but not quite as good -- they use the same amount of salt but without sweetness to balance out."], "output": "{'aspect_term': [['salt', '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 people with carts of food don't understand you because they don't speak English, their job is to give you the delicious food you point at."], "output": "{'aspect_term': [['food', 'positive'], ['people with carts of 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": ["Will have to return to try the chocolate!"], "output": "{'aspect_term': [['chocolate', '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": ["people are rude bit again it's new york!"], "output": "{'aspect_term': [['people', '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 all you can eat deal is truly amazing here."], "output": "{'aspect_term': [['all you can eat deal', '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 nothing like its menu description."], "output": "{'aspect_term': [['food', 'negative'], ['menu description', '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": ["then we ordered a dinosaur rolls and white tuna sashimi."], "output": "{'aspect_term': [['dinosaur rolls', 'neutral'], ['white tuna sashimi', '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 porcini mushroom pasta special was tasteless, so was the seafood tagliatelle."], "output": "{'aspect_term': [['porcini mushroom pasta special', 'negative'], ['seafood tagliatelle', '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 isn't the greatest , but I suppose that's how they keep the prices down ."], "output": "{'aspect_term': [['atmosphere', 'neutral'], ['prices', '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": ["All the NYU students love this place so it makes for a fun young atmosphere."], "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": ["To begin, we were told there was a 30 minute wait and started to leave, when the hostess offered to call us on our cell phone when the table was ready."], "output": "{'aspect_term': [['hostess', 'positive'], ['wait', 'negative'], ['table', 'positive']], 'aspect_category': [[None, 'positive'], [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 bagels are fabulous."], "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": ["Delivery service is great too."], "output": "{'aspect_term': [['Delivery 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": ["I ordered a Lassi and asked 4 times for it but never got it."], "output": "{'aspect_term': [['Lassi', '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": ["Granted the space is smaller than most, it is the best service you will find in even the largest of restaurants."], "output": "{'aspect_term': [['space', 'negative'], ['service', '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": ["Ambience is delightful, service impeccable."], "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": ["We saw them heating up at least one frozen item though I'm not sure which dim sum dish it was."], "output": "{'aspect_term': [['dim sum dish', '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 touch more jalapeno heat for contrast and it would have been very good indeed."], "output": "{'aspect_term': [['jalapeno', '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 food is asian-air fusion."], "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 my husband and go there, we spend $60.00 (have LOBSTER TAILS UMMMMM need I say more) I can't say any more, it a place you'll never forget If you never go, you'll miss A Meal of your life time"], "output": "{'aspect_term': [['place', 'positive'], ['Meal', 'positive'], ['LOBSTER TAILS', '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": ["Unless you are eating in the Pizzeria side of this place, and are not in a rush, this place is a bad idea."], "output": "{'aspect_term': [['place', 'negative'], ['place', '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": ["And they have these home made potato chips at the bar that are the most delicious things in the world!"], "output": "{'aspect_term': [['potato chips', 'positive'], ['bar', '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": ["It costs $2 extra to turn a regular roll into an inside-out roll, but the roll more than triples in size, and that's not just from the rice."], "output": "{'aspect_term': [['roll', 'negative'], ['roll', 'negative'], ['roll', 'negative'], ['rice', '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": ["THR AT MOSHPHERE IS COMPACT, MODERN, YET COZY."], "output": "{'aspect_term': [['AT MOSHPHERE', '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": ["Both the fresh mozzerella slices and the Plain Cheese slice are phenomenal."], "output": "{'aspect_term': [['fresh mozzerella slices', 'positive'], ['Plain Cheese slice', '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": ["Kosher dills are the perfect compliment for your unforgetable sandwich and they give you plenty of them."], "output": "{'aspect_term': [['Kosher dills', 'positive'], ['sandwich', '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": ["Save your money and don't waste your calories, go to Margharita's on Washington Street instead, they have amazing food and the BEST service."], "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 first 2 courses were very good, but the chocolate sampler was too rich for me and the dessert wine far too sweet."], "output": "{'aspect_term': [['courses', 'positive'], ['chocolate sampler', 'negative'], ['dessert wine', 'negative']], 'aspect_category': [[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": ["The service was fast and friendly and the food was very tasty and they had the best hot sauce to add to your meals."], "output": "{'aspect_term': [['service', 'positive'], ['food', 'positive'], ['hot sauce', 'positive'], ['meals', '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 grilled cheese at home afterwards was better.!!"], "output": "{'aspect_term': [['grilled cheese', '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": ["Diner food at bistro prices is a bummer ."], "output": "{'aspect_term': [['food', 'negative'], ['prices', '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": ["I've been here 3 times for lunch and it is one of my favorites in the city."], "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": ["Consistently good Japanese Tapas."], "output": "{'aspect_term': [['Japanese Tapas', '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 cool bar with great food, and tons of excellent beer."], "output": "{'aspect_term': [['bar', 'positive'], ['food', 'positive'], ['beer', '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 food always tastes fresh and served promptly."], "output": "{'aspect_term': [['food', 'positive'], ['served', '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 picks are:  - Scallion Pancake (fried with vegetable juice, very special and tasty)  - Guizhou Chicken  - Shredded Squid Family Style (one of my personal favorites)  - Sichuan Spicy Soft Shell Crab  - Shuizhu Fish (this one is for hardcore Sichuan food fans, I wouldn't recommend to my American friends as it's very spicy."], "output": "{'aspect_term': [['Scallion Pancake', 'positive'], ['vegetable juice', 'positive'], ['Guizhou Chicken', 'positive'], ['Shredded Squid Family Style', 'positive'], ['Sichuan Spicy Soft Shell Crab', 'positive'], ['Shuizhu Fish', 'positive'], ['Sichuan food', 'neutral']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive'], [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": ["Not a small feat for good french food in the area."], "output": "{'aspect_term': [['french 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": ["but the service was a bit slow."], "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": ["Service is fast and friendly."], "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": ["Priced at upper intermediate range."], "output": "{'aspect_term': [['Priced', '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": ["Over price, and small portions ."], "output": "{'aspect_term': [['price', 'negative'], ['portions', '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": ["You can even get packages of the chutneys to stock your fridge!"], "output": "{'aspect_term': [['chutneys', '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 price was extremely reasonable for the appetizers and food we ate."], "output": "{'aspect_term': [['price', 'positive'], ['appetizers', '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": ["What came to our table was burned beyond recognition and stringy."], "output": "{'aspect_term': [['table', '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 main downside to the place is the nazi-like guy running it who constantly complains about the noise level."], "output": "{'aspect_term': [['noise level', 'negative'], ['guy', '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": ["After 2 tries by the waiter to take it away (we hadn't even looked at it yet, we had full beers yet to drink), the manager approached and told us they needed the table for people with reservations."], "output": "{'aspect_term': [['waiter', 'negative'], ['beers', 'neutral'], ['manager', 'negative'], ['reservations', 'positive']], 'aspect_category': [[None, 'negative'], [None, 'neutral'], [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": ["Someone else recommended the dessert - we also left that."], "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": ["The environment is romantic, but the food is horrible, the service is pathetic, and gabriella lies about everything she could."], "output": "{'aspect_term': [['environment', 'positive'], ['food', 'negative'], ['service', 'negative']], 'aspect_category': [[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 actually gave 10% tip (which we have never done despite mediocre food and service), because we felt totally ripped off."], "output": "{'aspect_term': [['food', 'neutral'], ['service', 'neutral'], ['tip', 'negative']], 'aspect_category': [[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": ["My co-workers had to wait almost an hour for delivery, only to discover that what they got was not what they ordered."], "output": "{'aspect_term': [['delivery', '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 chicken parm was edible but had canned tomato sauce and boxed pasta and the chicken with portobello mushrooms consisted of dry, inedible chicken with terrible sauce."], "output": "{'aspect_term': [['chicken parm', 'conflict'], ['chicken with portobello mushrooms', 'negative'], ['chicken', 'negative'], ['tomato sauce', 'negative'], ['pasta', 'negative'], ['sauce', 'negative']], 'aspect_category': [[None, 'conflict'], [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": ["The dishes offered were unique, very tasty and fresh from the lamb sausages, sardines with biscuits, large whole shrimp to the amazing pistachio ice cream (the best and freshest I've ever had)."], "output": "{'aspect_term': [['dishes', 'positive'], ['lamb sausages', 'positive'], ['sardines with biscuits', 'positive'], ['large whole shrimp', 'positive'], ['pistachio ice cream', '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": ["The mussaman curry that I ordered was as thin as water and aside from the poorly fried tofu that I ordered in it, they graciously provided me with ONE piece of poorly cooked potato."], "output": "{'aspect_term': [['mussaman curry', 'negative'], ['fried tofu', 'negative'], ['potato', '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 and I have been there a couple of times and each time we sat at the sushi bar (chef Yoshi) and ordered everything ala carte."], "output": "{'aspect_term': [['sushi bar', 'neutral'], ['chef', 'neutral'], ['ala carte', '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": ["Oh yes, and they lie on the phone, claiming they have seating in the garden, then of course the seats are not available."], "output": "{'aspect_term': [['seating in the garden', 'neutral'], ['seats', '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 left after one drink."], "output": "{'aspect_term': [['drink', '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": ["There are a few Italian employees who may not speak the best English but for me that adds to the experience."], "output": "{'aspect_term': [['employees', '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 have to say that if this what makes it easier to get a saet a lunch- I dont mind."], "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": ["Drawbacks: service is slow and they don't toast!"], "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": ["Personal pans are the perfect size for those hungry nights."], "output": "{'aspect_term': [['Personal pans', '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 actually get 2 salads worth if u take it home and add it to some lettuce!"], "output": "{'aspect_term': [['salads', 'negative'], ['lettuce', '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": ["however, it's the service that leaves a bad taste in my mouth."], "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": ["$20 gets you unlimited sushi of a very high quality- I even took a friend here from Japan who said it was one of the best sushi places in the US that he has been to."], "output": "{'aspect_term': [['sushi', 'positive'], ['sushi places', 'positive'], ['quality', '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": ["go here for the drinks!"], "output": "{'aspect_term': [['drinks', '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": ["He not only makes his own homemade mozzarella, but every pie is ultra fresh."], "output": "{'aspect_term': [['mozzarella', 'positive'], ['pie', '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 did have to wait at the bar for approx."], "output": "{'aspect_term': [['bar', '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": ["though the service could be better (possibly due to more than one very large group in the house), it is very cordial and warm, as is the general clientele."], "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 music does get a little loud at times, but it just made me want to lean closer to my beautiful wife, and as I did, I got a whiff of corriander."], "output": "{'aspect_term': [['music', 'conflict'], ['corriander', '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": ["Other guests enjoyed pizza, santa fe chopped salad and fish and chips."], "output": "{'aspect_term': [['pizza', 'positive'], ['santa fe chopped salad', 'positive'], ['fish and chips', '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 list isn't great, and the desserts are shipped in from Bruno's down the street, which is not as good as it used to be."], "output": "{'aspect_term': [['wine list', 'negative'], ['desserts', '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": ["I have been here a few times for dinner, once for brunch and twice for lunch."], "output": "{'aspect_term': [['dinner', 'neutral'], ['brunch', 'neutral'], ['lunch', '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 dining room is quietly elegant with no music to shout over -- how refreshing!"], "output": "{'aspect_term': [['dining room', '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": ["Quite frankly, this is some of the worst sushi I have ever tried."], "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": ["And the Tom Kha soup was pathetic."], "output": "{'aspect_term': [['Tom Kha soup', '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": ["Its a great place for a casual date or to entertain clients for lunch."], "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": ["The service is good and the resturant is clean."], "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": ["You can't say its cheap because food is cheaper in Chinatown."], "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": ["Some of the workers ignore me and talk to the female customers, other times, they've skipped my order."], "output": "{'aspect_term': [['workers', '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": ["My entree of hot pot with seafood was full of imitation crabmeat with a couple pieces of shrimp and squid, and was unnecessarily heated with a burner."], "output": "{'aspect_term': [['hot pot with seafood', 'negative'], ['shrimp', 'negative'], ['squid', 'negative'], ['entree', 'positive'], ['crabmeat', 'negative']], 'aspect_category': [[None, 'negative'], [None, 'negative'], [None, 'negative'], [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 LOVE their Thai noodles with shrimp and chicken and coconut juice is the MUST!"], "output": "{'aspect_term': [['Thai noodles with shrimp and chicken and coconut juice', '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": ["While we thoroughly enjoyed the food, it was annoying to scream across the table for conversation."], "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 sushi has been from average to below average, the wait service has always been sub-par the atmosphere goes from nice to really irritating (if you sit in the area beyond the kitchen, the acousitcs are horrid, everything echoes is extremely loud)."], "output": "{'aspect_term': [['sushi', 'negative'], ['wait service', 'negative'], ['atmosphere', 'conflict'], ['area', 'negative']], 'aspect_category': [[None, 'negative'], [None, 'negative'], [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": ["like saying her bread comes from a special bakery when we have seen her buying it dowtown manhathan."], "output": "{'aspect_term': [['bread', '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've been to sapphire twice and both times the food was fine, if not 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 bread and lamb chops I had before the meal were quite good, however."], "output": "{'aspect_term': [['bread', 'positive'], ['lamb chops', 'positive'], ['meal', '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": ["If you are looking for a good quality, cheap eats - this is the place."], "output": "{'aspect_term': [['quality', '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 narrow corridor leads to a tiny space where there are three tiny white tiled counters, a great deal of mess (stacks of bottles, cans) and a small counter holding 12-14 entrees."], "output": "{'aspect_term': [['corridor', 'negative'], ['space', 'negative'], ['counters', 'negative'], ['counter', 'negative'], ['entrees', 'neutral']], 'aspect_category': [[None, 'negative'], [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": ["I've been to several places for Dim Sum and this has got to be the WORST."], "output": "{'aspect_term': [['Dim Sum', '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 friendly service, Fast seating, Fast Delivery, Excellent sushi."], "output": "{'aspect_term': [['service', 'positive'], ['seating', 'positive'], ['Delivery', 'positive'], ['sushi', '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 dish had like 6 pieces of beef in it."], "output": "{'aspect_term': [['dish', 'neutral'], ['beef', '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": ["My husband and I enjoyed each of the 6 taste size portions and left completely full."], "output": "{'aspect_term': [['portions', '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": ["By far, the best pizza in Manhattan."], "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": ["After dinner, take your date to the HUGE dance floor, probably one of the biggest you'll see in NY."], "output": "{'aspect_term': [['dance floor', 'positive'], ['dinner', '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": ["Bottom line: B+ for the food, F for the service."], "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": ["The atmosphere is great!!!"], "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": ["It's charmingly small and that leads to an atmoshere that is extremely cozy and romantic, even."], "output": "{'aspect_term': [['atmoshere', '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": ["yourself a favor and have dinner here and see if you dont agree with me."], "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": ["I ordered the smoked salmon and roe appetizer and it was off flavor."], "output": "{'aspect_term': [['smoked salmon and roe appetizer', '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 at reasonable prices."], "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": ["Nice atmosphere, the service was very pleasant and the desert was good."], "output": "{'aspect_term': [['atmosphere', 'positive'], ['service', 'positive'], ['desert', '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 decor in this place is very diner-ish and the kind of place you expect in the East Village - not romantic, just simple, small and sparse."], "output": "{'aspect_term': [['decor', '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": ["At the end you're left with a mild broth with noodles that you can slurp out of a cup."], "output": "{'aspect_term': [['broth with noodles', '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": ["Reasonable prices."], "output": "{'aspect_term': [['prices', '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 to spice three times- twice during lunch and once at dinner."], "output": "{'aspect_term': [['lunch', 'neutral'], ['dinner', '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": ["When I saw that their website had a link to da Ciro in Napoli, I knew there was going to be good 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": ["Even though the restaurant was packed, we were seated promptly and even asked for a table upstairs with no problems."], "output": "{'aspect_term': [['table', 'positive'], ['seated', '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 am not a vegetarian but, almost all the dishes were great."], "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": ["($200 for 2 glasses of champagne, not too expensive bottle of wine and 2 after dinner drinks)."], "output": "{'aspect_term': [['glasses of champagne', 'negative'], ['bottle of wine', 'negative'], ['after dinner drinks', '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": ["big and soft as well as good lunch food."], "output": "{'aspect_term': [['lunch 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": ["Don't waste money on decor."], "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": ["Service is top notch."], "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": ["Their calzones are horrific, bad, vomit-inducing, YUCK."], "output": "{'aspect_term': [['calzones', '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": ["Stuffing yourself with Japanese food is a rare thing."], "output": "{'aspect_term': [['Japanese 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 lobster sandwich is $24 and although it was good it was not nearly enough to warrant that price."], "output": "{'aspect_term': [['lobster sandwich', 'conflict'], ['price', '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": ["As for the bar, this is another bad idea."], "output": "{'aspect_term': [['bar', '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 great 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": ["It may be a bit packed on weekends, but the vibe is good and it is the best French food you will find in the area."], "output": "{'aspect_term': [['vibe', 'positive'], ['French food', 'positive'], ['packed', 'negative']], 'aspect_category': [[None, 'positive'], [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": ["But when you are seated the waitresses are great, they explain everything on the menu, and the price of the food is really cheap for the service you get."], "output": "{'aspect_term': [['waitresses', 'positive'], ['price', 'positive'], ['service', 'positive'], ['menu', 'neutral'], ['food', 'neutral']], 'aspect_category': [[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": ["Planet Thailand has always been a hit with me , I go there usually for the sushi, which is great , the thai food is excellent too ."], "output": "{'aspect_term': [['sushi', 'positive'], ['thai 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 puke green walls leave a lot to be desired, but the food is very good."], "output": "{'aspect_term': [['food', 'positive'], ['walls', '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": ["Great bagels, spreads and a good place to hang out in."], "output": "{'aspect_term': [['bagels', 'positive'], ['spreads', '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": ["Well, this place is so Ghetto its not even funny."], "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": ["Went there for an office lunch."], "output": "{'aspect_term': [['office 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": ["Seating is ok even though sometimes there's alot of people."], "output": "{'aspect_term': [['Seating', '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": ["Also, the hostess called me today to thank us for coming and mentioned how she hoped that my girlfriend enjoyed her birthday - unexpected, but a truly above and beyond thing to do..."], "output": "{'aspect_term': [['hostess', '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 is the most Japanese it can ever get."], "output": "{'aspect_term': [['place', '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 pizza and fantastic service."], "output": "{'aspect_term': [['pizza', '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 usually just get some of the dinner specials and they are very reasonably priced and very tasty."], "output": "{'aspect_term': [['dinner specials', 'positive'], ['priced', '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 delicious and beautifully prepared along with the friendly and personable service."], "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 space is nice but when we order our drink we were in for a surprise."], "output": "{'aspect_term': [['space', 'positive'], ['drink', '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 service does sometimes lack focus and it is not ideal if you are in a hurry but I have never been treated rudely."], "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 food was absolutely horrible!"], "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": ["I think the stuff was better than Disney."], "output": "{'aspect_term': [['stuff', '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 entrees to the sides to the drinks, everything was creatively prepared yet still simple."], "output": "{'aspect_term': [['entrees', 'positive'], ['sides', 'positive'], ['drinks', '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 dim sum here is only so-so."], "output": "{'aspect_term': [['dim sum', '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 can get pricey but the prixe fixe tasting menu is the greatest food for a good price and they cater the food to any food allergies or food you don't like."], "output": "{'aspect_term': [['food', 'conflict'], ['food', 'positive'], ['price', 'positive'], ['food', 'positive'], ['food', 'neutral'], ['food', 'negative']], 'aspect_category': [[None, 'conflict'], [None, 'positive'], [None, 'positive'], [None, 'positive'], [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 menu looked good, except for offering the Chilean Sea Bass, but the server does not offer up the specials that were written on the board outside."], "output": "{'aspect_term': [['menu', 'positive'], ['Chilean Sea Bass', 'negative'], ['server', 'negative'], ['specials', 'neutral']], 'aspect_category': [[None, 'positive'], [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": ["Excellent lunch buffet for only $6.95."], "output": "{'aspect_term': [['lunch buffet', '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 is nothing like the one on the website."], "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": ["With the theater 2 blocks away we had a delicious meal in a beautiful room."], "output": "{'aspect_term': [['meal', 'positive'], ['room', '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": ["Big Wong gets big Ups for a fine establishment."], "output": "{'aspect_term': [['establishment', '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 live in Upper Manhattan, Siam Square is THE place for Thia food."], "output": "{'aspect_term': [['Thia 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": ["Our son loves pizza and we have a certified Neapolitan pizzaria in our home city (Seattle), we liked this nearly as much - and the differences were more about personal preference than any reflection on either restaurant."], "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": ["Our waiter and all of the people helping him were attentive and genuine."], "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 service is ok, some of the people didn't get what they asked for."], "output": "{'aspect_term': [['service', '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": ["We always get a sampling of appetizers and share."], "output": "{'aspect_term': [['appetizers', '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 isn't classical restaurant fare, the chef has given new life to an old cuisine with some really innovative and tasty dishes that are genuinely Indian without being heavy or same old restaurant burn-outs."], "output": "{'aspect_term': [['chef', 'positive'], ['dishes', 'positive'], ['cuisine', 'neutral'], ['Indian', 'positive']], 'aspect_category': [[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": ["The beverages were excellent, and the dessert was good."], "output": "{'aspect_term': [['beverages', 'positive'], ['dessert', '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": ["A++   The service was good to excellent along with the attitude."], "output": "{'aspect_term': [['service', 'positive'], ['attitude', '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 could not catch our waiter's eye, and he ignored us."], "output": "{'aspect_term': [['waiter', '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 place is small and intimate and you may feel a little crowded, but the service is excellent and it's great for friends out, a romantic date, or a special occassion."], "output": "{'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": ["For the next hour and a half we stood in the crowded lobby area of this touristy restaurant listening to all types of explanations of why we were not being seated."], "output": "{'aspect_term': [['lobby area', 'negative'], ['seated', '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": ["Also, don't plan on asking for your favorite roll, if it's not on the menu, you can't have it."], "output": "{'aspect_term': [['roll', 'negative'], ['menu', '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 staff at this little bistro is very friendly, I have never experienced more incompetency."], "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": ["If you like spicy food get the chicken vindaloo."], "output": "{'aspect_term': [['chicken vindaloo', 'neutral'], ['spicy 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": ["It's all about 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": ["Downstairs lounge is always a good attraction"], "output": "{'aspect_term': [['Downstairs lounge', '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": ["Owner must have coem on this website to give himself credit."], "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": ["I didn't take a look at the rest menu, but the oysters were fantastic."], "output": "{'aspect_term': [['menu', 'neutral'], ['oysters', '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": ["As we were leaving, the couple standing by the door said to another waiter, we're not in a hurry."], "output": "{'aspect_term': [['waiter', '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": ["Ok, so the servers wander around a little clueless, but there's more than enough servers for the crowd they get -- it's fine, you just have to make a small effort to get their attention."], "output": "{'aspect_term': [['servers', 'negative'], ['servers', '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": ["Nothing better than buying a snapple for $3.25 too."], "output": "{'aspect_term': [['snapple', '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": ["Veal Parmigana - Better than Patsy's!"], "output": "{'aspect_term': [['Veal Parmigana', '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 am not the most experienced person when it comes to Thai food, but my friend who took me there is."], "output": "{'aspect_term': [['Thai 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": ["INCREDIBLY POOR SERVICE AN FOOD QUALITY AT EXORBITANT PRICES."], "output": "{'aspect_term': [['SERVICE', 'negative'], ['FOOD QUALITY', 'negative'], ['PRICES', '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": ["So all I'm trying to say is this restaurant is by far the best thai food restaurant I've ever been to."], "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": ["Price and quality of fish alone will keep us from making a return visit."], "output": "{'aspect_term': [['Price', 'negative'], ['fish', 'negative'], ['quality', '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": ["Bill a little high, but worth it."], "output": "{'aspect_term': [['Bill', '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 ate clams oreganta and spectacular salad with perfectly marinated cucumbers and tomatoes with lots of shrimp and basil."], "output": "{'aspect_term': [['clams oreganta', 'positive'], ['salad with perfectly marinated cucumbers and tomatoes with lots of shrimp and basil', '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 recieved prompt service with a smile."], "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": ["Other than being a little crowded and a bit overpriced, the atmosphere is filled with energy (and the beautiful people of course) and the food was surprising good!"], "output": "{'aspect_term': [['atmosphere', 'positive'], ['people', '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": ["The service is always bad though, don't expect much of anything from your server, and I would not recommend bringing a date here either."], "output": "{'aspect_term': [['service', 'negative'], ['server', '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": ["They charge $6.00 for rice."], "output": "{'aspect_term': [['rice', '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 have over 100 different beers to offer thier guest so that made my husband very happy and the food was delicious, if I must recommend a dish it must be the pumkin tortelini."], "output": "{'aspect_term': [['beers', 'positive'], ['food', 'positive'], ['pumkin tortelini', 'positive'], ['dish', '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": ["Their eggplant is so delicate, sweet tender!"], "output": "{'aspect_term': [['eggplant', '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": ["Usually 3 vs. 4 items per dish."], "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": ["In summer-eat outside on a terrace (another great feature of Suan)!!!"], "output": "{'aspect_term': [['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": ["It took them 25 minutes to bring our appetizer."], "output": "{'aspect_term': [['appetizer', '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 fried rice is amazing here."], "output": "{'aspect_term': [['fried rice', '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 get what you pay for and with that logic in mind, Spice is a great place to grab some cheap eats and drinks in a beautiful setting."], "output": "{'aspect_term': [['eats', 'positive'], ['drinks', 'positive'], ['setting', '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 the mango chicken and i can't go on to tell you how delicious that was and the presentation was beatiful."], "output": "{'aspect_term': [['mango chicken', 'positive'], ['presentation', '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": ["Great atmoshere and worth every bit."], "output": "{'aspect_term': [['atmoshere', '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 ambiance is minimal the food is not phenomenal, but some dishes are quite good, such as the eggplant parmesan, veal in carozza chicken saltimbocca."], "output": "{'aspect_term': [['ambiance', 'positive'], ['food', 'negative'], ['dishes', 'positive'], ['eggplant parmesan', 'positive'], ['veal in carozza chicken saltimbocca', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'negative'], [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 zucchini and mashed potatoes are a blend of garlic and butter which simply melts in your mouth."], "output": "{'aspect_term': [['zucchini', 'positive'], ['mashed potatoes', 'positive'], ['garlic', 'positive'], ['butter', '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": ["delicious simple food in nice outdoor atmosphere."], "output": "{'aspect_term': [['food', 'positive'], ['atmosphere', '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 friend ordered some of their special sushi rolls which had excellent presentation and tasted great!"], "output": "{'aspect_term': [['sushi 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": ["Ive been here so many times the waiters know my name."], "output": "{'aspect_term': [['waiters', '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 pizza is delicious and the proprietor is one of the nicest in NYC."], "output": "{'aspect_term': [['pizza', 'positive'], ['proprietor', '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 noodle and rices dishes taste great."], "output": "{'aspect_term': [['noodle and rices 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": ["Taj Mahal offeres gret value and great food."], "output": "{'aspect_term': [['value', '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 was boring and expensive."], "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": ["He offers subpar service and has no personality."], "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": ["Quality of food is excellent and price is cheap, stick to pork, fish, chicken, lamb and vegetables."], "output": "{'aspect_term': [['Quality of food', 'positive'], ['price', 'positive'], ['pork', 'positive'], ['fish', 'positive'], ['chicken', 'positive'], ['lamb', 'positive'], ['vegetables', 'positive']], 'aspect_category': [[None, 'positive'], [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 service is outstanding and my crab-cake eggs benedict could not have been better."], "output": "{'aspect_term': [['service', 'positive'], ['crab-cake eggs benedict', '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 son and his girlfriend both wanted cheeseburgers and they were huge!"], "output": "{'aspect_term': [['cheeseburgers', '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 thing I moderately enjoyed was their Grilled Chicken special with Edamame Puree."], "output": "{'aspect_term': [['Grilled Chicken special with Edamame Puree', '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": ["We would like to thank Marcelo and Grace for a wonderful dining experience!!!"], "output": "{'aspect_term': [['dining', '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 not very tasty, the portioins were tiny even for such a high quality restaurant."], "output": "{'aspect_term': [['food', 'negative'], ['portioins', '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": ["After being told that our party of three would be seated in 10 minutes and watching other parties (multiples of 2 and higher) seated for 40 minutes, the three of us were squished into a small 2-person table."], "output": "{'aspect_term': [['2-person 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": ["The food at this place is 'gourmet' Indian cuisine."], "output": "{'aspect_term': [['food', 'neutral'], [\"'gourmet' Indian cuisine\", '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": ["Try green curry with vegetables."], "output": "{'aspect_term': [['green curry with vegetables', '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": ["Pair you food with the excellent beers on tap or their well priced wine list."], "output": "{'aspect_term': [['food', 'neutral'], ['beers on tap', 'positive'], ['wine list', 'positive'], ['priced', 'positive']], 'aspect_category': [[None, 'neutral'], [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 offer the same menu but have creative drinks that are loaded with alcohol and cheeky names -- but they do cost you."], "output": "{'aspect_term': [['menu', 'neutral'], ['drinks', '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": ["i don't usually order wine with indian so i can't comment on their wine list or their wines."], "output": "{'aspect_term': [['wine', 'neutral'], ['indian', 'neutral'], ['wine list', 'neutral'], ['wines', '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": ["We ate here in March, 2006 and ordered the pre-theatre 3-course dinner with wine flight."], "output": "{'aspect_term': [['pre-theatre 3-course dinner', 'neutral'], ['wine flight', '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": ["Drinks way over priced."], "output": "{'aspect_term': [['Drinks', 'negative'], ['priced', '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": ["I would never wait for a table to eat, it just is not THAT great."], "output": "{'aspect_term': [['table', '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": ["By far the best salad I have had in a fast food restaurant."], "output": "{'aspect_term': [['salad', 'positive'], ['fast food', '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 dish is my favorite and I always get it when I go there and never get tired of it."], "output": "{'aspect_term': [['dish', '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 only does make the best pizza in NY , maybe anywhere."], "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 was with a party of 7 (close but not next the the front doors) and we were eating with our coats on."], "output": "{'aspect_term': [['front doors', '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 going out for a nice dinner, I like a nice ambiance as well as very good food."], "output": "{'aspect_term': [['dinner', '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": ["The soup for the udon was soy sauce and water."], "output": "{'aspect_term': [['soup for the udon', 'negative'], ['soy sauce', 'neutral'], ['water', 'neutral']], 'aspect_category': [[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": ["The rice to fish ration was also good--they didn't try to overpack the rice."], "output": "{'aspect_term': [['rice to fish ration', 'positive'], ['rice', '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": ["It is set far from the small street it's on, and there is no traffic noise."], "output": "{'aspect_term': [['traffic noise', '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 have been to this place many times, and always have great food, wine, and service."], "output": "{'aspect_term': [['food', 'positive'], ['wine', '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": ["We parked on the block of Nina's the place looked nice, with people obviously enjoying their pizzas."], "output": "{'aspect_term': [['place', 'positive'], ['pizzas', '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 atmosphere, combination of all the hottest music dress code is relatively strict except on Fridays."], "output": "{'aspect_term': [['atmosphere', 'positive'], ['music', 'positive'], ['dress code', 'negative']], 'aspect_category': [[None, 'positive'], [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 entertainment was great they have shows that go on through out the dinner."], "output": "{'aspect_term': [['shows', 'positive'], ['dinner', 'neutral'], ['entertainment', '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": ["The bagels always warm, soft on the inside, crispy on the outside and enormous in size."], "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 food is expensive, but worth every bite."], "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": ["Succulent steaks cooked precisely to your desired 'doneness' accompanied by salads and sides that don't look like leafy road kill."], "output": "{'aspect_term': [['steaks', 'positive'], ['salads', 'positive'], ['sides', '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": ["He was terribly thirsty after the meal too."], "output": "{'aspect_term': [['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 specials are usually quite good too."], "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": ["I would highly recommend this place to anyone looking for a casual atmosphere that whisks you away to the left bank of the river Seine."], "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": ["A gentleman, maybe the manager, came to our table, and without so much as a smile or greeting asked for our order."], "output": "{'aspect_term': [['manager', 'negative'], ['table', '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": ["I really loved the different and inovated touch that's the cheff gives to the food."], "output": "{'aspect_term': [['cheff', '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 ambience is very calm and quiet."], "output": "{'aspect_term': [['ambience', '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 isn't your corner Chinese food takeout."], "output": "{'aspect_term': [['Chinese 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 cuisine from what I've gathered is authentic Taiwanese, though its very different from what I've been accustomed to in Taipei."], "output": "{'aspect_term': [['cuisine', '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": ["Wonderful strawberry daiquiries as well!"], "output": "{'aspect_term': [['strawberry daiquiries', '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 impressed with the food."], "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 place is larger than most and features adequate seating unlike most joints, and has a bar which deserves a mention."], "output": "{'aspect_term': [['seating', 'positive'], ['bar', 'positive'], ['place', '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": ["Ess-A-Bagel (either by Sty-town or midtown) is by far the best bagel in NY."], "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": ["I recommend this place to everyone who asks me where to go for a good 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": ["Considering their price of $6.25 for lunch special, the dish was ridiculously small."], "output": "{'aspect_term': [['price', 'negative'], ['dish', 'negative'], ['lunch special', '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 food was authentic."], "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 staff is excellent, specjal: that girl behind the bar, european chic."], "output": "{'aspect_term': [['staff', 'positive'], ['bar', '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 was impeccable and unobtrusive -- the staff knows what they are there to do -- to know their menu, present your meal, and attend to your needs."], "output": "{'aspect_term': [['service', 'positive'], ['staff', 'positive'], ['menu', 'neutral'], ['meal', '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": ["Try the Pad Thai, it's fabulous and their prices are so cheap!"], "output": "{'aspect_term': [['Pad Thai', '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": ["Their bagels are fine, but they are a little overcooked, and not really a 'special' bagel experience."], "output": "{'aspect_term': [['bagels', 'conflict'], ['bagel', '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": ["The waiters are sweet, the food is tasty and the bill is never too large."], "output": "{'aspect_term': [['waiters', 'positive'], ['food', 'positive'], ['bill', '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 page wine menu, one page entree and horedevous."], "output": "{'aspect_term': [['wine menu', 'positive'], ['entree', 'positive'], ['horedevous', '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": ["My chow fun and chow see was really bland and oily."], "output": "{'aspect_term': [['chow fun and chow see', '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 svc can be a bit rude at times, esp if you have big group, but overall the restaurant is a must!"], "output": "{'aspect_term': [['svc', '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": ["We could have made a meal of the yummy dumplings from the dumpling menu."], "output": "{'aspect_term': [['dumplings', 'positive'], ['meal', 'positive'], ['dumpling menu', '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 is the type of place to run into old friends and have a late, raucus 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": ["Decent wine selection too."], "output": "{'aspect_term': [['wine selection', '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": ["Sushi wasn't anything spectacular for the price."], "output": "{'aspect_term': [['Sushi', 'neutral'], ['price', '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": ["And the staff is also young, energeic and hot!!!!"], "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": ["Great selection of wine, and seafood."], "output": "{'aspect_term': [['selection of wine', 'positive'], ['seafood', '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 my co-workers were amazed at how small the dish was."], "output": "{'aspect_term': [['dish', '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": ["we were seated at the sushi bar in front of yasuda."], "output": "{'aspect_term': [['sushi bar', '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 drumsticks over rice and sour spicy soup in town!"], "output": "{'aspect_term': [['drumsticks over rice', 'positive'], ['sour spicy soup', '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": ["Best Italian food I ever had (and being Italian, that means alot)."], "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": ["The ambience was nice, but service wasn't so great."], "output": "{'aspect_term': [['ambience', '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": ["Yes, there might be a wait if you have no reservations."], "output": "{'aspect_term': [['wait', 'negative'], ['reservations', '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": ["I ordered the crab cocktail and it was soaked in a lime juice concoction where all you could taste was the lime."], "output": "{'aspect_term': [['crab cocktail', 'negative'], ['lime juice concoction', 'neutral'], ['lime', 'neutral']], 'aspect_category': [[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": ["Great pizza for lunch place."], "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 menu has lots of options: I hope to go back to try those potato pancakes."], "output": "{'aspect_term': [['menu', 'positive'], ['potato pancakes', '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 am a 100 lb girl, had a glass of wine and a glass of beer prior to the dinner, and I was still HUNGRY after my visit to this place!"], "output": "{'aspect_term': [['glass of wine', 'neutral'], ['glass of beer', 'neutral'], ['dinner', '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": ["My boyfriend ate tuna and it was cooked perfectly!"], "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": ["They even have a section in the menu called American Chinese food!"], "output": "{'aspect_term': [['menu', 'negative'], ['American Chinese 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": ["Shockingly easy to throw a group dinner here: simple contract, deposit only to hold the date the entire 2nd fl mezz for our grp of 20."], "output": "{'aspect_term': [['group 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": ["But, nothing stands out about the cooking."], "output": "{'aspect_term': [['cooking', '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 highly spiced chai tea was great too."], "output": "{'aspect_term': [['chai tea', '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 planning to get dessert but the waitress basically through the bill at us before we had a chance to order."], "output": "{'aspect_term': [['dessert', 'neutral'], ['waitress', 'negative'], ['bill', 'neutral']], 'aspect_category': [[None, 'neutral'], [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 flavors are great, and the menu is extensive."], "output": "{'aspect_term': [['flavors', '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": ["The service was bad, the food took to forever to come, we sat on the upper level."], "output": "{'aspect_term': [['service', '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": ["Eating in, the atmosphere saves it, but at your desk, it's a very disappointing experience."], "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": ["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 restaurant is a bit noisy but that is something that can be overlooked once you sit down and enjoy 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": ["This is the pinnacle of Indian Fast Food (all fast foods in my opinion)."], "output": "{'aspect_term': [['Indian Fast 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 is the best if you like thin crusted pizza."], "output": "{'aspect_term': [['pizza', 'positive'], ['thin crusted pizza', '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": ["It's just O.K. pizza."], "output": "{'aspect_term': [['pizza', '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": ["Good luck getting a table."], "output": "{'aspect_term': [['getting a 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": ["I have been a longtime fan of Holy Basil in the East Village, and while I do believe their food has slightly slipped in quality, I have been hesitant to be disloyal."], "output": "{'aspect_term': [['food', 'negative'], ['quality', '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": ["Overall the restaurant is more expensive than our other sushi favorites, but everything was delicious."], "output": "{'aspect_term': [['sushi', '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 waiters and owners were nonchalant about this and promised to call the exterminator but weren't as dismayed or apologetic as I would have expected."], "output": "{'aspect_term': [['waiters', 'negative'], ['owners', '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": ["Orsay, is without a doubt one of the best values for authentic French food in NYC."], "output": "{'aspect_term': [['French 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": ["It cannot be the ambience, because the place is very cramped and some guests have to sit in an aisle."], "output": "{'aspect_term': [['ambience', 'negative'], ['place', 'negative'], ['aisle', '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": ["Complimentary stuff kept coming, and when the waiter saw me opening a gift, I received my dessert on a plate that had Happy Birthday written on it, with a candlevery nice touch, and attentive staff."], "output": "{'aspect_term': [['stuff', 'positive'], ['waiter', 'positive'], ['dessert', 'positive'], ['staff', '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 service, however, was a bright flower in a garden."], "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": ["We had the most wonderful waitress."], "output": "{'aspect_term': [['waitress', '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 amazing, the service was so attentive and personable, and how about that ambience!"], "output": "{'aspect_term': [['food', 'positive'], ['service', 'positive'], ['ambience', '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": ["However, their popularity has yet to slow down, and I still find myself drawn to their ambiance and delectable reputation."], "output": "{'aspect_term': [['ambiance', '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 is extraordinary, yet not overbearing, and the decor brings a taste of trendy SoHo into Queens."], "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": ["The atmosphere is noisy and the waiters are literally walking around doing things as fast as they can."], "output": "{'aspect_term': [['atmosphere', 'negative'], ['waiters', '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": ["Quick and friendly 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": ["As soon as I wake up on a saturday or sunday it is the first thing on my mind is when and how I will be getting to fried dumpling."], "output": "{'aspect_term': [['fried dumpling', '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 pastas are fantastic and the homemade lasagna is some of the best that I have had in the City."], "output": "{'aspect_term': [['pastas', 'positive'], ['homemade lasagna', '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 worried we would have trouble getting in, but somehow managed to have a short wait."], "output": "{'aspect_term': [['wait', '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": ["She gets 10 for her excellent service and advice."], "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 food was well prepared and the service impecable."], "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": ["In terms of the food itself -- nothing special, we limited ourselves to several appetizers."], "output": "{'aspect_term': [['food', '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": ["After the main course came, we didn't see our waiter for at least 40 MINUTES!"], "output": "{'aspect_term': [['main course', 'neutral'], ['waiter', '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": ["I had the best ravioli ever."], "output": "{'aspect_term': [['ravioli', '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 fast to order the appetizer platter since we were very hungry."], "output": "{'aspect_term': [['appetizer platter', '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've had to wait only a few times during lunch but this place is definitely worth the wait."], "output": "{'aspect_term': [['lunch', 'neutral'], ['wait', '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": ["Great value for the quality ingredients."], "output": "{'aspect_term': [['ingredients', '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 lobster sandwich and it was FANTASTIC."], "output": "{'aspect_term': [['lobster 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": ["Service is highly refined: our seating was delayed 35 minutes past our reservation and the maitre d' apologized and regularly kept us apprised of progress."], "output": "{'aspect_term': [['Service', 'positive'], ['maitre', 'positive'], ['reservation', 'negative']], 'aspect_category': [[None, 'positive'], [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": ["On the other hand, if you are not fooled easily, you will find hundreds of restaurants that will give you service and ambiance that is on par with Alain Ducasse, and food that will outshine in presentaion, taste, choice, quality and quantity."], "output": "{'aspect_term': [['service', 'neutral'], ['ambiance', 'neutral'], ['food', 'negative'], ['presentaion', 'negative'], ['taste', 'negative'], ['choice', 'negative'], ['quality', 'negative'], ['quantity', 'negative']], 'aspect_category': [[None, 'neutral'], [None, 'neutral'], [None, 'negative'], [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": ["The portion sizes here are huge, and the sushi is good."], "output": "{'aspect_term': [['portion sizes', '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": ["Also, the sandwiches (nearing $7) didn't come with anything like chips or a side."], "output": "{'aspect_term': [['sandwiches', 'negative'], ['chips', 'neutral'], ['side', 'neutral']], 'aspect_category': [[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": ["Decor is nice and minimalist, food simple yet very well presented and cooked, and the wine list matches the food very well."], "output": "{'aspect_term': [['Decor', 'positive'], ['food', 'positive'], ['wine list', 'positive'], ['food', '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 place's decor and hidden bathrooms made for a good laugh."], "output": "{'aspect_term': [['decor', 'positive'], ['bathrooms', '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": ["He takes real pride in his food and his business."], "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 have to say I have never had a disapointing meal here."], "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": ["Lunch came with pickels and slaw, no extra charge."], "output": "{'aspect_term': [['Lunch', 'positive'], ['pickels and slaw', '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": ["Terrific menu full of unique rolls and special dishes."], "output": "{'aspect_term': [['menu', 'positive'], ['rolls', 'positive'], ['dishes', '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": ["There was no ambiance."], "output": "{'aspect_term': [['ambiance', '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 only friendly staff member was the guy at the bar."], "output": "{'aspect_term': [['staff member', 'positive'], ['bar', 'neutral'], ['guy', '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": ["Only wine and beer are served, but the house varities are actually quite good."], "output": "{'aspect_term': [['wine', 'neutral'], ['beer', 'neutral'], ['house varities', 'positive'], ['served', 'negative']], 'aspect_category': [[None, 'neutral'], [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": ["We got a little tipsy from the sake but isn't that what Saturday nights with the girlfriends are all about?"], "output": "{'aspect_term': [['sake', '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": ["not the food ,not the ambiance , not the service, I agree with the previous reviews you wait and wait , the wait staff are very rude and when you get in they are looking to get you right out ."], "output": "{'aspect_term': [['food', 'neutral'], ['ambiance', 'neutral'], ['service', 'neutral'], ['wait staff', 'negative']], 'aspect_category': [[None, 'neutral'], [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": ["The staff are attentive, and have smiles on their faces."], "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": ["Over time, the food quality has decreased substantially, it is a lot less crowded than it used to, and the service must definitely be part of the reason."], "output": "{'aspect_term': [['food quality', 'negative'], ['service', '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 takeout menu says to keep an eye out for an expanded menu offering more italian dishes, I can't wait!"], "output": "{'aspect_term': [['takeout menu', 'positive'], ['menu', 'positive'], ['italian dishes', '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": ["fine dining restaurant quality."], "output": "{'aspect_term': [['quality', '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 a go-to for dates as well as entertaining out of town guests."], "output": "{'aspect_term': [['entertaining', '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": ["Had a late night dinner on a Saturday night."], "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": ["Also, top the meal with a delicious and perfect slice of tiramisu."], "output": "{'aspect_term': [['tiramisu', 'positive'], ['meal', '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": ["After really enjoying ourselves at the bar we sat down at a table and had dinner."], "output": "{'aspect_term': [['bar', 'positive'], ['table', 'neutral'], ['dinner', 'neutral']], 'aspect_category': [[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 service was excellent and the food was delicious."], "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": ["Interesting other dishes for a change include chicken in curry sauce and salmon caserole."], "output": "{'aspect_term': [['dishes', 'positive'], ['chicken in curry sauce', 'positive'], ['salmon caserole', '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 never had Edamame pureed before but I thought it was innovative and tasty (could've used a bit more salt)."], "output": "{'aspect_term': [['Edamame pureed', '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": ["Right off the major deegan you get ladies from all over the city."], "output": "{'aspect_term': [['ladies', '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'm no food critic, but I'd like to think I have a tiny bit of experience under my belt having lived in NY for the last 11 years."], "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": ["As always we had a great glass of wine while we waited."], "output": "{'aspect_term': [['glass 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": ["20 minutes for our reservation but it gave us time to have a few cocktails and enjoy our surroundings and each other."], "output": "{'aspect_term': [['reservation', 'negative'], ['cocktails', 'positive'], ['surroundings', '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": ["Both times I was extremely dissappointed by the service, which was boarderline rude."], "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": ["Try the tandoori salmon!"], "output": "{'aspect_term': [['tandoori salmon', '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 octopus eaters were floored by the Octopus salad."], "output": "{'aspect_term': [['Octopus salad', '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 very good as well, considering that we tried the budget selection (though I wish the pork belly that I ordered was roasted a bit longer, so that fat was more of a melt-in-your-mouth experience)."], "output": "{'aspect_term': [['Food', 'positive'], ['pork belly', 'negative'], ['fat', 'negative']], 'aspect_category': [[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 place is a great stop for great 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": ["No food snobs allowed, this place is for people who appreciate good food."], "output": "{'aspect_term': [['food', 'neutral'], ['food', '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": ["This place must have cost the owners afortune to build."], "output": "{'aspect_term': [['owners', 'neutral'], ['cost', '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": ["Haru serves very fresh fish, has a trendy, modern ambiance, prime location on Park Avenue South and friendly service."], "output": "{'aspect_term': [['fish', 'positive'], ['service', 'positive'], ['ambiance', 'positive'], ['location', '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": ["After passing by this restaurant for sometime I finally decided to go in and have 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": ["Too bad the food wasn't of the same heritage."], "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": ["However, in the summer of 2003, it seems the management has changed and the great big door has been replaced for a glass front ridding itself of the dark romantic getup."], "output": "{'aspect_term': [['management', 'neutral'], ['door', 'positive'], ['glass front', '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": ["No free drink."], "output": "{'aspect_term': [['drink', '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": ["Edible but really a ripoff at those prices given whats in the area."], "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's a place for people who pay a lot for mediocre food, noise and a chance to be with their fellow bridge and tunnel folks."], "output": "{'aspect_term': [['food', 'neutral'], ['noise', '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": ["Worse of all, $60 was erroneously added to our $80 bill."], "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": ["A glass of Leaping Lizard, a glass of prosecco, and the mussels had everything happy."], "output": "{'aspect_term': [['glass of prosecco', 'positive'], ['mussels', 'positive'], ['glass of Leaping Lizard', '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 owner truly caters to all your needs."], "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": ["Otherwise, this place has great service and prices and a nice friendly atmosphere."], "output": "{'aspect_term': [['service', 'positive'], ['prices', 'positive'], ['atmosphere', '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": ["Two words: Free wine."], "output": "{'aspect_term': [['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": ["I complete the total bagel experience by having it lightly toasted."], "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": ["We were a group of 8 and well seved."], "output": "{'aspect_term': [['seved', '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 crust is thin, the ingredients are fresh and the staff is friendly."], "output": "{'aspect_term': [['crust', 'positive'], ['staff', 'positive'], ['ingredients', '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": ["You can get an excellent meal at most of the many Indian restaurants on nearby Lexington Avenue for the cost of one the dainty dishes here."], "output": "{'aspect_term': [['meal', 'positive'], ['cost', 'conflict'], ['dishes', 'positive']], 'aspect_category': [[None, 'positive'], [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": ["For dinner I had the chicken tikka-masala and some garlic naan."], "output": "{'aspect_term': [['chicken tikka-masala', 'neutral'], ['garlic naan', 'neutral'], ['dinner', '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 really good, I had the onion soup and it was one of the best ever."], "output": "{'aspect_term': [['food', 'positive'], ['onion soup', '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": ["It is about FOOD and Ambiance, and imagine how dreadful it will be it we only had to listen to an idle engine."], "output": "{'aspect_term': [['FOOD', 'negative'], ['Ambiance', '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 food, great prices, great service."], "output": "{'aspect_term': [['food', 'positive'], ['prices', '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 list is extensive and impressive."], "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": ["Although be warned their dinner menu to sit and take out prices are different."], "output": "{'aspect_term': [['prices', 'neutral'], ['dinner menu to sit', 'neutral'], ['take out', '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 just OK, at least for what food was available."], "output": "{'aspect_term': [['food', 'neutral'], ['food', '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": ["I've eaten thai many times, and am very familiar with the cuisine."], "output": "{'aspect_term': [['cuisine', '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 dim sum is delectable while the prices are quite easy on the wallet."], "output": "{'aspect_term': [['dim sum', '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": ["Metrazur has a beautiful spot overlooking the main terminal."], "output": "{'aspect_term': [['spot', '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 I lived upstate for a while I would buy freeze the bagels and they would still be better than any else."], "output": "{'aspect_term': [['bagels', '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": ["Fresh ingredients and everything is made to order."], "output": "{'aspect_term': [['ingredients', '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": ["Ambiance and music funky, which I enjoy."], "output": "{'aspect_term': [['Ambiance', '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": ["The price very reasonable."], "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 would like to return and try some of the other menu items when I don't have to rush off to a show."], "output": "{'aspect_term': [['menu items', '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": ["Even though I made the reservation at 3pm for the same night through Dinnerbroker, we were seated at a table with one of the best view!"], "output": "{'aspect_term': [['table', 'positive'], ['reservation', 'positive'], ['seated', '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've had the chicken with garlic sauce, chicken with black bean sauce, and hunan chicken."], "output": "{'aspect_term': [['chicken with garlic sauce', 'neutral'], ['chicken with black bean sauce', 'neutral'], ['hunan chicken', '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 red curry is weak and tasteless, the pad thai is stuck together and lumpy, the rice is often overcooked, and the seafood is pretty sketchy."], "output": "{'aspect_term': [['red curry', 'negative'], ['pad thai', 'negative'], ['rice', 'negative'], ['seafood', 'negative']], 'aspect_category': [[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": ["Volare virgins or weekly regulars, everyone gets treated the same and you can't ask for more than that when the service is this friendly."], "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 bagels are also reasonably priced for NYC."], "output": "{'aspect_term': [['bagels', 'positive'], ['priced', '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 only thing the waiters don't do for you is wipe your chin when you leave."], "output": "{'aspect_term': [['waiters', '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 tiny table for two (dinner plates hung over edge) was right in the middle of one of the lanes of waiter traffic."], "output": "{'aspect_term': [['table', 'negative'], ['waiter traffic', 'negative'], ['dinner plates', '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": ["Oh yes, and if you are a fan of Indian oldies film stars, there are plenty of portraits of Indian actors and actresses in classic black white that adorn the walls, some of which, I would love to know where they obtained."], "output": "{'aspect_term': [['portraits', '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": ["Although the tables may be closely situated, the candle-light, food-quality and service overcompensate."], "output": "{'aspect_term': [['candle-light', 'positive'], ['food-quality', 'positive'], ['service', 'positive'], ['tables', 'negative']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [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": ["Try the sea bass."], "output": "{'aspect_term': [['sea bass', '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": ["Apparently, the good cook works then."], "output": "{'aspect_term': [['cook', '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 back garden sitting area is very pleasant, where you can see their personal herb garden."], "output": "{'aspect_term': [['back garden sitting area', 'positive'], ['personal herb garden', '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": ["So if you want a nice, enjoyable meal at Montparnasse, go early for the pre-theater prix-fixe."], "output": "{'aspect_term': [['meal', 'positive'], ['pre-theater prix-fixe', '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 excellent, the decor is great, and the food is delicious and comes in large portions."], "output": "{'aspect_term': [['service', 'positive'], ['decor', 'positive'], ['food', 'positive'], ['portions', '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": ["Until you realize that their five minutes is meaningless and your wait may be anywhere from two to twenty minutes it may be frustrating."], "output": "{'aspect_term': [['wait', '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": ["Just bring someone who speaks Cantonese because waiter may not understand you."], "output": "{'aspect_term': [['waiter', '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 cheesecake!"], "output": "{'aspect_term': [['cheesecake', '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 Taiwanese food in NY!"], "output": "{'aspect_term': [['Taiwanese 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": ["Unique apppetizers."], "output": "{'aspect_term': [['apppetizers', '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 all had the tasting menu and unlike some of the other reviews, I felt there was more than enough food."], "output": "{'aspect_term': [['menu', '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 bar has various selections and the mixed drink special is a catcher! 2 for 1's."], "output": "{'aspect_term': [['bar', 'positive'], ['mixed drink 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": ["I was very impressed by this low-key upper eastsider and their authentically thai cuisine!!!"], "output": "{'aspect_term': [['thai cuisine', '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": ["Tried the pad see ew on the recommendation of the last reviewer since it's one of my favorite dishes."], "output": "{'aspect_term': [['pad see ew', 'neutral'], ['dishes', '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": ["We ended our great experience by having Gulab Jamun (dessert) recommended by the waiter."], "output": "{'aspect_term': [['Gulab Jamun (dessert)', 'positive'], ['waiter', '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": ["It took them 15 minutes to put water in our glasses."], "output": "{'aspect_term': [['water', '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": ["Good bagels and good cream cheese."], "output": "{'aspect_term': [['bagels', 'positive'], ['cream cheese', '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 moment we walked in they were more than accomodating even though the place was packed."], "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 food was pretty good, but a little flavorless and the portions very small, including dessert."], "output": "{'aspect_term': [['food', 'conflict'], ['dessert', 'negative'], ['portions', 'negative']], 'aspect_category': [[None, 'conflict'], [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 are in a big group, this place is perfect because it recomends sharing - they have lazy susans on most tables - even families can feel comfortable here."], "output": "{'aspect_term': [['lazy susans', 'positive'], ['tables', '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": ["Ummm...the beer was cold."], "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": ["Highly recommend this as great value for excellent sushi and service."], "output": "{'aspect_term': [['sushi', 'positive'], ['service', 'positive'], ['value', '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 wait here is long for dim sum, but if you don't like sharing tables or if the typical raucous dim sum atmosphere is not your gig, this is a sleek (for Chinatown) alternative."], "output": "{'aspect_term': [['wait', 'negative'], ['dim sum', 'neutral'], ['dim sum atmosphere', 'neutral'], ['tables', 'positive']], 'aspect_category': [[None, 'negative'], [None, 'neutral'], [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 seats are uncomfortable if you are sitting against the wall on wooden benches."], "output": "{'aspect_term': [['seats', '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 only tried a simple dish of spinach ravioli in a light oil and garlic sauce, but it actually faired better than most NYC Italian joints I've tried similar dishes at."], "output": "{'aspect_term': [['spinach ravioli in a light oil and garlic sauce', 'positive'], ['dish', 'positive'], ['dishes', '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": ["Very affordable and excellent ambient!"], "output": "{'aspect_term': [['ambient', '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 last two times I ordered from here my food was soo spicy that  I could barely eat it, and the spice took away from the flavor of the dish."], "output": "{'aspect_term': [['food', 'negative'], ['flavor', 'negative'], ['dish', 'negative'], ['spice', 'negative']], 'aspect_category': [[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 tired and cold when we got to the restaurant, then we sat down to begin ordering appetizers."], "output": "{'aspect_term': [['appetizers', '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 is 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": ["The food is very good for it's price, better than most fried dumplings I've had."], "output": "{'aspect_term': [['food', 'positive'], ['price', 'positive'], ['fried dumplings', 'negative']], 'aspect_category': [[None, 'positive'], [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 is good, especially their more basic dishes, and the drinks are delicious."], "output": "{'aspect_term': [['food', 'positive'], ['dishes', 'positive'], ['drinks', '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 food was spicy and 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 recommend the thai popcorn :)"], "output": "{'aspect_term': [['thai popcorn', '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 average and the prices are anything but."], "output": "{'aspect_term': [['sushi', 'neutral'], ['prices', '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": ["Very good service and very good prices."], "output": "{'aspect_term': [['service', '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 is inventive but still keeps traditional indian flavoring."], "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": ["We visited Orsay during NY Restaurant Week and tried their $35 menu."], "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": ["An excellent alternative to fast food joints and ordering in but, the food was slightly disappointing."], "output": "{'aspect_term': [['fast food', '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": ["If the omakase is to showcase technique and variety, serving almost 40% of items BBQ-ed and a spicy tuna roll wrapped with not-so-fresh nori seems to be a rather limp performance."], "output": "{'aspect_term': [['spicy tuna roll', 'negative'], ['serving', 'neutral'], ['nori', '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": ["Don't eat here unless you're starving for thai food and you work next door."], "output": "{'aspect_term': [['thai 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": ["We didn't get drink refills and she didn't even offer us the option of dessert."], "output": "{'aspect_term': [['drink refills', 'negative'], ['dessert', '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": ["We arrived on time for our reservation and seated promptly.The"], "output": "{'aspect_term': [['reservation', '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": ["Again, the waitress was awesome."], "output": "{'aspect_term': [['waitress', '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 small wait, but shorter than I expected."], "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": ["I do not recommend lunch specials just because it tasts the same with other regular chinese restaurant."], "output": "{'aspect_term': [['lunch specials', '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 turkey burger was not cooked at all, my friends salmon was completely raw."], "output": "{'aspect_term': [['turkey burger', 'negative'], ['salmon', '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": ["This is one of the best comfort food places in the city."], "output": "{'aspect_term': [['comfort 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": ["Very romantic fires - I've literally spent hours at Lanterna, drinking wine from their extensive wine and enjoying the ambience."], "output": "{'aspect_term': [['wine', 'positive'], ['ambience', 'positive'], ['wine', '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": ["Pizza is terrific, as is homemade pasta."], "output": "{'aspect_term': [['Pizza', 'positive'], ['homemade pasta', '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 care more about the food and ambience."], "output": "{'aspect_term': [['food', 'neutral'], ['ambience', '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": ["You rarely have to wait for a seat and the currys (masaman, green, red) are full of flavor and come super spicy if you ask for it."], "output": "{'aspect_term': [['seat', 'positive'], ['currys (masaman, green, red)', 'positive'], ['flavor', '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": ["We ordered the special, grilled branzino, that was so infused with bone, it was difficult to eat."], "output": "{'aspect_term': [['grilled branzino', '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 charge different prices all the time."], "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": ["Though the Spider Roll may look like a challenge to eat, with soft shell crab hanging out of the roll, it is well worth the price you pay for them."], "output": "{'aspect_term': [['Spider Roll', 'conflict'], ['price', 'positive'], ['shell crab', 'positive']], 'aspect_category': [[None, 'conflict'], [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": ["A very inviting restaurant, with friendly 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": ["Chance is a small cozy restaurant, with a romantic feel to it, the decor is great."], "output": "{'aspect_term': [['decor', '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 very attentive and we can almost always get a table."], "output": "{'aspect_term': [['staff', '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": ["The food is good, but very expensive for the casualness of it."], "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": ["If the weather is nice, try to snag an outside table."], "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": ["So, for good food i'd recommend it, but not for a fun night out."], "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 slow had to wait to order and get food although not crowded."], "output": "{'aspect_term': [['Service', 'negative'], ['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 o.k., but not any better than what you get at a good neighborhood restaurant."], "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": ["For some reason, all the seafood on the menu was unavailable except for the Salmon."], "output": "{'aspect_term': [['seafood', 'negative'], ['menu', 'negative'], ['Salmon', 'neutral']], 'aspect_category': [[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": ["The service was terrible, we had to wait for everything and ask several of different people for the same thing before we were allowed to be served."], "output": "{'aspect_term': [['service', 'negative'], ['served', '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 staff was accomodating, the food was absolutely delicious and the place is lovely."], "output": "{'aspect_term': [['staff', 'positive'], ['food', 'positive'], ['place', '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": ["Have the iced tea."], "output": "{'aspect_term': [['iced tea', '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 Cafe Noir dont get me wrong, it is jsut that the people who work there are evil and incompetent!!"], "output": "{'aspect_term': [['people', '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": ["Have always found that the waiters will go out of their way to be helpful, despite the fact they are often busy with lots of diners."], "output": "{'aspect_term': [['waiters', 'positive'], ['diners', '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 place has the best Chinese style BBQ ribs in the city."], "output": "{'aspect_term': [['BBQ ribs', '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": ["Overall, not worth the money."], "output": "{'aspect_term': [['money', '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": ["Overall a disappointing experience for that price category."], "output": "{'aspect_term': [['price', '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": ["from an English speaking staff."], "output": "{'aspect_term': [['staff', '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 main course had an average portion, and was decent overall."], "output": "{'aspect_term': [['main course', 'positive'], ['portion', '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": ["We arrived for dinner expecting to be impressed by a place that has an impressive past - but, that's just it -- the PAST!"], "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": ["We only ordered desserts and drinks, but no refills were offered."], "output": "{'aspect_term': [['desserts', 'neutral'], ['drinks', '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": ["Oh, and the complimentary pudding dessert was just enough- yummy!"], "output": "{'aspect_term': [['pudding dessert', '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": ["Solid wine list, knowledgeable staff, friendly owners and an adventurous, ever-changing menu keep us coming back."], "output": "{'aspect_term': [['wine list', 'positive'], ['staff', 'positive'], ['owners', 'positive'], ['menu', '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 people that work there are always so friendly you forget you are in New York sometimes."], "output": "{'aspect_term': [['people', '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 good and the view of the new york city skiline was terrific even on a foggy rainy day like that of when I went."], "output": "{'aspect_term': [['Food', '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": ["We had a wonderful meal at Naples 45 a month ago on a visit to NYC."], "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 sake menu should not be overlooked!"], "output": "{'aspect_term': [['sake 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": ["Every waitress and customer who passed by me bumped into my chair."], "output": "{'aspect_term': [['waitress', '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": ["After complaining about the chicken dish, the manager came over to tell us that, no one had ever complained before, and that we just didn't know what the dish was supposed to taste like."], "output": "{'aspect_term': [['chicken dish', 'negative'], ['manager', 'negative'], ['dish', 'neutral']], 'aspect_category': [[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": ["Their pad penang is delicious and everything else is fantastic."], "output": "{'aspect_term': [['pad penang', '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 found it on a cold night, the perfect spot to warm up."], "output": "{'aspect_term': [['spot', '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 didn't give us the dinner special until we asked for it."], "output": "{'aspect_term': [['dinner special', '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've rarely had a problem with slow staff in the 10 years I've been going."], "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": ["They're also friendlier here, especially the owner, Kenny."], "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": ["We, there were four of us, arrived at noon - the place was empty - and the staff acted like we were imposing on them and they were very rude."], "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 really recommend the very simple Unda (Egg) rolls."], "output": "{'aspect_term': [['Unda (Egg) 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": ["You should pass on the calamari."], "output": "{'aspect_term': [['calamari', '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 work near-by, and they have the BEST oatmeal in the neighborhood- not a packaged or quick-cooked item."], "output": "{'aspect_term': [['oatmeal', '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 white bean brushetta to start was incredible and the pasta was phenomenal."], "output": "{'aspect_term': [['white bean brushetta', 'positive'], ['pasta', '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": ["This place is always very crowded and popular."], "output": "{'aspect_term': [['place', '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 can't wait for summer, when they serve outside on their gigantic patio."], "output": "{'aspect_term': [['patio', '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 one asked what was wrong as we left with nothing touched on our plates."], "output": "{'aspect_term': [['plates', '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": ["We also had shared a house salad that was fresh."], "output": "{'aspect_term': [['house salad', '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 waiters were not attentive except that the bill turned up on the table before we were finished."], "output": "{'aspect_term': [['waiters', 'negative'], ['bill', '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": ["I grew up eating Dosa and have yet to find a place in NY to satisfy my taste buds."], "output": "{'aspect_term': [['Dosa', '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 waitress, seems to be more concerned of looking good than actually waitressing."], "output": "{'aspect_term': [['waitress', '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": ["Please if your thinking about it go, and stay the wait you won't be disappointed."], "output": "{'aspect_term': [['wait', '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": ["We were disappointed with the pre-fixe menu of only 2 choices per course (other restaurants offer 3 choices) and ended up ordering a la carte."], "output": "{'aspect_term': [['pre-fixe menu', 'negative'], ['choices per course', 'neutral'], ['ordering a la carte', '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": ["My first time there I happened not to like the Crab Croquette apt that i ordered and they were happy to change it for me without making no big deal."], "output": "{'aspect_term': [['Crab Croquette apt', '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- relaxed and stylish."], "output": "{'aspect_term': [['Ambiance', '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 is limited but almost all of the dishes are excellent."], "output": "{'aspect_term': [['menu', 'negative'], ['dishes', '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": ["Butter was melted, white wine warm, cheese oozing everywhere."], "output": "{'aspect_term': [['Butter', 'negative'], ['white wine', 'negative'], ['cheese', '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": ["Three courses - choices include excellent mussels, puff pastry goat cheese and salad with a delicious dressing, and a hanger steak au poivre that is out of this world."], "output": "{'aspect_term': [['mussels', 'positive'], ['puff pastry goat cheese', 'positive'], ['salad with a delicious dressing', 'positive'], ['hanger steak au poivre', 'positive'], ['courses', 'neutral']], 'aspect_category': [[None, 'positive'], [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": ["And forget what you read under me, the atmosphere isn't that bad either."], "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": ["I ordered the chu chu curry and my friend ordered the pad thai chicken."], "output": "{'aspect_term': [['chu chu curry', 'neutral'], ['pad thai chicken', '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": ["It is obvious that no one in the restaurant has any idea about or experience with Japanese cuisine."], "output": "{'aspect_term': [['Japanese cuisine', '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 did not have mayonnaise, forgot our toast, left out ingredients (ie cheese in an omelet), below hot temperatures and the bacon was so over cooked it crumbled on the plate when you touched it."], "output": "{'aspect_term': [['toast', 'negative'], ['mayonnaise', 'negative'], ['bacon', 'negative'], ['cheese', 'neutral'], ['ingredients', 'negative'], ['plate', 'neutral'], ['omelet', 'neutral']], 'aspect_category': [[None, 'negative'], [None, 'negative'], [None, 'negative'], [None, 'neutral'], [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": ["If you go for the pre-theatre menu, it's an even greater deal."], "output": "{'aspect_term': [['pre-theatre 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": ["From beginning appetizers, the scallops were incredible, to the delicious chocolate souffle with rasberry mint sorbet, we were delighted by the taste sensations."], "output": "{'aspect_term': [['beginning appetizers', 'positive'], ['scallops', 'positive'], ['chocolate souffle with rasberry mint sorbet', 'positive'], ['taste', '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": ["My goodness, everything from the fish to the rice to the seaweed was absolutely amazing."], "output": "{'aspect_term': [['fish', 'positive'], ['rice', 'positive'], ['seaweed', '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": ["Deep Fried Skewers are good and still rare to find in NYC."], "output": "{'aspect_term': [['Deep Fried Skewers', '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 bar, most gorgeous bartenders you've ever seen (specifically the blond lady)."], "output": "{'aspect_term': [['bar', 'positive'], ['bartenders', '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 people in the restaurant were pretty obnoxious and loud."], "output": "{'aspect_term': [['people', '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 family and I ate here last night for our annual Christmas dinner with the family members who would rather spend the holidays with friends out-of-town."], "output": "{'aspect_term': [['Christmas 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": ["Southern Indian cuisine is still there, too."], "output": "{'aspect_term': [['Southern Indian cuisine', '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 prices were CHEAP compared to the quality of service and food."], "output": "{'aspect_term': [['prices', '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": ["Behind this counter, two men are squeezed in."], "output": "{'aspect_term': [['counter', '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 your visiting, you'll enjoy the ambiance and the fact that it's in Time Sq..."], "output": "{'aspect_term': [['ambiance', '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, atlhough tables opened up next to us and we ASKED for a slightly larger space, they left us awkardly seated."], "output": "{'aspect_term': [['tables', 'neutral'], ['space', '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": ["Unlike HH up the block, this place actually gives you hearty and hot bagels this town is known for."], "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": ["I am not sure if I would call the food here Indian as it is a fusion of what seems to be French with an Indian or exotic touch."], "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 food is tasty and portion sizes are appropriate."], "output": "{'aspect_term': [['food', 'positive'], ['portion sizes', '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": ["Cheese plate is a varied delight and great bargain at $10."], "output": "{'aspect_term': [['Cheese 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": ["Their wines by the glass are a great accompaniment and you can eat like a king with wine for under $30."], "output": "{'aspect_term': [['wines by the glass', 'positive'], ['wine', '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 decor is nice, but more casual than fine dining."], "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": ["Not a large place, but it's cute and cozy."], "output": "{'aspect_term': [['place', '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": ["But the thing that my wife and I hated was it was so loud and it felt like 'bar' or 'pub'."], "output": "{'aspect_term': [['bar', 'negative'], ['pub', '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": ["I almost wanted to write a bad review, so no one would ever go here and I could have all the dumplings to myself!"], "output": "{'aspect_term': [['dumplings', '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 are someone who appreciates the same things but hope to have food to spare or share, Kai may not be the best option."], "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": ["Furthermore, the rice had no seasoning, so the sushi was bland and disgusting."], "output": "{'aspect_term': [['rice', 'negative'], ['sushi', 'negative'], ['seasoning', '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": ["A bit breezy up there on the mezzanine from the wind coming from the tracks."], "output": "{'aspect_term': [['mezzanine', '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": ["Normally that would be improper, however they were all delicious and my host did not complain."], "output": "{'aspect_term': [['host', '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": ["Most of the servers are very attentive, friendly and quite attractive."], "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": ["I really like both the scallops and the mahi mahi (on saffron risotto-yum!)."], "output": "{'aspect_term': [['scallops', 'positive'], ['mahi mahi (on saffron risotto', '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 menu seemed to have a wide variety of dishes for seafood lovers and interesting ways of preparing them."], "output": "{'aspect_term': [['menu', 'positive'], ['variety of dishes', 'positive'], ['seafood', '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 staff was knowledgeable and full of personality."], "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": ["Our waitress was sweet and accomodating, not overbearing."], "output": "{'aspect_term': [['waitress', '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": ["Similar to other Indian restaurants, they use the dinner special to attract customers at the door."], "output": "{'aspect_term': [['dinner 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": ["If you love wine and cheese and delicious french fare, you'll love Artisanal!"], "output": "{'aspect_term': [['wine', 'positive'], ['french fare', 'positive'], ['cheese', '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": ["Maybe I say so because it looked promising for people who like artery-clogging jewish deli food, but turns out to be poorly run and awful."], "output": "{'aspect_term': [['jewish deli 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": ["But the best part about LS is the late night atmosphere, delightfully free of the BTs."], "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": ["Prices are in line."], "output": "{'aspect_term': [['Prices', '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 staff was too busy ordering sushi for dinner and then laying it out to eat on the bar to even bring me my check."], "output": "{'aspect_term': [['staff', 'negative'], ['sushi', 'neutral'], ['check', 'neutral'], ['dinner', 'neutral'], ['bar', 'neutral']], 'aspect_category': [[None, 'negative'], [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": ["Plus, on Wednesday nights the house wine is unlimited!"], "output": "{'aspect_term': [['house 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": ["This is one great place to eat pizza more out but not a good place for take-out pizza."], "output": "{'aspect_term': [['pizza', 'positive'], ['take-out pizza', '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": ["No refills on fountain drinks, though."], "output": "{'aspect_term': [['fountain 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": ["Do not get the Go Go Hamburgers, no matter what the reviews say."], "output": "{'aspect_term': [['Go Go Hamburgers', '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 burger was great, also."], "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": ["brick oven gallery is My pick for best pizza restaurant anywhere."], "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 best thing I tasted were the lambchops."], "output": "{'aspect_term': [['lambchops', '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 moment you enter till the moment you walk out the friendly and helpful staff was was just Fantastic."], "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 space is a bit too small for live music, so on  jazz nights, it can be loud and cramped."], "output": "{'aspect_term': [['live music', 'neutral'], ['space', 'negative'], ['jazz nights', 'neutral']], 'aspect_category': [[None, 'neutral'], [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": ["By far this is the only chinese desserts place I know in NY or anywhere close in the Northeastern America that serves desserts with frog jelly in a couple of varieties and pig feet ginger simmered in black vinegar."], "output": "{'aspect_term': [['pig feet ginger simmered in black vinegar', 'positive'], ['desserts with frog jelly', '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": ["Traditional French decour was pleasant though the hall was rather noisy - the restaurant was full and we had to raise our voices to be able to maintain a conversation."], "output": "{'aspect_term': [['Traditional French decour', 'positive'], ['hall', '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": ["Great food, good size menu, great service and an unpretensious setting."], "output": "{'aspect_term': [['food', 'positive'], ['menu', 'positive'], ['service', 'positive'], ['setting', '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": ["Tell them Herky sent you and get a free confused look from the waiter."], "output": "{'aspect_term': [['waiter', '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 recommend the jelly fish, drunken chicken and the soupy dumplings, certainly the stir fry blue crab."], "output": "{'aspect_term': [['jelly fish', 'positive'], ['drunken chicken', 'positive'], ['soupy dumplings', 'positive'], ['stir fry blue crab', '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 tables are crammed way too close, the menu is typical of any Italian restaurant, and the wine list is simply overpriced."], "output": "{'aspect_term': [['tables', 'negative'], ['menu', 'neutral'], ['wine list', '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": ["Okay service."], "output": "{'aspect_term': [['service', '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": ["We didn't even see a menu, as our waiter described both the specials and the main dishes."], "output": "{'aspect_term': [['menu', 'neutral'], ['main dishes', 'neutral'], ['waiter', 'positive'], ['specials', 'neutral']], 'aspect_category': [[None, 'neutral'], [None, 'neutral'], [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 the perfect date spot for Williamsburg couples."], "output": "{'aspect_term': [['date spot', '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 started with lox and mussels (the best ive ever had, ever) and had the cod and trout for dinner."], "output": "{'aspect_term': [['lox', 'positive'], ['mussels', 'positive'], ['cod', 'neutral'], ['trout', 'neutral'], ['dinner', 'neutral']], 'aspect_category': [[None, 'positive'], [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": ["But the thai is definitely not great -- bland and indistinguished."], "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": ["Cute place, nice wait staff but would never go there again."], "output": "{'aspect_term': [['wait staff', '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": ["What generous portions!"], "output": "{'aspect_term': [['portions', '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 delicious, the atmosphere was relaxed, and we have now adopted Plate 347 as our Secret on Second!"], "output": "{'aspect_term': [['food', 'positive'], ['atmosphere', '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 had a terrific meal, and our server guided us toward a very nice wine in our price range, instead of allowing us to purchase a similarly priced wine that wasn't as good."], "output": "{'aspect_term': [['meal', 'positive'], ['server', 'positive'], ['wine', 'positive'], ['wine', 'negative'], ['price range', 'positive'], ['priced', 'neutral']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [None, 'positive'], [None, 'negative'], [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 staff is very kind and well trained, they're fast, they are always prompt to jump behind the bar and fix drinks, they know details of every item in the menu and make excelent recomendations."], "output": "{'aspect_term': [['staff', 'positive'], ['bar', 'neutral'], ['drinks', 'neutral'], ['menu', '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 ambience is very romantic and definitely a good place to bring a date."], "output": "{'aspect_term': [['ambience', '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 decided to eat in tea room which was small and cute."], "output": "{'aspect_term': [['tea room', '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 wine the service was very good too."], "output": "{'aspect_term': [['wine', '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 had to ask her three times before she finally came back with the dish Ive requested."], "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": ["Service could be improved but overall this is a place that understands the importance of little things (the heavy, black, antique-seeming teapot, for one) in the restaurant experience."], "output": "{'aspect_term': [['Service', 'negative'], ['teapot', '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": ["Having discovered Ping's on the internet, we entered with qualms but were instantly put to ease by the fish tanks that greet you as u walk in."], "output": "{'aspect_term': [['fish tanks', '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 black cod with yuzu sauce, which was wonderful."], "output": "{'aspect_term': [['black cod with yuzu sauce', '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 usually go there later at night when I get off work so I don't have to deal with crowds or lines."], "output": "{'aspect_term': [['lines', 'negative'], ['crowds', '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 restaurant is rather small but we were lucky to get a table quickly."], "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": ["We had champagne and caviar and felt like princesses!"], "output": "{'aspect_term': [['champagne', 'positive'], ['caviar', '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 went here for lunch a couple of weeks ago on a Saturday, and I was thoroughly impressed with the food."], "output": "{'aspect_term': [['lunch', 'neutral'], ['food', '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": ["Just don't take the seat between the bar and the back half of the restaurant, i saw a woman get nudged 40times sitting there."], "output": "{'aspect_term': [['seat', '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": ["Oh, don't even let me start with how expensive the bills were!"], "output": "{'aspect_term': [['bills', '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 lousy - too sweet or too salty and the portions tiny."], "output": "{'aspect_term': [['food', 'negative'], ['portions', '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": ["Scalina Fedeli reminded me why service is so integral to fine dining."], "output": "{'aspect_term': [['service', 'positive'], ['dining', '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 Pastrami sandwich was like buttah and with pickles and an icy cold beer to wash it down, it was a pleasurable experience."], "output": "{'aspect_term': [['Pastrami sandwich', 'positive'], ['beer', 'positive'], ['pickles', '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": ["Food was good not great not worth the wait or another visit"], "output": "{'aspect_term': [['Food', 'conflict'], ['wait', '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": ["If you like the food and the value you get from some of Chinatown restaurants, this is not the place for you."], "output": "{'aspect_term': [['food', 'neutral'], ['value', '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": ["sometimes i get good food and ok service."], "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": ["Were meeting up with some friends for a drink at Lafayette 161 and happened to walk by Thai Angel famished."], "output": "{'aspect_term': [['drink', '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 like the ambience, it's very dark and original."], "output": "{'aspect_term': [['ambience', '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 dosas are skimpy, unattractive and drip with grease, and personally I'd drink popcorn topping before I'd eat another one of these."], "output": "{'aspect_term': [['dosas', 'negative'], ['popcorn topping', '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": ["Waitstaff are very friendly."], "output": "{'aspect_term': [['Waitstaff', '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 no excuse for such lousy service!"], "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": ["Salads were fantastic."], "output": "{'aspect_term': [['Salads', '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 spicy wontons and the salt pepper shrimps."], "output": "{'aspect_term': [['spicy wontons', 'positive'], ['salt pepper shrimps', '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": ["This is the perfect spot for meeting friends, having lunch, dinner, pre-theatre or after-theatre drinks!"], "output": "{'aspect_term': [['lunch', 'positive'], ['dinner', 'positive'], ['pre-theatre or after-theatre drinks', 'positive'], ['spot', '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 lunch special is an asbolute steal."], "output": "{'aspect_term': [['lunch 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": ["I'd highly recommend it for a special occasion -- it provides and intimate setting and nice service."], "output": "{'aspect_term': [['setting', '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 highlight of the night was the mayonaisse for my side of fries I received from one of the food runners, which is not good considering the bill was nearly $100."], "output": "{'aspect_term': [['mayonaisse', 'negative'], ['food runners', 'neutral'], ['bill', 'negative'], ['fries', '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": ["Has the chef and owner changed???"], "output": "{'aspect_term': [['chef', 'neutral'], ['owner', '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 mediocre at best but it was the horrible service that made me vow never to go back."], "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": ["Perhaps this food is considered extreme to an Upper East Side resident, but for the rest of us who've actually eaten ethnic food, this is simply dull."], "output": "{'aspect_term': [['food', 'conflict'], ['ethnic food', '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": ["The combination of fresh tomato sauce, fresh mozz cheese, basil and the dough they make with imported flour, makes this is one of the better pizza's in NY."], "output": "{'aspect_term': [['fresh tomato sauce', 'positive'], ['fresh mozz cheese', 'positive'], ['basil', 'positive'], ['dough', 'positive'], ['pizza', 'positive'], ['flour', '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": ["You will pay a lot for the decore, but the food is no better or worse than a lot of other Chinese and Asian fusion places in NY."], "output": "{'aspect_term': [['decore', 'negative'], ['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": ["And really large portions."], "output": "{'aspect_term': [['portions', '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 cannot imagine better Indian food in all of the city."], "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": ["Lucky Strike is a great casual place to just grab a bite to eat."], "output": "{'aspect_term': [['place', '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'd like to have a nice light meal with an asian accent, Long Tan is a good place on the slope."], "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": ["Service was warm and attentive, beef carpaachio was exellent (huge portion) and pasta was fresh and well-prepared."], "output": "{'aspect_term': [['Service', 'positive'], ['beef carpaachio', 'positive'], ['pasta', 'positive'], ['portion', '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": ["Only complaint would be that at an average cost of $12-$15 per meal, I'd like not to have to worry about finding a seat!"], "output": "{'aspect_term': [['cost', 'negative'], ['meal', 'neutral'], ['seat', '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 man that was hosting promised to save a table for our party of 7, then sat a party of 2 at the very table he was saving (mean while there were boths open all around)."], "output": "{'aspect_term': [['man', 'negative'], ['table', 'neutral'], ['table', '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 a great Thai restaurant with a very friendly staff."], "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": ["I was here a few weeks back and we had the worst customer service experience at a restaurant ever."], "output": "{'aspect_term': [['customer 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": ["The table service could have been a little more attentive but as someone who also works in the service industry, I understood they were busy."], "output": "{'aspect_term': [['table service', 'conflict'], ['service', '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": ["Be careful of portions - they're HUGE."], "output": "{'aspect_term': [['portions', '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": ["People are always friendly."], "output": "{'aspect_term': [['People', '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 enough wines by the glass either."], "output": "{'aspect_term': [['wines by the glass', '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 visiting this restaurant and having dinner and drinks!"], "output": "{'aspect_term': [['dinner', 'positive'], ['drinks', '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": ["In fact, while leaving the place we saw two people looking at the menu, and I couldn't help telling them that the food was horrible."], "output": "{'aspect_term': [['food', 'negative'], ['menu', '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": ["This was my frist time at Cafe St. Bart's and I must say how delicous the food and the service was."], "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": ["DO not try unless you're just going there to hang out like the rest of the hipsters who apparently have no sense of taste."], "output": "{'aspect_term': [['taste', '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 music is the best among all the Indian restaurants I have visited."], "output": "{'aspect_term': [['music', '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 love and I know gourmet food by excellence!"], "output": "{'aspect_term': [['gourmet 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 boyfriend had the New England Chowder it was good but I think the award should go to the Lobster Bisque."], "output": "{'aspect_term': [['New England Chowder', 'positive'], ['Lobster Bisque', '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": ["It can be a little confusing as to where one goes to order, but once the food is ordered, you are in for a treat."], "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": ["- for dessert we split chocolate cake and vanilla gelato (with espresso), which were tasty, but I thought a bit overpriced."], "output": "{'aspect_term': [['chocolate cake', 'conflict'], ['vanilla gelato (with espresso)', 'conflict'], ['dessert', '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": ["Joe's Pizza used to have the best slice until this pizzeria opened up."], "output": "{'aspect_term': [['slice', '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 bartender on my most recent visit was so incredibly rude that I will never go back."], "output": "{'aspect_term': [['bartender', '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": ["love 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": ["We ordered some beef and noodle soup dishes from the Thai section of the menu but nothing we got was Thai."], "output": "{'aspect_term': [['beef', 'negative'], ['noodle soup dishes', 'negative'], ['menu', '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": ["However, if you want great food at a great price and don't mind the decor, you can't beat this place."], "output": "{'aspect_term': [['food', 'positive'], ['price', 'positive'], ['decor', 'negative']], 'aspect_category': [[None, 'positive'], [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 owner and staff are all Japanese as well and that adds to the entire ambiance."], "output": "{'aspect_term': [['staff', 'positive'], ['ambiance', 'positive'], ['owner', '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": ["My steak au poivre was one of the worst I've had."], "output": "{'aspect_term': [['steak au poivre', '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 went with 5 friends and we lingered at the table for a bit and didn't feel rushed at all even though there was a wait."], "output": "{'aspect_term': [['table', 'neutral'], ['wait', '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 very good and warm."], "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 Bagels have an outstanding taste with a terrific texture, both chewy yet not gummy."], "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 don't mind pre-sliced low quality fish, unfriendly staff and a sushi chef that looks like he is miserable then this is your place."], "output": "{'aspect_term': [['fish', 'negative'], ['staff', 'negative'], ['sushi chef', '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 appetizers are just OK and the main courses were decidedly subpar."], "output": "{'aspect_term': [['appetizers', 'neutral'], ['main courses', '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": ["stick with the chicken, beef, and lamb dishes."], "output": "{'aspect_term': [['chicken', 'positive'], ['beef', 'positive'], ['lamb dishes', '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": ["Try sushimi cucumber roll."], "output": "{'aspect_term': [['sushimi cucumber roll', '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 corned beef was tender and melted in my mouth."], "output": "{'aspect_term': [['corned beef', '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 a little tight and on a cold day, the seating by the entranceway can be pretty drafty."], "output": "{'aspect_term': [['seating', 'negative'], ['place', '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 food inludes famous scrumptious bombay style chaat such as bhelpuri, sevpuri and samosa chaats, as well as other great indian appetizers."], "output": "{'aspect_term': [['food', 'positive'], ['bhelpuri', 'positive'], ['sevpuri', 'positive'], ['samosa chaats', 'positive'], ['indian appetizers', 'positive'], ['bombay style chaat', '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": ["We both opted for a pasta dish and they were served timely and fresh."], "output": "{'aspect_term': [['pasta dish', 'positive'], ['served', '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 incredibly helpful and attentive."], "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": ["Over the years, it has always provided a pleasurable dining experience with quality food and wine."], "output": "{'aspect_term': [['food', 'positive'], ['wine', 'positive'], ['dining', '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": ["Friendly and informative staff, very attentive and prompt raw bar service."], "output": "{'aspect_term': [['staff', 'positive'], ['bar 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": ["My friends and I experienced amazing cheese and a delicious, new summer menu at Artisanal last night."], "output": "{'aspect_term': [['cheese', '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": ["There is actually space to breathe and the decor sets the tone for an intimate dinner."], "output": "{'aspect_term': [['space', 'positive'], ['decor', 'positive'], ['dinner', '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": ["Make sure you have the Spicy Scallop roll.. ."], "output": "{'aspect_term': [['Spicy Scallop roll', '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 like your music blasted and the system isnt that great and if you want to pay at least 100 dollar bottle minimun then you'll love it here."], "output": "{'aspect_term': [['music', 'negative'], ['bottle minimun', '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": ["Been going here since it opened have seen the quality value decrease considerably."], "output": "{'aspect_term': [['quality value', '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": ["Rao's has the best service and atmosphere in NYC."], "output": "{'aspect_term': [['service', 'positive'], ['atmosphere', '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": ["Pizza was a little soggy."], "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": ["If presentation and service is your thing, then this magic show works."], "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": ["All I can say is $2 pints during happy hour and the some of the cheapest oysters you'll find in the city, though the quality is some of the best."], "output": "{'aspect_term': [['oysters', 'positive'], ['quality', '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 agreed favorite is the orrechiete with sausage and chicken (usually the waiters are kind enough to split the dish in half so you get to sample both meats)."], "output": "{'aspect_term': [['orrechiete with sausage and chicken', 'positive'], ['waiters', 'positive'], ['meats', 'neutral'], ['dish', '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": ["We were walking around the village and went into this place just for some drinks."], "output": "{'aspect_term': [['drinks', '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 parathas and kebabs are made when ordered ensuring a level of freshness that is unsurpassed."], "output": "{'aspect_term': [['parathas', 'positive'], ['kebabs', '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 fries are yummy."], "output": "{'aspect_term': [['fries', '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": ["Always a nice crowd, but never loud."], "output": "{'aspect_term': [['crowd', '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": ["Beef noodle soup is good as well."], "output": "{'aspect_term': [['Beef noodle soup', '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 doesn't compare with Mamoun's in terms of price, freshness, value, and consisent quality, but that's just my opinion."], "output": "{'aspect_term': [['price', 'negative'], ['freshness', 'negative'], ['value', 'negative'], ['quality', 'negative']], 'aspect_category': [[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": ["They also have a back garden open in the summer - cute and French with outdoor seating - what more could you ask for?"], "output": "{'aspect_term': [['back garden', 'positive'], ['outdoor seating', '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 eaten at Saul, many times, the food is always consistently, outrageously 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": ["My husband said he could've eaten several more, the portion was fine for me he even exclaimed that the french fries were the best he has had."], "output": "{'aspect_term': [['portion', 'conflict'], ['french fries', '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": ["Nha Trang, while being notorious for utter lack of comfort and decor, horribly slow wait staff and horribly quick meals, is one of the best vietnamese restaurants i've ever been to. the pho is delicious and comes with very fresh vegtables."], "output": "{'aspect_term': [['comfort', 'negative'], ['decor', 'negative'], ['wait staff', 'negative'], ['meals', 'negative'], ['pho', 'positive'], ['vegtables', 'positive']], 'aspect_category': [[None, 'negative'], [None, 'negative'], [None, 'negative'], [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": ["The place is a BISTRO which means: simple dishes and wine served efficiently in a bustling atmosphere."], "output": "{'aspect_term': [['place', 'positive'], ['dishes', 'positive'], ['wine', 'positive'], ['atmosphere', 'positive'], ['served', '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": ["We have never had any problems with charging the meal or the tip, and the food was delivered quickly, but we live only a few minutes walk from them."], "output": "{'aspect_term': [['meal', 'positive'], ['food', 'positive'], ['tip', '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": ["This place is really trendi but they have forgotten about the most important part of a  restaurant, the food."], "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": ["Odd for Ave B, not just odd, The place attracts an eclectic crowd to say the least."], "output": "{'aspect_term': [['place', '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": ["First off, the waitress was completely unattentive the 2 times we saw her(odd in a restaurant with 6 tables) and got our order wrong."], "output": "{'aspect_term': [['waitress', 'negative'], ['tables', '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 Dim Sum was so-so, but not spectacular."], "output": "{'aspect_term': [['Dim Sum', '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 server was really cool and served us our food and drinks with a smile."], "output": "{'aspect_term': [['server', 'positive'], ['food', 'neutral'], ['drinks', 'neutral'], ['served', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'neutral'], [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 food is fresh, delicious, and reasonably priced."], "output": "{'aspect_term': [['food', 'positive'], ['priced', '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 the atmorphere @ peep!"], "output": "{'aspect_term': [['atmorphere', '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 was attentive, yet unimposing, the food was far better than many notorious restaurants in Midtown and the wine list is extensive and well priced."], "output": "{'aspect_term': [['service', 'conflict'], ['food', 'positive'], ['wine list', 'positive'], ['priced', 'positive']], 'aspect_category': [[None, 'conflict'], [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": ["Hopefully next time, I will save room for dessert."], "output": "{'aspect_term': [['dessert', '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 service varys from day to day- sometimes they're very nice, and sometimes not."], "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 REALLY ENJOYED THE SHOWS PUT ON BY THE ACTORS."], "output": "{'aspect_term': [['SHOWS', 'positive'], ['ACTORS', '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": ["Average to good Thai food, but terrible delivery."], "output": "{'aspect_term': [['Thai food', 'positive'], ['delivery', '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 design and atmosphere is just as good."], "output": "{'aspect_term': [['design', 'positive'], ['atmosphere', '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": ["It's super-trendy and there's always someone to take that empty seat, so it seems that customer service has been deemed not of the essence."], "output": "{'aspect_term': [['service', 'positive'], ['seat', '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": ["We had great desserts (including the best cannoli I've ever had) and then they offered an after dinner drink, on the house."], "output": "{'aspect_term': [['desserts', 'positive'], ['cannoli', 'positive'], ['after dinner drink', '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've lived in NYC all my life and had never before seen so many waterbugs in one place (except in a really bad dream)."], "output": "{'aspect_term': [['waterbugs', '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've never had bad service and the fish is fresh and delicious."], "output": "{'aspect_term': [['service', 'positive'], ['fish', '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": ["Its a nice quiet location to go eat a good meal, relax, be able to talk and have a very good time."], "output": "{'aspect_term': [['location', '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": ["I've dined at Alain Ducasse's restaurant in Monte Carlo for half the price for the same excellent dining experience."], "output": "{'aspect_term': [['dining', '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": ["We ate outside at Haru's Sake bar because Haru's restaurant next door was overflowing."], "output": "{'aspect_term': [['bar', '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": ["Never in my life did I think that I could be satisfied both in taste and in quantity for $3.00 in NYC."], "output": "{'aspect_term': [['taste', 'positive'], ['quantity', '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 was excellent, the food was excellent, but the entire experience was very cool."], "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": ["However, looking at the table next to ours, we both sort of wished we had ordered pizza, which looked PERRRRRRRRRFECT."], "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 other night we had the $30 three course meal and everything was delicious - if I could of licked the plate clean I would of."], "output": "{'aspect_term': [['three course 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": ["uni from maine vs california, sea vs freshwater eel) to get a good taste comparison."], "output": "{'aspect_term': [['eel', '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 quantity is also very good, you will come out satisfied."], "output": "{'aspect_term': [['quantity', '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": ["During our meal, the management came over and checked on us and even bought us a round of drinks."], "output": "{'aspect_term': [['management', 'positive'], ['meal', 'neutral'], ['round of drinks', 'neutral']], 'aspect_category': [[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": ["Mine was a little burnt but still delicious with goat cheese and panchetta (raddichio was kind of bitter though)."], "output": "{'aspect_term': [['goat cheese', 'positive'], ['panchetta', 'positive'], ['raddichio', 'negative']], 'aspect_category': [[None, 'positive'], [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 real kicker of the menu, however, is the beef cubes or the chicken with chili and lemon grass."], "output": "{'aspect_term': [['menu', 'neutral'], ['beef cubes', 'positive'], ['chicken with chili and lemon grass', 'positive']], 'aspect_category': [[None, 'neutral'], [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": ["Add to that great service and great food at a reasonable price and you have yourself the beginning of a great evening."], "output": "{'aspect_term': [['service', 'positive'], ['food', '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": ["Go here for a romantic dinner but not for an all out wow dining experience."], "output": "{'aspect_term': [['dinner', 'positive'], ['dining', '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": ["Told us to sit anywhere, and when we sat he said the table was reserved."], "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": ["Service was very good - prompt, attentive and non-intrusive."], "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": ["my personal favorite is an everything bagel with lox spread, but all the bagles are unbeliavably good."], "output": "{'aspect_term': [['bagel with lox spread', 'positive'], ['bagles', '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": ["Decent Thai food in cute - though a bit dank - little Nolita hangout, BUT service terrible."], "output": "{'aspect_term': [['Thai 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": ["The flavors are very fresh and pretty inobtrusive, nothing flashy."], "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": ["Ive asked a cart attendant for a lotus leaf wrapped rice and she replied back rice and just walked away."], "output": "{'aspect_term': [['cart attendant', 'negative'], ['lotus leaf wrapped rice', 'neutral'], ['rice', 'neutral']], 'aspect_category': [[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": ["We could only get through an appetizer and cheese fondue."], "output": "{'aspect_term': [['appetizer', 'neutral'], ['cheese fondue', '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": ["Service has always been friendly and efficient."], "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": ["I ordered tamarind duck and my wife ordered noodles with ground beef, and we were both delighted by the way the dishes evoked Thai flavors in unexpected ways."], "output": "{'aspect_term': [['tamarind duck', 'positive'], ['noodles with ground beef', 'positive'], ['dishes', 'positive'], ['Thai flavors', '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 service was typical short-order, dinner type."], "output": "{'aspect_term': [['service', '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": ["Ballato's is consistently delicious authentic 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": ["But the pizza is way to expensive."], "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": ["The decor is dark, cool and soothing, while the food's presentation is spectacular, considering the low prices."], "output": "{'aspect_term': [['decor', 'positive'], ['prices', 'positive'], [\"food's presentation\", '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": ["but when we looked at the menu, there weren't a lot of choices, most of them were dumplings in the appetizer section."], "output": "{'aspect_term': [['menu', 'negative'], ['dumplings', 'neutral'], ['appetizer', '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": ["Our waiter was fine, the place looks nice in that not-trying-too-hard way, but at those prices, a little more should be expected of your food."], "output": "{'aspect_term': [['waiter', 'positive'], ['place', 'positive'], ['prices', 'negative'], ['food', '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": ["Try the congee and the donut like deep fried dough they call Ow Ley Soh, a delicious and sweet tasting bread."], "output": "{'aspect_term': [['congee', 'positive'], ['bread', 'positive'], ['donut like deep fried dough they call Ow Ley Soh', '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 live in the neighborhood and my friends meet me down here not only for the bar scene but also the promise of The Pizza Place at 3am."], "output": "{'aspect_term': [['bar scene', '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 noted it was crossed off on the bill."], "output": "{'aspect_term': [['bill', '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": ["Leon is an East Village gem: casual but hip, with well prepared basic French bistro fare, good specials, a warm and lively atmosphere."], "output": "{'aspect_term': [['specials', 'positive'], ['atmosphere', 'positive'], ['French bistro fare', '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 aesthetics of this place are like an airport lounge."], "output": "{'aspect_term': [['aesthetics', 'negative'], ['place', '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": ["Authentic food and they have REAL service, not just the rush you get sometimes when they try to push you out the door."], "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 just wonder how you can have such a delicious meal for such little money."], "output": "{'aspect_term': [['meal', 'positive'], ['money', '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": ["Dahkin also offers prix fixe lunch and buffet."], "output": "{'aspect_term': [['prix fixe lunch', 'positive'], ['buffet', '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 offers impeccable service."], "output": "{'aspect_term': [['staff', '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 prices cannot be beat for the quality, quantity, freshness and taste."], "output": "{'aspect_term': [['prices', 'positive'], ['quality', 'positive'], ['quantity', 'positive'], ['freshness', 'positive'], ['taste', '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 would recommend reservations on weekends though."], "output": "{'aspect_term': [['reservations', '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": ["Here you get the zen feel without feeling rigid."], "output": "{'aspect_term': [['zen feel', '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 great choice at any cost and a great deal."], "output": "{'aspect_term': [['cost', '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 outdoor atmosphere of sitting on the sidewalk watching the world go by 50 feet away on 6th avenue on a cool evening was wonderful."], "output": "{'aspect_term': [['outdoor 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": ["The portions are HUGE, so it might be good to order three things to split (rather than one appetizer and entree per person) for two people."], "output": "{'aspect_term': [['portions', 'positive'], ['appetizer', 'neutral'], ['entree', 'neutral']], 'aspect_category': [[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": ["Next time, we wouldn't dare ordering anything else other than some simple Asian appetizers and drinks."], "output": "{'aspect_term': [['Asian appetizers', 'positive'], ['drinks', '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 not fresh and the rice tasted old and stale."], "output": "{'aspect_term': [['fish', 'negative'], ['rice', '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 appetizing is excellent - just as good as Zabars Barney Greengrass at a reasonable price (if bought by the pound)."], "output": "{'aspect_term': [['appetizing', '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": ["With so many good restaurants on the UWS, I don't need overpriced food, absurdly arrogant wait-staff who don't recognize they work at a glorified diner, clumsy service, and management that doesn't care."], "output": "{'aspect_term': [['food', 'negative'], ['wait-staff', 'negative'], ['service', 'negative'], ['management', 'negative'], ['diner', '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": ["They have authentic Indian at amazin prices."], "output": "{'aspect_term': [['Indian', '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": ["On a hot day it was fabulous to stop in and enjoy lunch."], "output": "{'aspect_term': [['lunch', '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 plan to come here again and look forward to trying their assortment of bruschetta, panini's .."], "output": "{'aspect_term': [['bruschetta', 'positive'], ['panini', '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 cannot imagine a friendlier staff working in a restaurant."], "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": ["They forgot a sandwich, didn't include plastic forks, and didn't include pita with the hummus platter."], "output": "{'aspect_term': [['sandwich', 'neutral'], ['plastic forks', 'neutral'], ['pita', 'neutral'], ['hummus platter', '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": ["Zero ambiance to boot."], "output": "{'aspect_term': [['ambiance', '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 go to Roth's try to be served by Mike, he is GREAT!!"], "output": "{'aspect_term': [['served', '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 drinks are a saving grace, but service staff, please, get over yourselves."], "output": "{'aspect_term': [['drinks', 'positive'], ['service staff', '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": ["Their sushi, Kamikaze and other Rolls are fresh and well presented."], "output": "{'aspect_term': [['sushi', 'positive'], ['Kamikaze', 'positive'], ['Rolls', '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": ["We had a party in their private room and they made it truly memorable and were very helpful in the planning."], "output": "{'aspect_term': [['private room', '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": ["His drinks are very inventive, delicious and classy."], "output": "{'aspect_term': [['drinks', '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 a consistently great place to dine for lunch or dinner."], "output": "{'aspect_term': [['lunch', 'neutral'], ['dinner', 'neutral'], ['dine', 'positive']], 'aspect_category': [[None, 'neutral'], [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 dinner menu is diverse and top-notch as well."], "output": "{'aspect_term': [['dinner 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": ["To celebrate a birthday, three of us went to Mare anticipating great 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": ["If it's just a quick martini at the bar (which I recommend Jeffery's) or a mind blowing Roast Chicken, go to Village!"], "output": "{'aspect_term': [['martini', 'neutral'], ['bar', 'neutral'], ['Roast Chicken', 'positive']], 'aspect_category': [[None, 'neutral'], [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": ["Plus, when our entrees were held up in the kitchen on a busy Saturday night, the owner sent over complimentary summer rolls to hold us over!"], "output": "{'aspect_term': [['entrees', 'negative'], ['summer rolls', 'positive'], ['owner', '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": ["Most importantly, 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": ["Threw my fiance's surprise 30th birthday dinner here couldn't be happier."], "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": ["Great food, great decor, great service."], "output": "{'aspect_term': [['food', 'positive'], ['decor', '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": ["Overall, I'm still impressed that the place even exists and the prices are quite decent but then again, its Chinatown."], "output": "{'aspect_term': [['prices', '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 yes Dal Bukhara is so dam good and so are all the kababs."], "output": "{'aspect_term': [['kababs', 'positive'], ['Dal Bukhara', '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": ["Kenny the owner is always there and he treats my family like we are part of his family."], "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": ["Try the lobster teriyaki and the rose special roll."], "output": "{'aspect_term': [['lobster teriyaki', 'positive'], ['rose special roll', '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": ["Ive been here a bunch of times now and the service is always outstanding."], "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": ["They have some great entrees here as well."], "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": ["Waitstaff is great, very attentive."], "output": "{'aspect_term': [['Waitstaff', '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 recommend putting your name down and then getting a drink at a local bar first though because of the wait time."], "output": "{'aspect_term': [['drink', 'neutral'], ['bar', 'neutral'], ['wait time', 'negative']], 'aspect_category': [[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": ["Here's to the fake fish tanks too..."], "output": "{'aspect_term': [['fish tanks', '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": ["Small servings for main entree, i had salmon (wasnt impressed) girlfriend had chicken, it was good."], "output": "{'aspect_term': [['salmon', 'negative'], ['chicken', 'positive'], ['servings', 'negative'], ['entree', '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": ["And the bill was outragous."], "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": ["The one vegetarian entree (Abby's treasure) was actually quite a surprise - it was delicious and had wintermelon covering an assortment of fresh mushrooms and vegetables."], "output": "{'aspect_term': [['vegetarian entree', 'positive'], [\"Abby's treasure\", 'positive'], ['wintermelon', 'positive'], ['assortment of fresh mushrooms and vegetables', '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": ["One would think we'd get an apology or complimentary drinks - instead, we got a snobby waiter wouldn't even take our order for 15 minutes and gave us lip when we asked him to do so."], "output": "{'aspect_term': [['waiter', 'negative'], ['drinks', '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": ["Went for a late weekday lunch."], "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": ["service is friendly, and never had a problem walking in and getting a table."], "output": "{'aspect_term': [['service', 'positive'], ['getting a 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": ["The blond wood decor is very soothing, the premium sake is excellent and the service is great."], "output": "{'aspect_term': [['blond wood decor', 'positive'], ['sake', '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 food was good too."], "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 recommend SEA if you like thai cuisine!"], "output": "{'aspect_term': [['thai cuisine', '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 prices are exceptionally reasonable for food of this caliber."], "output": "{'aspect_term': [['prices', '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": ["try the spicy shrimp appetizer (again, not the greatest value in the world but worth the price) and the lamb vindaloo is great."], "output": "{'aspect_term': [['shrimp appetizer', 'positive'], ['price', 'conflict'], ['lamb vindaloo', 'positive']], 'aspect_category': [[None, 'positive'], [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": ["The restaraurant is very small so reservations are a must."], "output": "{'aspect_term': [['reservations', '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": ["For appetizers, I recommend the shrimp fritters and dumplings."], "output": "{'aspect_term': [['appetizers', 'neutral'], ['shrimp fritters', 'positive'], ['dumplings', 'positive']], 'aspect_category': [[None, 'neutral'], [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 everythig about it-especially the shows and actors."], "output": "{'aspect_term': [['shows', 'positive'], ['actors', '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 only fallback on this restaurant is the prices."], "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": ["A restaurant that doesn't try to do anything except serve great food with great service in a pleasant atmosphere."], "output": "{'aspect_term': [['food', 'positive'], ['service', 'positive'], ['atmosphere', '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 food was pretty tradional but it was hot and good with large portions."], "output": "{'aspect_term': [['food', 'positive'], ['portions', '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 there is very attentive and down to earth."], "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 food is great and they have a good selecion of wines at reasonable prices."], "output": "{'aspect_term': [['food', 'positive'], ['selecion of wines', '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": ["An oasis of refinement:  Food, though somewhat uneven, often reaches the pinnacles of new American fine cuisine - chef's passion (and kitchen's precise execution) is most evident in the fish dishes and soups."], "output": "{'aspect_term': [['Food', 'conflict'], ['chef', 'positive'], ['fish dishes', 'positive'], ['soups', 'positive'], ['kitchen', 'positive'], ['cuisine', 'positive']], 'aspect_category': [[None, 'conflict'], [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 couldn't reccommend their Godmother pizza any higher."], "output": "{'aspect_term': [['Godmother 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": ["Very popular style Izakaya (Sake and small portion of sake-friendly dishes )."], "output": "{'aspect_term': [['Sake', 'positive'], ['dishes', 'positive'], ['portion', '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": ["Food and service was okay."], "output": "{'aspect_term': [['Food', 'neutral'], ['service', '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": ["As a long-time patron of Mamoun's, I always figured that I had found the best late night food spot in the city."], "output": "{'aspect_term': [['food spot', '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 very good too but for the most part, it's just regular food, nothing special."], "output": "{'aspect_term': [['food', 'positive'], ['food', '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": ["I went there in late afternoon for some bite size food and refleshment with my date."], "output": "{'aspect_term': [['food', 'neutral'], ['refleshment', '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 entree was bland and small, dessert was not inspired."], "output": "{'aspect_term': [['entree', 'negative'], ['dessert', '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": ["We had a great tiem watching the shows and characters and ar food was just what we were looking for."], "output": "{'aspect_term': [['shows', 'positive'], ['food', 'positive'], ['characters', '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 service was great as well."], "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 food was average or above including some surprising tasty dishes."], "output": "{'aspect_term': [['food', 'positive'], ['dishes', '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 to find a restaurant where the owners have some imagination and they have actually pulled it off, like in this case."], "output": "{'aspect_term': [['owners', '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 some really good, inexpensive sushi."], "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": ["It won't break the bank but I also wouldnt come back for the food."], "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 certain staples are excellent (the burger, some of the pastas), the food is not really the point."], "output": "{'aspect_term': [['burger', 'positive'], ['pastas', 'positive'], ['food', 'neutral'], ['staples', 'positive']], 'aspect_category': [[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": ["The food was below average, the service was pathetic, there was no ambience at all."], "output": "{'aspect_term': [['food', 'negative'], ['service', 'negative'], ['ambience', '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 exotic food is beautifully presented and is a delight in delicious combinations."], "output": "{'aspect_term': [['exotic 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": ["You must try the shrimp appetizers."], "output": "{'aspect_term': [['shrimp appetizers', '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 thought that this place is using too much of MSG cooking in the foods."], "output": "{'aspect_term': [['foods', 'negative'], ['MSG cooking', '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": ["Immediately after we paid, the waiter took the money and said, okay, you guys are outta here."], "output": "{'aspect_term': [['waiter', '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": ["Service was very friendly."], "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": ["I must say the view of NYC is so beautiful!"], "output": "{'aspect_term': [['view', '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 never before eaten 40 pieces of relatively good nigiri."], "output": "{'aspect_term': [['nigiri', '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": ["Great food at REASONABLE prices, makes for an evening that 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 hostess is rude to the point of being offensive."], "output": "{'aspect_term': [['hostess', '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 had the cod with paella (spicy and very filling, I'm a big eater and could only eat half) while my boyfriend had the classic fish and chips (again, a big serving - at least 5 pieces of fish and a basketful of fries)."], "output": "{'aspect_term': [['cod with paella', 'negative'], ['fish and chips', 'negative'], ['serving', 'negative'], ['fish', 'neutral'], ['fries', 'neutral']], 'aspect_category': [[None, 'negative'], [None, 'negative'], [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": ["This is such a lovely, peaceful place to eat outside."], "output": "{'aspect_term': [['place', '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": ["Warm and friendly in the winter and terrific outdoor seating in the warmer months."], "output": "{'aspect_term': [['outdoor seating', '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 prices and ambience are especially great considering it's in the West Village."], "output": "{'aspect_term': [['prices', 'positive'], ['ambience', '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": ["Because of the delicate thin crust, take-out pies get soggy in their boxes."], "output": "{'aspect_term': [['take-out pies', 'negative'], ['crust', '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": ["If you love seafood, you would love this place!"], "output": "{'aspect_term': [['seafood', '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": ["Love the Jazz bands on Fri and Sat."], "output": "{'aspect_term': [['Jazz bands', '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 ordering from the regular menu, then you would not regret!"], "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": ["Disappointing food, lousy service."], "output": "{'aspect_term': [['food', 'negative'], ['service', '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": ["Nice ambiance, nice little bar, good bartender, Francois, and good service."], "output": "{'aspect_term': [['bar', 'positive'], ['bartender', 'positive'], ['service', 'positive'], ['ambiance', '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": ["My suggestion is to eat family style because you'll want to try the other dishes."], "output": "{'aspect_term': [['dishes', 'neutral'], ['eat family style', '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": ["Of course the reason its so packed is because the food is so 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": ["A great way to make some money is to buy a case of snapple from Costco and sell it right outside for only $2.50."], "output": "{'aspect_term': [['case of snapple', '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": ["Guacamole+shrimp appetizer was really great, we both had the filet, very good, didn't much like the frites that came with, but the filet was so good, neither of us cared."], "output": "{'aspect_term': [['Guacamole+shrimp appetizer', 'positive'], ['filet', 'positive'], ['frites', 'negative'], ['filet', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [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": ["Service is great, takeout is good too."], "output": "{'aspect_term': [['Service', 'positive'], ['takeout', '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": ["overall, a solid restaurant and at less than $40pp (including wine), a solid deal as well."], "output": "{'aspect_term': [['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": ["Aside from the Sea Urchin, the chef recommended an assortment of fish including Fatty Yellow Tail, Boton Shrimp, Blue Fin Torro (Fatty Tuna), Sea Eel, etc."], "output": "{'aspect_term': [['chef', 'neutral'], ['assortment of fish', 'neutral'], ['Fatty Yellow Tail', 'neutral'], ['Boton Shrimp', 'neutral'], ['Sea Eel', 'neutral'], ['Sea Urchin', 'neutral'], ['Blue Fin Torro (Fatty Tuna)', 'neutral']], 'aspect_category': [[None, 'neutral'], [None, 'neutral'], [None, 'neutral'], [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": ["kalbi and nebbiolo do work together."], "output": "{'aspect_term': [['kalbi', 'neutral'], ['nebbiolo', '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": ["Located at the end of a magnificent block."], "output": "{'aspect_term': [['Located', '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 is usually very good, though ocasionally I wondered about freshmess of raw vegatables in side orders."], "output": "{'aspect_term': [['Food', 'conflict'], ['raw vegatables', '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": ["The bruscetta is a bit soggy, but the salads were fresh, included a nice mix of greens (not iceberg) all dishes are served piping hot from the kitchen."], "output": "{'aspect_term': [['bruscetta', 'negative'], ['salads', 'positive'], ['dishes', 'positive'], ['mix of greens', 'positive'], ['iceberg', 'neutral'], ['served', 'positive']], 'aspect_category': [[None, 'negative'], [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": ["This place is not worth the prices."], "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": ["The decor is vibrant and eye-pleasing with several semi-private boths on the right side of the dining hall, which are great for a date."], "output": "{'aspect_term': [['decor', 'positive'], ['dining hall', 'positive'], ['semi-private boths', '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 got an excellent piece of cheesecake and we had several other nice pastries."], "output": "{'aspect_term': [['cheesecake', 'positive'], ['pastries', '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 like the somosas, chai, and the chole, but the dhosas and dhal were kinda dissapointing."], "output": "{'aspect_term': [['somosas', 'positive'], ['chai', 'positive'], ['chole', 'positive'], ['dhosas', 'negative'], ['dhal', 'negative']], 'aspect_category': [[None, 'positive'], [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": ["We ordered a tuna melt - it came with out cheese which just made it a tuna sandwich."], "output": "{'aspect_term': [['tuna melt', 'negative'], ['cheese', 'neutral'], ['tuna sandwich', '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 sicilian is my favorite it is moist not dry like most places but all their pizza is great!"], "output": "{'aspect_term': [['pizza', 'positive'], ['sicilian', '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 definitely good, but I left a bit disappointed."], "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 chicken and steak were seasoned and cooked to perfection, and the lamb sandwhich is great for heartier appetites."], "output": "{'aspect_term': [['chicken', 'positive'], ['steak', 'positive'], ['lamb sandwhich', '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 too crazy about their sake martini."], "output": "{'aspect_term': [['sake martini', '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": ["Got club soda, filled with ice, no lime."], "output": "{'aspect_term': [['club soda, filled with ice, no lime', '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": ["Also good for client lunch meetings, esp."], "output": "{'aspect_term': [['lunch meetings', '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": ["Good, dark atmosphere and the music is a nice touch."], "output": "{'aspect_term': [['atmosphere', '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": ["Grilled whole fish wonderful, great spicing."], "output": "{'aspect_term': [['fish', '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 people who want great food plus great service, Roxy is a place to AVOID!"], "output": "{'aspect_term': [['food', 'negative'], ['service', '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": ["Each table has a pot of boiling water sunken into its surface, and you get platters of thin sliced meats, various vegetables, and rice and glass noodles."], "output": "{'aspect_term': [['table', 'neutral'], ['pot of boiling water', 'neutral'], ['meats', 'neutral'], ['vegetables', 'neutral'], ['rice', 'neutral'], ['glass noodles', 'neutral']], 'aspect_category': [[None, 'neutral'], [None, 'neutral'], [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": ["The food is good, I can't lie."], "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": ["Stick to the gulab jamun."], "output": "{'aspect_term': [['gulab jamun', '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": ["Kind of a small place but I guess if they are not too busy might be able to fit a group or kids."], "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": ["They have it all -- great price, food, and service."], "output": "{'aspect_term': [['price', 'positive'], ['food', '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 wasn't thrilled to have to wait on line for thirty minutes, but I guess that's the price you pay for a popular place."], "output": "{'aspect_term': [['wait', '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've been to this restaurant more than a dozen times and when I'm craving for Pho, Lemon grass chicken or Beef Cube on rice, this is the place to go."], "output": "{'aspect_term': [['Pho', 'positive'], ['Lemon grass chicken', 'positive'], ['Beef Cube on rice', '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": ["However, service was as plain as sesame crusted Salmon I had."], "output": "{'aspect_term': [['service', 'neutral'], ['sesame crusted Salmon', '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": ["Yes you have to wait to be seated and because its small there is no waiting area and the seat at the bar was all taken."], "output": "{'aspect_term': [['waiting area', 'negative'], ['seat', 'negative'], ['bar', 'neutral'], ['wait', 'negative']], 'aspect_category': [[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": ["We are very particular about sushi and were both please with every choice which included: ceviche mix (special), crab dumplings, assorted sashimi, sushi and rolls, two types of sake, and the banana tempura."], "output": "{'aspect_term': [['sushi', 'positive'], ['ceviche mix (special)', 'positive'], ['crab dumplings', 'positive'], ['assorted sashimi', 'positive'], ['sushi', 'positive'], ['rolls', 'positive'], ['sake', 'positive'], ['banana tempura', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [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 counter service is bad."], "output": "{'aspect_term': [['counter 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 need at least three rolls to be full, and that's at least $14.00!"], "output": "{'aspect_term': [['rolls', '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": ["Their exotic salad is basic ly a delcious little green salad with a peanut sauce that is perfect before their sweet basil fried tofu."], "output": "{'aspect_term': [['exotic salad', 'positive'], ['green salad', 'positive'], ['sweet basil fried tofu', 'positive'], ['peanut sauce', '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": ["An excellent 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": ["If you're craving for Haru's great food, especially the House Roll, but can't stand the wait building outisde, head across the street to their Sake Bar!"], "output": "{'aspect_term': [['food', 'positive'], ['wait building', '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 picks: Guizhou chicken, fish with hot bean source, fish fillet in spicy source (special menu)."], "output": "{'aspect_term': [['Guizhou chicken', 'positive'], ['fish with hot bean source', 'positive'], ['fish fillet in spicy source', 'positive'], ['special menu', '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": ["Waiters tend to forget drinks completely, food portions are so tiny, two people have trouble sharing one entree."], "output": "{'aspect_term': [['Waiters', 'negative'], ['food portions', 'negative'], ['drinks', 'neutral'], ['entree', 'negative']], 'aspect_category': [[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": ["The portions are now very small, the sauces are overly-ambitious usually inedible while the service is still good, the restaurant, due to its popularity, seems frantic."], "output": "{'aspect_term': [['portions', 'negative'], ['sauces', 'negative'], ['service', 'positive']], 'aspect_category': [[None, 'negative'], [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": ["If anyones has doubt of not knowing enough about wines,please check their wine list."], "output": "{'aspect_term': [['wines', 'neutral'], ['wine list', '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 crackling calamari salad, which is usually a cheap disaster at many restaurants, is crispy and lightly dressed."], "output": "{'aspect_term': [['crackling calamari salad', '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 lava cake dessert was incredible and I recommend it."], "output": "{'aspect_term': [['lava cake dessert', '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 steak was very fatty and the sauce was overpowering and not very tasty."], "output": "{'aspect_term': [['steak', 'negative'], ['sauce', '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": ["Even if the food wasn't this good, the garden is a great place to sit outside and relax."], "output": "{'aspect_term': [['food', 'positive'], ['garden', 'positive'], ['place', '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": ["And I would have to agree with the masses in terms of service - delivery is their Achilles' heel."], "output": "{'aspect_term': [['service', 'negative'], ['delivery', '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 food was actually aweful."], "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": ["Some servers make you feel like they are doing you a favor to bring you the food."], "output": "{'aspect_term': [['servers', 'negative'], ['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": ["word of advice, save room for pasta dishes and never leave until you've had the tiramisu."], "output": "{'aspect_term': [['pasta dishes', 'positive'], ['tiramisu', '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 delicious but do not come here on a empty stomach."], "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": ["Growing up in NY, I have eaten my share of bagels."], "output": "{'aspect_term': [['bagels', '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": ["As much as I like the food there, I can't bring myself to go back."], "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": ["Nicky the Nose at the bar is a treat."], "output": "{'aspect_term': [['bar', '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 dim sum is ok but doesn't taste that fresh, and the little dishes don't look steamy hot as they should (also note lack of Chinese here)."], "output": "{'aspect_term': [['dim sum', 'negative'], ['little dishes', '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": ["We actually left hungry and went across the street to Wo Hop at 15 Mott street for some good chinese food."], "output": "{'aspect_term': [['chinese 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 service is spotty, sometimes really friendly and sometimes barely there."], "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 seafood is amazing, there's a good wine list, and the ever-changing menu always offers some great surprises."], "output": "{'aspect_term': [['seafood', 'positive'], ['wine list', 'positive'], ['menu', '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": ["We couldn't carry our conversation as we were routinely interrupted by waitress and servants asking us to order and hinting that we're taking too much time -- amazing, we just sat down."], "output": "{'aspect_term': [['waitress', 'negative'], ['servants', '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 wine list is extensive and can easily hike up an otherwise reasonably priced meal."], "output": "{'aspect_term': [['wine list', 'positive'], ['meal', 'positive'], ['priced', '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": ["Having not been home in the last 2 years may skew this reviewer a bit, but the food was tasty and spicy sans the oil that comes floating along at similar venues."], "output": "{'aspect_term': [['food', 'positive'], ['oil', '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 dim sum servings here are a bit larger than I'm used to."], "output": "{'aspect_term': [['dim sum servings', '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": ["Fish is so very fresh."], "output": "{'aspect_term': [['Fish', '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": ["While Sapphire is certainly not lacking in ambiance, and probably has the best decor of any Indian restaurant I have been to in New York City, the food was not what I had hoped for."], "output": "{'aspect_term': [['food', 'negative'], ['ambiance', 'positive'], ['decor', '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": ["The food is 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": ["Right off the L in Brooklyn this is a nice cozy place with good pizza."], "output": "{'aspect_term': [['pizza', '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": ["The food is reliable and the price is moderate."], "output": "{'aspect_term': [['food', 'positive'], ['price', '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": ["I love to visit Murrays for my bagel fix."], "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": ["My wife and I went to Orsay for Valentine's 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 two star chefs left quite some time ago to open their own place."], "output": "{'aspect_term': [['chefs', '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": ["And the fried clams had just enough kick to them to make 'em worth eating."], "output": "{'aspect_term': [['fried clams', '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": ["Good drink."], "output": "{'aspect_term': [['drink', '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": ["night without a reservation, we had to wait at the bar for a little while, but the manager was so nice and made our wait a great experience."], "output": "{'aspect_term': [['manager', 'positive'], ['reservation', 'neutral'], ['bar', 'neutral'], ['wait', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'neutral'], [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": ["Unfortunately, the food was NOT something to get worked up about."], "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 wine and cheese plate are plentiful and can't wait to try the fondue or table grilling."], "output": "{'aspect_term': [['wine', 'positive'], ['cheese', 'positive'], ['fondue', 'positive'], ['table grilling', '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 food is uniformly exceptional, with a very capable kitchen which will proudly whip up whatever you feel like eating, whether it's on the menu or not."], "output": "{'aspect_term': [['food', 'positive'], ['kitchen', 'positive'], ['menu', '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": ["Try their plain pizza with fresh garlic or eggplant."], "output": "{'aspect_term': [['plain pizza', 'positive'], ['garlic', 'positive'], ['eggplant', '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 food is spectacular, from the appitizers to the main course, and then of course the desserts, (WOW) you'll need no more."], "output": "{'aspect_term': [['food', 'positive'], ['appitizers', 'positive'], ['main course', 'positive'], ['desserts', '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 food is alright - some stuff is good - some is not (like the steak dish which tends to be dry)."], "output": "{'aspect_term': [['food', 'conflict'], ['steak dish', '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": ["it's the only place you can get yummy authentic japanese comfort food."], "output": "{'aspect_term': [['japanese comfort 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 both ordered the Steak, medium."], "output": "{'aspect_term': [['Steak', '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 was so bad I actually refused to pay for my food."], "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": ["I always get the Shabu-Shabu dinner and the beef is always fresh."], "output": "{'aspect_term': [['Shabu-Shabu dinner', 'neutral'], ['beef', '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": ["It saves walking in and waiting for a table in the often noisy, crowded bar at dinnertime."], "output": "{'aspect_term': [['bar', 'negative'], ['waiting', 'negative'], ['table', '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 spicy Tuna roll is huge and probably the best that I've had at this price range."], "output": "{'aspect_term': [['Tuna roll', 'positive'], ['price range', '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 sweet lassi was excellent as was the lamb chettinad and the garlic naan but the rasamalai was forgettable."], "output": "{'aspect_term': [['sweet lassi', 'positive'], ['lamb chettinad', 'positive'], ['garlic naan', 'positive'], ['rasamalai', 'negative']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [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": ["Our server checked on us maybe twice during the entire meal."], "output": "{'aspect_term': [['server', 'negative'], ['meal', '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": ["When you want a piece of beef, head on over."], "output": "{'aspect_term': [['beef', '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": ["But the coconut rice was good."], "output": "{'aspect_term': [['coconut rice', '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": ["Good for casual dinner with jeans and sneakers."], "output": "{'aspect_term': [['casual 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": ["It appears to be the owner's first venture and it shows."], "output": "{'aspect_term': [['owner', '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 won't go back unless someone else is footing the bill."], "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": ["Saturday, Nov. 6th I had a group from work come in with about 35 people and the staff was amazing to accomodate us."], "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": ["Jimmy's is hands down the hottest night spot in the Bronx."], "output": "{'aspect_term': [['spot', '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 also ordered the Change Mojito, which was out of this world."], "output": "{'aspect_term': [['Change Mojito', '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 live in New Jersey and whenever we go into New York City we buy bagels to eat hot and then to freeze (they told me that if I call in the order, they'd bring it out to the car so I wouldn't have to look for parking)."], "output": "{'aspect_term': [['bagels', '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 he's not making authentic Neapolitan pizza in the open brick oven or lightly frying zucchini blossoms, he's visiting the regulars (a growing legion) and checking on newcomers."], "output": "{'aspect_term': [['Neapolitan pizza', 'positive'], ['zucchini blossoms', '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 would not have been so disappointed with the portions if the qualities were good enough to make up for it, but they were not!"], "output": "{'aspect_term': [['portions', 'negative'], ['qualities', '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 prices are about $9 for an entree for dinner and even less for lunch."], "output": "{'aspect_term': [['prices', 'positive'], ['entree', 'positive'], ['dinner', 'neutral'], ['lunch', 'positive']], 'aspect_category': [[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": ["The wine list is excellent."], "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": ["The noise level was unbearable, conversation impossible."], "output": "{'aspect_term': [['noise level', '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": ["Example is the soup which was about 6 oz for $12 dollars and the mushrooms where $12 for about 1oz."], "output": "{'aspect_term': [['soup', 'positive'], ['mushrooms', '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": ["Great for groups, great for a date, great for early brunch or a nightcap."], "output": "{'aspect_term': [['brunch', 'positive'], ['nightcap', '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": ["Went to Ottimo and was expecting outstanding pizza (as I love La Pizza Fresca)."], "output": "{'aspect_term': [['pizza', '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": ["To my right, the hostess stood over a busboy and hissed rapido, rapido as he tried to clear and re-set a table for six."], "output": "{'aspect_term': [['hostess', 'negative'], ['busboy', 'neutral'], ['table', 'neutral']], 'aspect_category': [[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": ["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": ["I recommend their Pad See Ew, Pork Chops or Tofu plates."], "output": "{'aspect_term': [['Pad See Ew', 'positive'], ['Pork Chops', 'positive'], ['Tofu plates', '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": ["Last time I went here, the waitress didn't come back after taking our order."], "output": "{'aspect_term': [['waitress', '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 went to DF for Valentines Day dinner."], "output": "{'aspect_term': [['Valentines Day 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": ["Our food was great too!"], "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": ["It takes forever to get a drink and they almost always forget to bring something (although they dont forget to charge you for it."], "output": "{'aspect_term': [['drink', '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": ["Several of the dim sum orders had about 6-8 pieces."], "output": "{'aspect_term': [['dim sum orders', '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": ["We were fans of the half-price Saturday night option until some inedible squid during a recent visit."], "output": "{'aspect_term': [['squid', 'negative'], ['half-price Saturday night option', '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": ["However, go for the ambience, and consider the food just a companion for a trip across the world!"], "output": "{'aspect_term': [['ambience', '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 waiter actually poured water on my hand and walked away."], "output": "{'aspect_term': [['waiter', 'negative'], ['water', '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": ["Service was excellent, and the AC worked very well too (thank God, it was hot!)."], "output": "{'aspect_term': [['Service', 'positive'], ['AC', '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": ["Wouldn't recomend it for dinner!"], "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": ["So I've never actually been to M proper, but I've had it delivered a few times."], "output": "{'aspect_term': [['delivered', '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 on a double date with friend and his girlfriend for a few drinks and appetizers."], "output": "{'aspect_term': [['drinks', '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": ["Kind, attentive wait staff."], "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": ["They might be all business at the counter when you give your order, but their food says I love you."], "output": "{'aspect_term': [['food', 'positive'], ['counter', '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 love Indian food and consider myself to be quite an expert on it."], "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 service was mediocre, and the lack of air conditioning made for a less than comfortable meal."], "output": "{'aspect_term': [['service', 'neutral'], ['air conditioning', 'negative'], ['meal', '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 price is reasonable although the service is poor."], "output": "{'aspect_term': [['price', '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": ["Food is average, and I would say even the chain restaurant Baluchi's tastes better."], "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": ["You get the sense that the people there care about their restaurant and about your experience and that is very nice."], "output": "{'aspect_term': [['people', '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": ["As soon as my father lifted his pen from the check a chef appeared to usher us out."], "output": "{'aspect_term': [['chef', 'negative'], ['check', '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 ceiling is amazing!"], "output": "{'aspect_term': [['ceiling', '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 split a tasty vegetable samosa and the malai tikka wrap."], "output": "{'aspect_term': [['vegetable samosa', 'positive'], ['malai tikka wrap', '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 here is rather good, but only if you like to wait for it."], "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 food is prepared quickly and efficiently."], "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": ["Everything is excellent, the menu is quite extensive, and you eat with a view on both sides of the city."], "output": "{'aspect_term': [['menu', '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": ["Spice is great Thai food, love the inexpensive appetizers."], "output": "{'aspect_term': [['Thai food', 'positive'], ['appetizers', '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'm still mad that i had to pay for lousy food."], "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": ["Anyways, if you're in the neighborhood to eat good food, I wouldn't waste my time trying to find something, rather go across the street to Tamari."], "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 took my girlfriend there for her birthday last night and we had a relaxing, really good 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": ["Once they ran out of Gnochi and made it for me from scratch!"], "output": "{'aspect_term': [['Gnochi', '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 got the $10 10-piece dim sum combo, every bite of which was great."], "output": "{'aspect_term': [['dim sum combo', '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 hanger steak was like rubber and the tuna was flavorless not to mention it tasted like it had just been thawed."], "output": "{'aspect_term': [['hanger steak', 'negative'], ['tuna', '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": ["Food was okay, nothing great."], "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": ["Emilio, the owner, is often sitting in the front table greeting guests as they come and go."], "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 crispy chicken wasn't for us, though."], "output": "{'aspect_term': [['crispy chicken', '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": ["After all that, they complained to me about the small tip."], "output": "{'aspect_term': [['tip', '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 Waitstaff were very nice and suggested swordfish for my husband he enjoyed his meal."], "output": "{'aspect_term': [['Waitstaff', 'positive'], ['swordfish', 'positive'], ['meal', '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 started out with a Bombay beer which was big enough for two."], "output": "{'aspect_term': [['Bombay 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": ["If you have a dumpling fetish i suggest you try some here!"], "output": "{'aspect_term': [['dumpling', '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 go back in line like three times on average until I can't walk anymore."], "output": "{'aspect_term': [['line', '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 great and inexpensive."], "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 palak paneer was standard, and I was not a fan of the malai kofta."], "output": "{'aspect_term': [['palak paneer', 'neutral'], ['malai kofta', '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": ["I had the salmon dish and while it was fine, for the price paid, I expected it to have some type of flavor."], "output": "{'aspect_term': [['salmon dish', 'conflict'], ['flavor', 'negative'], ['price', 'neutral']], 'aspect_category': [[None, 'conflict'], [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": ["Try the lasagnette appetizer."], "output": "{'aspect_term': [['lasagnette 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": ["If you want some roast duck, pork or chicken on rice with ginger, try them out!"], "output": "{'aspect_term': [['roast duck', 'positive'], ['pork', 'positive'], ['chicken on rice with ginger', '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 great to go for a quick lunch either alone or with a friend."], "output": "{'aspect_term': [['lunch', '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 PORTIONS ARE REALLY LARGE."], "output": "{'aspect_term': [['FOOD PORTIONS', '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": ["Going to Volare is like going to your favorite aunt's house for dinner, assuming that your aunt is a great Italian cook."], "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": ["Great wine selection, Gigondas is worth the price, and the house champagne is a great value."], "output": "{'aspect_term': [['wine selection', 'positive'], ['Gigondas', 'positive'], ['house champagne', 'positive'], ['price', '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 food here does a great service to the name (Cantonese that is...)."], "output": "{'aspect_term': [['food', 'positive'], ['Cantonese', '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 enjoyed everything I have ever gotten and the fish is so fresh and always prepared in a great way."], "output": "{'aspect_term': [['fish', '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 was a bit slow, but they were very friendly."], "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": ["Yet paired with such rude service, would never recommend for anyone interested in carrying any kind of conversation while there."], "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": ["Killer Sushi!"], "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": ["Excellent dumplings served amid clean, chic decor."], "output": "{'aspect_term': [['dumplings', '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": ["We visited Bread Bar during January restaurant week and were so pleased with the menu selections and service."], "output": "{'aspect_term': [['menu selections', '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 pickles were great addition."], "output": "{'aspect_term': [['pickles', '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 average and creme brulee was awful - the sugar was charred, not caramelized and smelled of kerosene."], "output": "{'aspect_term': [['Food', 'neutral'], ['creme brulee', 'negative'], ['sugar', '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 walked in on a Wednesday night and were seated promptly."], "output": "{'aspect_term': [['seated', '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": ["Despite a slightly limited menu, everything prepared is done to perfection, ultra fresh and a work of food art."], "output": "{'aspect_term': [['menu', 'negative'], ['food art', '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": ["They are still living in the dark ages and do not have an answering machine, so if you want to make a reservation you are limited."], "output": "{'aspect_term': [['reservation', '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": ["You have to increase the service a lot."], "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": ["It's a nice place to relax and have conversation."], "output": "{'aspect_term': [['place', '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 was the worst dining experience I've ever had."], "output": "{'aspect_term': [['dining experience', '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 meat dishes were only so-so."], "output": "{'aspect_term': [['meat dishes', '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 would have gotten some cole slaw and a knish if my stomach had more space."], "output": "{'aspect_term': [['cole slaw', 'neutral'], ['knish', '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 wait staff is friendly, and the food has gotten better and better!"], "output": "{'aspect_term': [['wait staff', '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 would definitely go back -- if only for some of those exotic martinis on the blackboard."], "output": "{'aspect_term': [['martinis', '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 a little more expensive than your average bagel place."], "output": "{'aspect_term': [['bagel', '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": ["Found service above average, but that could be because we were 13 of us."], "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": ["Food was average but tasty."], "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 boyfriend and I recently had an early dinner at Artisanal and was satisfied with our experience."], "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": ["The food was so-so."], "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": ["I've overheard comments from him to his employees that should not have been delivered in the dining area and I've been sitting there while he lectured another customer."], "output": "{'aspect_term': [['employees', 'negative'], ['dining area', '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": ["This little place definitely exceeded my expectations and you sure get a lot of food for your money."], "output": "{'aspect_term': [['food', 'positive'], ['money', 'positive'], ['place', '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": ["For great chinese food nearby, you have Wu Liang Ye and Grand Sichuan just a block away."], "output": "{'aspect_term': [['chinese 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've been coming here as a child and always come back for the taste."], "output": "{'aspect_term': [['taste', '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 all ate pasta entre'es, which were great."], "output": "{'aspect_term': [[\"pasta entre'es\", '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 had scrapped the bottom of the vessel in which they make the rice -RESULT - WE HAD LARGE CHUNKS OF BURNT RICE IN OUR SERVING BOWL."], "output": "{'aspect_term': [['rice', 'negative'], ['RICE', '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": ["Pastrami or corned beef are juicy and piled high (ask for extra rye bread)."], "output": "{'aspect_term': [['Pastrami or corned beef', 'positive'], ['rye bread', '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 brioche and lollies as party favors is a cute and sweet touch to a most memorable meal."], "output": "{'aspect_term': [['brioche and lollies', '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": ["Try the chocolate mud cake (warmed) with 2 scoops of dulce de leche gelato."], "output": "{'aspect_term': [['chocolate mud cake (warmed)', 'positive'], ['dulce de leche gelato', '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": ["For many people, this may not seem like Aunthentic Thai food because most places in NYC arent quite authentic."], "output": "{'aspect_term': [['Thai 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": ["I have eaten a lot of pizza here."], "output": "{'aspect_term': [['pizza', '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": ["We concluded with tiramisu chocolate cake, both were delicious."], "output": "{'aspect_term': [['tiramisu chocolate cake', '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 sauce is delicious and the crust is perfect."], "output": "{'aspect_term': [['sauce', 'positive'], ['crust', '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 he finally did, he was unable to make a gin and tonic -- couldn't find tonic."], "output": "{'aspect_term': [['gin and tonic', 'neutral'], ['tonic', '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": ["They have a very diverse menu so its something for everybody."], "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": ["The waitress remembers me and is very friendly, she knows what my regular is and that's the fried mini buns with the condensed milk and the assorted fruits on beancurd."], "output": "{'aspect_term': [['waitress', 'positive'], ['fried mini buns with the condensed milk and the assorted fruits on beancurd', '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 the pasta is delicious here (a rarity in New York pizza restaurants)."], "output": "{'aspect_term': [['pasta', '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 a 3 hour brunch- they definitely do not rush you- and they kept the unlimited mimosas flowing the whole time."], "output": "{'aspect_term': [['brunch', 'positive'], ['mimosas', '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, wine selection, ambiance are all outstanding and deserve recognition."], "output": "{'aspect_term': [['service', 'positive'], ['wine selection', 'positive'], ['ambiance', '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": ["Where tanks in other Chinatown restaurants display a lurking myriad of sad-looking marine life in their murky waters, the tanks at Ping's are clear as glass with healthy-looking creatures who do not yet know that they will be part of some dim sum lover's brunch."], "output": "{'aspect_term': [['tanks', 'negative'], ['tanks', 'positive'], ['dim sum', 'neutral'], ['brunch', 'neutral']], 'aspect_category': [[None, 'negative'], [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": ["Salads are a delicious way to begin the meal."], "output": "{'aspect_term': [['Salads', '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": ["I look forward to eating here again"], "output": "{'aspect_term': [['eating', '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 great deal for 6 Blue Point oysters and a beer or glass of wine for $8!"], "output": "{'aspect_term': [['Blue Point oysters', 'neutral'], ['beer', 'neutral'], ['glass of wine', '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": ["I could have drank 4 glasses of water and still been parched - so watch out."], "output": "{'aspect_term': [['glasses of water', '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": ["Won't or Can't is not in the service directory."], "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": ["We go on Mondays for the prix fixe and our experience with the food has been comparable to Blue Ribbon."], "output": "{'aspect_term': [['food', 'neutral'], ['prix fixe', '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 mostly made from scratch, fresh and well prepared."], "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": ["But who says Murray's is anything about service."], "output": "{'aspect_term': [['service', '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 found the food, service and value exceptional everytime I have been there."], "output": "{'aspect_term': [['food', 'positive'], ['service', 'positive'], ['value', '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 food, drinks and service are clearly among the best in the city."], "output": "{'aspect_term': [['food', 'positive'], ['drinks', '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": ["Thalia is a beautiful restaurant with beautiful people serving you, but the food doesn't quite match up."], "output": "{'aspect_term': [['people serving', '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 atmosphere is unheralded, the service impecible, and the food magnificant."], "output": "{'aspect_term': [['atmosphere', '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": ["i've been back to nha trang literally a hundred times for the beef cubes - they're that good."], "output": "{'aspect_term': [['beef cubes', '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 well attended to by the enthusiastic staff especially the manager Tony Gaskin who made excellent suggestions for our menu selections."], "output": "{'aspect_term': [['staff', 'positive'], ['manager', 'positive'], ['menu selections', '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": ["Best Pastrami I ever had and great portion without being ridiculous."], "output": "{'aspect_term': [['Pastrami', 'positive'], ['portion', '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": ["IT IS WHAT MODERN CUISINE IS ALL ABOUT."], "output": "{'aspect_term': [['CUISINE', '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": ["Each bite of food at Kai was indeed delicious, fresh, and elegant."], "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 Kruno, the beverage manager is the best bartender I have yet to come across."], "output": "{'aspect_term': [['bartender', 'positive'], ['beverage manager', '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 bland oily."], "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 tastes makes your mouth water for more."], "output": "{'aspect_term': [['tastes', '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 horrible and the ambience is not that great."], "output": "{'aspect_term': [['Service', 'negative'], ['ambience', '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 barebecued salmon is elegantly spiced and not at all dry."], "output": "{'aspect_term': [['barebecued salmon', '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": ["now if they could only get a toaster."], "output": "{'aspect_term': [['toaster', '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 had very high expectations for this place and made a reservation a couple of months in advance for a special 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": ["Whem asked, we had to ask more detailed questions so that we knew what the specials were."], "output": "{'aspect_term': [['specials', '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": ["Waiters are slow but sweet."], "output": "{'aspect_term': [['Waiters', '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": ["While I quite liked the food and the ambience, I'm not quite sure if it they really deserve it the Michelin rating they have displayed so prooudly in the window."], "output": "{'aspect_term': [['food', 'positive'], ['ambience', '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've the best desserts and mixed drinks as well as snack foods."], "output": "{'aspect_term': [['desserts', 'positive'], ['mixed drinks', 'positive'], ['snack foods', '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 entire place and the treatment we received felt as a conveyor belt."], "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": ["Good crowd, good outdoor seating, with a hip japanese vibe."], "output": "{'aspect_term': [['outdoor seating', 'positive'], ['vibe', '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": ["Any if you have a reservation you'll wait for max 5 minutes - so have a drink at the bar."], "output": "{'aspect_term': [['reservation', 'positive'], ['drink', 'neutral'], ['bar', 'neutral']], 'aspect_category': [[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": ["Fresh, authentic, french cuisine in substantial portions."], "output": "{'aspect_term': [['french cuisine', 'positive'], ['portions', '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 atmosphere is much better than Sripraphai (more modern and sleek)."], "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": ["The banana tower is an amazing dessert as well."], "output": "{'aspect_term': [['banana tower', 'positive'], ['dessert', '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 restaurant looks out over beautiful green lawns to the Hudson River and the Statue of Liberty."], "output": "{'aspect_term': [['lawns', '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 really also the service, is good and the waiters are friendly."], "output": "{'aspect_term': [['service', '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": ["The Pad thai, lad nar and various other dishes all look good on paper but, I've had better thai food in less asthetically pleasing places."], "output": "{'aspect_term': [['Pad thai', 'conflict'], ['lad nar', 'conflict'], ['dishes', 'conflict'], ['places', 'negative'], ['thai food', 'neutral']], 'aspect_category': [[None, 'conflict'], [None, 'conflict'], [None, 'conflict'], [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 cold appetizer dishes taste like the way I remember them to taste when I was growing up in Taiwan."], "output": "{'aspect_term': [['cold appetizer 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": ["Restaurant snobs need not bother, this is a small, neighborhood kind of place."], "output": "{'aspect_term': [['place', '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": ["Based on the reviews for dinner, this is a place I would reconsider revisiting for that, but definitely not for Dim Sum again."], "output": "{'aspect_term': [['Dim Sum', 'negative'], ['dinner', '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": ["Good, 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 anti-pasta was excellent, especially the calamari, as were the filling pasta mains."], "output": "{'aspect_term': [['anti-pasta', 'positive'], ['calamari', 'positive'], ['filling pasta mains', '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 food is a diamond in rough -- the food is delicious and homemade with the perfect balance of herbs and tomatoes."], "output": "{'aspect_term': [['food', 'positive'], ['food', 'positive'], ['herbs', 'positive'], ['tomatoes', '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 jukebox plays everything from Italian Opera to The Strokes."], "output": "{'aspect_term': [['jukebox', '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 bruschetta and panini's are so yummy!"], "output": "{'aspect_term': [['bruschetta', 'positive'], ['panini', '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": ["Great for large groups and celebrations - our SUPER HAPPY waiter was the entertainment of the evening."], "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": ["I don't know about you guys, but when I go somewhere to eat I go for the food not for the atmosphere."], "output": "{'aspect_term': [['food', 'neutral'], ['atmosphere', '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 portions are large and the servers always surprise us with a different starter."], "output": "{'aspect_term': [['portions', 'positive'], ['servers', 'positive'], ['starter', '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": ["Great bagels made the old-fashioned way."], "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 menu consisted of standard brassiere food, better then places like Balthazar etc."], "output": "{'aspect_term': [['menu', 'positive'], ['brassiere 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": ["This place would be so much better served by being run by a group that actually understands customer service."], "output": "{'aspect_term': [['service', 'negative'], ['served', '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": ["Cornelia Street looks like a Broadway set for West Side Story and the inside of Po is so cool quaint you really can't top the setting for a romantic dinner in NYC."], "output": "{'aspect_term': [['dinner', 'positive'], ['setting', '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 drinks are amazing and half off till 8pm."], "output": "{'aspect_term': [['drinks', '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": ["Such nice people working here - but I have to review the food."], "output": "{'aspect_term': [['people', 'positive'], ['food', '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": ["Great romantic place for a date (try to get the corner booth table for a little privacy and to sit close!)."], "output": "{'aspect_term': [['privacy', 'positive'], ['corner booth table', 'positive'], ['place', '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 is overpriced and soggy."], "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": ["We've been to Grocery three times and not once has an item on the menu disappointed."], "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": ["The wine list is interesting and has many good values."], "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": ["Overall I was impressed and will return, it's a great QPR (Quality to Price Ratio)."], "output": "{'aspect_term': [['Price', 'positive'], ['Quality', '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": ["This place is worth going even if only for their beer."], "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": ["I would recommend Roxy's for that, but not for their food."], "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": ["Ingredients are organic which is a real plus for me."], "output": "{'aspect_term': [['Ingredients', '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 fact, two people could really share one plate."], "output": "{'aspect_term': [['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": ["If you're looking for a place to sit down, have a drink and conversations with friends, go to sweet-n-tart and order yourself a hong-kong styled milk and tea with tapioca pearls (hot)."], "output": "{'aspect_term': [['drink', 'neutral'], ['hong-kong styled milk', 'positive'], ['tea with tapioca pearls (hot)', 'positive']], 'aspect_category': [[None, 'neutral'], [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": ["Delivery is fast too."], "output": "{'aspect_term': [['Delivery', '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 also special order any kind of dumpling,etc."], "output": "{'aspect_term': [['dumpling', '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 was excellent - friendly and 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": ["Should you happen to be impressed by the cuisine definitely try it."], "output": "{'aspect_term': [['cuisine', '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 thing more wonderful than the food (which is exceptional) is the service."], "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'm partial to the Gnocchi."], "output": "{'aspect_term': [['Gnocchi', '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 some of the reviews here are accurate about the crowd and noise."], "output": "{'aspect_term': [['crowd', 'negative'], ['noise', '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": ["One thing I liked about this place is that I never felt rushed or pressured to give up my table ot incoming guests."], "output": "{'aspect_term': [['table', '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": ["Besides having the table we had been promised given to other restaurant patrons twice before we were actually seated, we were served dishes we hadn't ordered three times, received one of our orders 20 minutes after the rest of the table had been served (and that order was undercooked), and charged $45 more than we should have been on our bill."], "output": "{'aspect_term': [['table', 'negative'], ['served', 'negative'], ['dishes', 'negative'], ['table', 'negative'], ['served', 'negative'], ['bill', 'negative']], 'aspect_category': [[None, 'negative'], [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": ["(food was delivered by a busboy, not waiter) We got no cheese offered for the pasta, our water and wine glasses remained EMPTY our entire meal, when we would have easily spent another $20 on wine."], "output": "{'aspect_term': [['food', 'neutral'], ['busboy', 'negative'], ['waiter', 'negative'], ['cheese', 'negative'], ['pasta', 'negative'], ['water and wine glasses', 'negative'], ['wine', 'neutral'], ['meal', 'neutral']], 'aspect_category': [[None, 'neutral'], [None, 'negative'], [None, 'negative'], [None, 'negative'], [None, 'negative'], [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": ["The spicy tuna and salmon are the best we've ever had."], "output": "{'aspect_term': [['spicy tuna', 'positive'], ['salmon', '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": ["Try the Times Square cocktail -- ginger lemonade with vodka (also available without vodka.)"], "output": "{'aspect_term': [['Times Square cocktail', 'positive'], ['ginger lemonade with vodka', '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 French restaurant in an area devoid of decent restaurants unless you're into eating 4 pound pastrami sandwiches at Katz' Deli, or Mexican food which is supplied by capable restaurants."], "output": "{'aspect_term': [['pastrami sandwiches', 'neutral'], ['Mexican 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": ["But the staff was so horrible to us."], "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": ["It is nearly impossible to get a table, so if you ever have the chance to go here for dinner, DO NOT pass it up."], "output": "{'aspect_term': [['table', 'negative'], ['dinner', '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": ["I went to Del Frisco's Friday night with my boyfriend for an 8:00 reservation."], "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": ["The bagel was huge."], "output": "{'aspect_term': [['bagel', '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 bread is the soft paratha bread (unlike the plain bread they use in Calcutta), and the stuffing is tandoori styled and very flavorful."], "output": "{'aspect_term': [['bread', 'positive'], ['paratha bread', 'positive'], ['bread', 'negative'], ['stuffing', 'positive'], ['tandoori', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [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": ["Please try the Filet Mignon, its just the most tender piece ever."], "output": "{'aspect_term': [['Filet Mignon', '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 above average for midtown and sligtly better than some of the other Heartland Breweries in the city."], "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": ["would have rather tried terrace in the sky or water club for that price"], "output": "{'aspect_term': [['price', '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 staff has always been attentive and kind, and I've always been amazed at how they've handled all the various different group sizes that come in."], "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": ["Just because it's cheap does NOT mean the portions are small or the food is nasty, IT IS GREAT!"], "output": "{'aspect_term': [['portions', '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": ["Meanwhile, the bartender continued to pour champagne from his reserve after we had finished our bottle and we enjoyed an amuse of turnip soup with pureed basil, gratis."], "output": "{'aspect_term': [['bartender', 'positive'], ['champagne', 'neutral'], ['turnip soup with pureed basil', '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": ["The food's as good as ever."], "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": ["Even with a relatively inexpensive botle of wine, if you can call $70.00 inexpensive, the cost is through the roof for better than average fare."], "output": "{'aspect_term': [['cost', 'negative'], ['botle of wine', '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": ["Very excited to hear that short-term Chef Jason Narone has moved on, he truly was a low point of their Sterling track record."], "output": "{'aspect_term': [['Chef', '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 place has good potential, but needs a significant amount of work before we can justify spending that much money on indian food you can get everywhere else."], "output": "{'aspect_term': [['money', 'negative'], ['indian 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 wait staff is very freindly, they make it feel like you're eating in a freindly little european town."], "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": ["Orsay, is a very pleasnt throw back to traditional French food, and French service as well."], "output": "{'aspect_term': [['French 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 really liked the noodle dishes at Rice Avenue compared to their Green Curry dish."], "output": "{'aspect_term': [['noodle dishes', 'positive'], ['Green Curry dish', '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": ["This place has many different styles of pizza and they are all amazing."], "output": "{'aspect_term': [['styles of 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": ["believe us, we've been eating sushi for over 15 yrs."], "output": "{'aspect_term': [['sushi', '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 place was nice and calm."], "output": "{'aspect_term': [['place', '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, I was there for a work dinner not long ago when my colleague from London noticed a very large waterbug on the ceiling."], "output": "{'aspect_term': [['ceiling', 'negative'], ['dinner', '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": ["Their Margarita is best I've had since I've returned from Naples!"], "output": "{'aspect_term': [['Margarita', '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": ["While they keep the capex to a minimum, they do put some cash into the bagels, because they among the best in the city."], "output": "{'aspect_term': [['capex', 'positive'], ['bagels', '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": ["Try the crunchy tuna, it is to die for."], "output": "{'aspect_term': [['crunchy 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": ["Moderate prices."], "output": "{'aspect_term': [['prices', '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": ["Wow over 100 beers to choose from."], "output": "{'aspect_term': [['beers', '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 BIG COMPLAINT: NO TOASTING AVAILABLE."], "output": "{'aspect_term': [['TOASTING', '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 quality of food at this restaurant accompanied  by fantastic live jazz makes this place a perfect 10!"], "output": "{'aspect_term': [['quality of food', 'positive'], ['live jazz', '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 pizza was soggy and the creative wild mushroom(third generation-Fornini) pizza we had was drenched with truffle oil in the middle( again making it soggy) and nothingon the rest."], "output": "{'aspect_term': [['plain pizza', 'negative'], ['truffle oil', 'neutral'], ['wild mushroom(third generation-Fornini) pizza', 'positive']], 'aspect_category': [[None, 'negative'], [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 selection changes frequently but the basic dishes are always available."], "output": "{'aspect_term': [['selection', 'neutral'], ['basic dishes', '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": ["I've had pizza both times and the caprese salad appetizer."], "output": "{'aspect_term': [['pizza', 'neutral'], ['caprese salad appetizer', '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": ["While the new restaurant still features much of the same classical furniture that made Tiffin so attractive, the menu has been overhauled."], "output": "{'aspect_term': [['classical furniture', 'positive'], ['menu', '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 wife and i have been going to nyc for years and wouldn't miss roxy,s food is expensive but it's new york!"], "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": ["When you're sitting in their main dining room (which has a spectacular, hand-painted high ceiling) you'd never know there was a world outside."], "output": "{'aspect_term': [['main dining room', 'positive'], ['ceiling', '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": ["Just straight up cheap, 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": ["Our server was very helpful and friendly."], "output": "{'aspect_term': [['server', '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, specify if you like your food spicy- its rather bland if you don't."], "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": ["After dealing with subpar pizza all over the Kensington neighborhood - I've found little toninos."], "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": ["I understand the area and folks you need not come here for the romantic, alluring ambiance or the five star service featuring a sommlier and a complicated maze of captain and back waiters - you come for the authentic foods, the tastes, the experiance."], "output": "{'aspect_term': [['ambiance', 'positive'], ['service', 'positive'], ['foods', 'positive'], ['tastes', 'positive'], ['sommlier', 'positive'], ['captain', 'positive'], ['back waiters', 'positive']], 'aspect_category': [[None, 'positive'], [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": ["Taxan delicious!"], "output": "{'aspect_term': [['Taxan', '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": ["Spreads and toppings are great - though a bit pricey."], "output": "{'aspect_term': [['Spreads', '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": ["Total hipster-wannabe attitude in an otherwise sweet spot."], "output": "{'aspect_term': [['spot', '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 a downside if you're ordering in -- the delivery guys have MAJOR attitude."], "output": "{'aspect_term': [['delivery guys', '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": ["Regardless of whether there are two people or two hundred people ahead of you the hostess will take your name and tell you Five minutes."], "output": "{'aspect_term': [['hostess', '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 food and the prices are very 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": ["We had Pam's special fried fish and it was amazing."], "output": "{'aspect_term': [[\"Pam's special fried fish\", '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 on a 3 day oyster binge, with Fish bringing up the closing, and I am so glad this was the place it O trip ended, because it was so great!"], "output": "{'aspect_term': [['place', 'positive'], ['oyster', 'neutral'], ['Fish', 'neutral']], 'aspect_category': [[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": ["Late nite omelletes are not good here, there is no variety!"], "output": "{'aspect_term': [['omelletes', '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 a shame that a nice, convenient place like the Pink Pony can be so ruined by lousy service."], "output": "{'aspect_term': [['place', '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": ["The food now is inconsistent."], "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": ["A Thai restaurant out of rice during dinner?"], "output": "{'aspect_term': [['rice', 'neutral'], ['dinner', '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": ["As there were so many to choose from we wandered up and down the street looking in the windows and such noticicing many empty seats ,except at Taj Mahal."], "output": "{'aspect_term': [['seats', '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 friendly and the atmosphere was casual."], "output": "{'aspect_term': [['service', 'positive'], ['atmosphere', '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": ["If you've ever been along the river in Weehawken you have an idea of the top of view the chart house has to offer."], "output": "{'aspect_term': [['view', '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 wouldn't even have complained at all if the food at least tasted good but the quality of food was crappy, too."], "output": "{'aspect_term': [['food', 'negative'], ['quality of 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": ["I liked the food at this quasi-thai restaurant."], "output": "{'aspect_term': [['food', 'positive'], ['quasi-thai', '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 was prompt, friendly and great."], "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": ["Service is average."], "output": "{'aspect_term': [['Service', '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": ["NO more reservations, expensive tips and annoying stuff."], "output": "{'aspect_term': [['reservations', 'positive'], ['tips', 'positive'], ['stuff', '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 Thai food is good."], "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": ["Check out the secret back room."], "output": "{'aspect_term': [['secret back room', '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": ["Note that they do not serve beer, you must bring your own."], "output": "{'aspect_term': [['beer', '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": ["But that wasn't the icing on the cake: a tiramisu that resembled nothing I have ever had."], "output": "{'aspect_term': [['icing on the cake', 'negative'], ['tiramisu', '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": ["Service is friendly, prices are good - delivery time was a little slow, but for the way this pizza tastes, I'm willing to overlook it."], "output": "{'aspect_term': [['Service', 'positive'], ['prices', 'positive'], ['delivery time', 'negative'], ['pizza', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'positive'], [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 large selection of bruschettas, paninis, tramezzinis keep the palate from stagnating."], "output": "{'aspect_term': [['bruschettas', 'positive'], ['paninis', 'positive'], ['tramezzinis', '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": ["For two people with tip was less than $25 bucks."], "output": "{'aspect_term': [['tip', '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": ["Of course this atmosphere is lacking, but what do you expect from a 24 hour bagel place anyways?"], "output": "{'aspect_term': [['atmosphere', 'negative'], ['bagel', '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 fried dumplings are GREAT!"], "output": "{'aspect_term': [['fried dumplings', '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 wine, great food."], "output": "{'aspect_term': [['wine', '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": ["Looking around, I saw a room full of New Yorkers enjoying a real meal in a real restaurant, not a clubhouse of the fabulous trying to be seen."], "output": "{'aspect_term': [['meal', 'positive'], ['room', 'neutral'], ['clubhouse', 'negative']], 'aspect_category': [[None, 'positive'], [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": ["Incredible food at a very agreable price brings me back just about every other day to this authentic Thai restaurant."], "output": "{'aspect_term': [['food', '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": ["You must have the crabmeat lasagna which is out of this world and the chocolate bread pudding for dessert."], "output": "{'aspect_term': [['crabmeat lasagna', 'positive'], ['chocolate bread pudding', 'positive'], ['dessert', '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": ["We were told that the wait was about twenty minutes and there would be no problem for our 8:00 pm curtain call."], "output": "{'aspect_term': [['wait', '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": ["Winnie and her staff are the best crew you can find serving you."], "output": "{'aspect_term': [['crew', 'positive'], ['staff', 'positive'], ['serving', '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 food is awesome - definitely try the striped bass."], "output": "{'aspect_term': [['food', 'positive'], ['striped bass', '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, served in small tasting portions (as an option) is very good with each dish being better than the next."], "output": "{'aspect_term': [['food', 'positive'], ['served', 'neutral'], ['portions', 'positive'], ['dish', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'neutral'], [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": ["Last memorial day, I tried to make reservations but was told they were closed that weekend (interesting, but...)."], "output": "{'aspect_term': [['reservations', '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": ["Make reservations but expect to be delayed 15-20 minutes as the hosting staff was having difficulty seating guests who arrived with a reservation because they probably had a lot of walk ins being so close to Time Square."], "output": "{'aspect_term': [['hosting staff', 'negative'], ['reservations', 'negative'], ['reservation', 'neutral'], ['seating', 'negative']], 'aspect_category': [[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": ["The Steak Tartare is a great bet, they fix it for you at the table."], "output": "{'aspect_term': [['Steak Tartare', '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 never brought us complimentary noodles, ignored repeated requests for sugar, and threw our dishes on the table."], "output": "{'aspect_term': [['noodles', 'negative'], ['sugar', 'negative'], ['dishes', '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": ["I had a huge pastrami sandwich on a roll."], "output": "{'aspect_term': [['pastrami 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": ["Overall A oh ya even though there is waiting it is deff worth it"], "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": ["The in-house lady DJ on Saturday nights has outrageously good taste in music, and moreover, takes requests."], "output": "{'aspect_term': [['music', 'positive'], ['in-house lady DJ', '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 also seated promptly at the time of our reservation and the service was very quick and professional."], "output": "{'aspect_term': [['service', 'positive'], ['reservation', '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": ["Always popular, always full, always a wait."], "output": "{'aspect_term': [['wait', '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 dim sum however was very good."], "output": "{'aspect_term': [['dim sum', '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": ["Prices are very good."], "output": "{'aspect_term': [['Prices', '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 red sliding doors may be unique but they do not block off the cold air from the outside."], "output": "{'aspect_term': [['doors', '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": ["(and I have eaten my share) Which impresses me for having such a large amount of people to serve."], "output": "{'aspect_term': [['serve', '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 waitress was very patient with us and the food is phenomenal!"], "output": "{'aspect_term': [['waitress', '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 service is good and ambience is good for a date or group outing."], "output": "{'aspect_term': [['service', 'positive'], ['ambience', '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 don't seem to place an emphasis on specials or fresh ingredients which to me is necessary for good thai."], "output": "{'aspect_term': [['specials', 'negative'], ['ingredients', 'negative'], ['thai', 'neutral']], 'aspect_category': [[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": ["We won't go to this place again for a good meal."], "output": "{'aspect_term': [['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": ["We had reservations at 9pm, but was not seated until 10:15pm."], "output": "{'aspect_term': [['reservations', '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 steak was excellent and one of the best I have had (I tasted the butter intitally but in no way did it overwhelm the flavor of the meat)."], "output": "{'aspect_term': [['steak', 'positive'], ['butter', 'negative'], ['flavor', 'neutral'], ['meat', 'positive']], 'aspect_category': [[None, 'positive'], [None, 'negative'], [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": ["Plain and simple it's bad thai food."], "output": "{'aspect_term': [['thai 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": ["I have been there many times, and food is good and consistent."], "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": ["We were seated and ignored by waitstaff."], "output": "{'aspect_term': [['waitstaff', '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": ["Anyway, the food is good, the price is right and they have a decent wine list."], "output": "{'aspect_term': [['food', 'positive'], ['price', 'positive'], ['wine list', '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": ["We were told that they were booked solid and no other table was available."], "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": ["The prices are wonderfully low."], "output": "{'aspect_term': [['prices', '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 was attentive without being overbearing and each dish we tried was wonderful from the spring rolls to the cod with pineapple tempura."], "output": "{'aspect_term': [['service', 'positive'], ['dish', 'positive'], ['spring rolls', 'positive'], ['cod with pineapple tempura', '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": ["There are much better places in NY with better prices."], "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": ["Hats off to the chef."], "output": "{'aspect_term': [['chef', '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 delicious and the waiter was incredibly helpful and attentive (considering we were the only ones there for the first hour)."], "output": "{'aspect_term': [['food', 'positive'], ['waiter', '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 sauce on the pizza is sooo good with garlic and fresh tomatoes and they don't skimp."], "output": "{'aspect_term': [['garlic', 'positive'], ['fresh tomatoes', 'positive'], ['sauce on the 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": ["it's a perfect place to have a amanzing indian food."], "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": ["It's easy to get a table for a large group and you don't get hustled out."], "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": ["If you are someone who appreciates simplicity, elegance, and wonderfully presented and tasting seafood and vegetables regardless of portion size, Kai is your place."], "output": "{'aspect_term': [['seafood', 'positive'], ['vegetables', 'positive'], ['portion size', 'negative']], 'aspect_category': [[None, 'positive'], [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 highly recommend Caviar Russe to anyone who wants delicious top grade caviar and fantastic service."], "output": "{'aspect_term': [['caviar', '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 ordered a Chicken Teriyaki dish and found that the chicken was extremely dry."], "output": "{'aspect_term': [['Chicken Teriyaki dish', 'negative'], ['chicken', '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": ["I almost hesititate to write a review because the atmosphere was so great and I would hate for it too become to crowded."], "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": ["The restaurant was packed at first, so we waited at the bar for about 20 minutes before we were seated."], "output": "{'aspect_term': [['bar', '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": ["We shared a bottle of sake, an order of edamames, and she had the sushi plate while I had the sashimi."], "output": "{'aspect_term': [['bottle of sake', 'neutral'], ['edamames', 'neutral'], ['sushi plate', 'neutral'], ['sashimi', '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": ["The wait staff is pleasant, fun, and for the most part gorgeous (in the wonderful aesthetic beautification way, not in that she's-way-cuter-than-me-that-b@#$* way)."], "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": ["Wine list selection is good and wine-by-the-glass was generously filled to the top."], "output": "{'aspect_term': [['Wine list selection', 'positive'], ['wine-by-the-glass', '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": ["Don't dine at Tamarind for the vegetarian dishes, they are simply not up to par with the non-veg selections."], "output": "{'aspect_term': [['vegetarian dishes', 'negative'], ['non-veg selections', '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": ["My wife had the fried shrimp which are huge and loved it."], "output": "{'aspect_term': [['fried shrimp', '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 is so easy to get a reservation at a top place in NYC with a week's notice."], "output": "{'aspect_term': [['reservation', '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 part of the experience was knowing that the manager (a bubbly, friendly young woman with a great smile) truly cared about how we were doing."], "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": ["The calamari comes with an incredible sauce, and the duck noodles are yummy as well."], "output": "{'aspect_term': [['calamari', 'positive'], ['sauce', 'positive'], ['duck noodles', '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 menu is Prix Fixe, so be prepared to spend at least $60 per person, but it is Well worth itsuperb food."], "output": "{'aspect_term': [['menu', 'negative'], ['food', 'positive'], ['Prix Fixe', 'neutral']], 'aspect_category': [[None, 'negative'], [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": ["Wine list is not huge but def well selected."], "output": "{'aspect_term': [['Wine list', '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": ["Instead of wasting your time here: SUPPORT RESTAURANTS THAT CARE ABOUT 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": ["The drinks are always welll made and wine selection is fairly priced."], "output": "{'aspect_term': [['drinks', 'positive'], ['wine selection', 'neutral'], ['priced', '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": ["I haven't eat a lamb chop as delicious as that,the salads are really nice dressed with lemon and extra virgnin olive oil."], "output": "{'aspect_term': [['lamb chop', 'positive'], ['salads', 'positive'], ['lemon', 'positive'], ['extra virgnin olive oil', '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": ["We were still sitting at the bar while we drank the sangria, but facing away from the bar when we turned back around, the $2 was gone the people next to us said the bartender took it."], "output": "{'aspect_term': [['sangria', 'neutral'], ['bar', 'neutral'], ['bar', 'neutral'], ['bartender', 'negative']], 'aspect_category': [[None, 'neutral'], [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']]} "}