NEUDM/aste-data-v2 · Datasets at Hugging Face

task_type stringclasses 1 value	dataset stringclasses 1 value	input list	output stringlengths 28 294	situation stringclasses 1 value	instruction stringclasses 1 value
generation	aste-data-v2	[ "The drinks are a saving grace , but service staff , please , get over yourselves ." ]	[['drinks', 'saving grace', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "There is a downside if you 're ordering in -- the delivery guys have MAJOR attitude ." ]	[['delivery guys', 'downside', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The all-Italian staff is warm and engaging from the start ." ]	[['staff', 'warm', 'positive'], ['staff', 'engaging', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The prices are exceptionally reasonable for food of this caliber ." ]	[['prices', 'reasonable', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The filet mignon dish was superb !" ]	[['filet mignon dish', 'superb', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "I had been a regular due to the consistently good food and ease of getting a table ." ]	[['food', 'good', 'positive'], ['getting a table', 'ease', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "I did n't expect to like Nosh as much as I did , but the pastrami on challah sandwich I had was otherworldly , the soups are like Mom 's , and the knishes give Yonah Schimmel 's a run for its money ." ]	[['pastrami on challah sandwich', 'otherworldly', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The atmosphere is nothing special , but it feels like a Sushi establishment in Tokyo ." ]	[['atmosphere', 'nothing special', 'neutral']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Cozy romantic atomosphere with only around 15 tables at most ." ]	[['atomosphere', 'Cozy romantic', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "This place is worth going even if only for their beer ." ]	[['beer', 'worth going', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The ambience was so fun , and the prices were great , on top of the fact that the food was really tasty ." ]	[['ambience', 'fun', 'positive'], ['prices', 'great', 'positive'], ['food', 'tasty', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The sandwhiches are out of this world !" ]	[['sandwhiches', 'out of this world', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Decor is charming ." ]	[['Decor', 'charming', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The food was very well prepared ." ]	[['food', 'well prepared', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Good , because hey , it 's more food , but bad because dim sum is supposed to be smaller portions so you can try out more dishes and smaller so that each dish is cheap ." ]	[['dim sum', 'bad', 'negative'], ['dim sum', 'smaller', 'negative'], ['food', 'more', 'positive'], ['portions', 'smaller', 'negative'], ['dishes', 'cheap', 'neutral'], ['dish', 'cheap', 'neutral']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "While most people can attest to spending over $ 50 on drinks in New York bars and hardly feeling a thing , the drinks here are plentiful and unique ." ]	[['drinks', 'plentiful', 'positive'], ['drinks', 'unique', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "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 ." ]	[['stuff', 'Complimentary', 'positive'], ['staff', 'attentive', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The food arrived 20 minutes after I called , cold and soggy ." ]	[['food', 'cold', 'negative'], ['food', 'soggy', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "If you go for the pre-theatre menu , it 's an even greater deal ." ]	[['pre-theatre menu', 'greater', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "If you are someone who appreciates simplicity , elegance , and wonderfully presented and tasting seafood and vegetables regardless of portion size , Kai is your place ." ]	[['seafood', 'wonderfully presented', 'positive'], ['seafood', 'tasting', 'positive'], ['vegetables', 'wonderfully presented', 'positive'], ['vegetables', 'tasting', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "We usually just get some of the dinner specials and they are very reasonably priced and very tasty ." ]	[['dinner specials', 'reasonably priced', 'positive'], ['dinner specials', 'tasty', 'positive'], ['priced', 'reasonably', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Horrible food and horrible service ." ]	[['food', 'Horrible', 'negative'], ['service', 'horrible', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "They treated us well and the food was extremely fresh and well-prepared ." ]	[['food', 'fresh', 'positive'], ['food', 'well-prepared', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Their exotic salad is basic ly a delicious little green salad with a peanut sauce that is perfect before their sweet basil fried tofu ." ]	[['exotic salad', 'delicious', 'positive'], ['green salad', 'delicious little', 'positive'], ['peanut sauce', 'perfect', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Even if the food was n't this good , the garden is a great place to sit outside and relax ." ]	[['food', "was n't this good", 'positive'], ['garden', 'great', 'positive'], ['place', 'great', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Volare virgins or weekly regulars , everyone gets treated the same and you ca n't ask for more than that when the service is this friendly ." ]	[['service', 'friendly', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The food came out wrong , the waiter was no where to be found and the wine showed up at the end of the meal ." ]	[['food', 'wrong', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The chicken and steak were seasoned and cooked to perfection , and the lamb sandwhich is great for heartier appetites ." ]	[['chicken', 'seasoned', 'positive'], ['chicken', 'perfection', 'positive'], ['steak', 'seasoned', 'positive'], ['steak', 'perfection', 'positive'], ['lamb sandwhich', 'great', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The food was great and the service was even better ." ]	[['food', 'great', 'positive'], ['service', 'better', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "While this can hardly be called a restaurant , it is possibly the best deal in Manhatten : $ 4 for a plate heaped with rice and 2-3 entrees ." ]	[['rice', 'best', 'positive'], ['entrees', 'best', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "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 ." ]	[['Traditional French decour', 'pleasant', 'positive'], ['hall', 'noisy', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "My son and his girlfriend both wanted cheeseburgers and they were huge !" ]	[['cheeseburgers', 'huge', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "I really recommend the very simple Unda ( Egg ) rolls ." ]	[['Unda ( Egg ) rolls', 'recommend', 'positive'], ['Unda ( Egg ) rolls', 'simple', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Very good wine choices ." ]	[['wine choices', 'good', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "This is the only Thai place I go too in NYC , it 's wonderful , and live relaxed Jazz on certain nights ." ]	[['Jazz', 'relaxed', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "We were seated and ignored by waitstaff ." ]	[['waitstaff', 'ignored', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Tasty steak , pork loin , the works ." ]	[['steak', 'Tasty', 'positive'], ['pork loin', 'Tasty', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "I 'd highly recommend it for a special occasion -- it provides and intimate setting and nice service ." ]	[['setting', 'intimate', 'positive'], ['service', 'nice', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The burger was great , also ." ]	[['burger', 'great', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "they did give a 15 % discount at the end , was n't enough , as they knew the service was horrible ." ]	[['discount', "was n't enough", 'negative'], ['service', 'horrible', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The pizza was great ." ]	[['pizza', 'great', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "I had never had Edamame pureed before but I thought it was innovative and tasty ( could 've used a bit more salt ) ." ]	[['Edamame pureed', 'innovative', 'positive'], ['Edamame pureed', 'tasty', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "however , it 's the service that leaves a bad taste in my mouth ." ]	[['service', 'bad taste', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The price was extremely reasonable for the appetizers and food we ate ." ]	[['price', 'reasonable', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Do n't dine at Tamarind for the vegetarian dishes , they are simply not up to par with the non-veg selections ." ]	[['vegetarian dishes', 'not up to par', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "They need a kick out of it but until then the sushi is pretty good and the place is consistent ." ]	[['sushi', 'good', 'positive'], ['place', 'consistent', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "I 've had to wait only a few times during lunch but this place is definitely worth the wait ." ]	[['wait', 'worth', 'positive'], ['wait', 'worth the wait', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "All in all the food was above average and I would return to see how they operate with four or less dinners ." ]	[['food', 'above average', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Delicious food , excellent service , and a pretty atmosphere make this a great choice for dinner and the $ 5.99 lunch buffet makes it an even better choice for lunch !" ]	[['food', 'Delicious', 'positive'], ['service', 'excellent', 'positive'], ['atmosphere', 'pretty', 'positive'], ['lunch buffet', 'better', 'positive'], ['dinner', 'great', 'positive'], ['lunch', 'better', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "For appetizers , I recommend the shrimp fritters and dumplings ." ]	[['shrimp fritters', 'recommend', 'positive'], ['dumplings', 'recommend', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Such nice people working here - but I have to review the food ." ]	[['people', 'nice', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The restaurant is dark and not very attractive and then you have spot lights shining on you putting you in the worst light possible , reaching for sunglasses ." ]	[['spot lights', 'worst', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Great wine , great food ." ]	[['wine', 'Great', 'positive'], ['food', 'great', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The service was mediocre , and the lack of air conditioning made for a less than comfortable meal ." ]	[['service', 'mediocre', 'neutral'], ['air conditioning', 'lack', 'negative'], ['meal', 'comfortable', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The food and staff always surprise me with the new heights they are taken to ." ]	[['food', 'surprise', 'positive'], ['staff', 'surprise', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "honestly the worst sushi my husband and i had in our entire lives ." ]	[['sushi', 'worst', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "However , if you want great food at a great price and do n't mind the decor , you ca n't beat this place ." ]	[['food', 'great', 'positive'], ['price', 'great', 'positive'], ['decor', "do n't mind", 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "What makes this restaurant special are the authentic sichuan cooking and being the only one in NYC that offers authentic chongqing hotpot ." ]	[['sichuan cooking', 'authentic', 'positive'], ['chongqing hotpot', 'authentic', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Interesting other dishes for a change include chicken in curry sauce and salmon caserole ." ]	[['dishes', 'Interesting', 'positive'], ['salmon caserole', 'Interesting', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "One of my favorites though was the Angry Lobster , a cold lobster salad that was magnificent ." ]	[['Angry Lobster', 'favorites', 'positive'], ['cold lobster salad', 'magnificent', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Ask for Usha , the nicest bartender in manhattan ." ]	[['bartender', 'nicest', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The service is outstanding and my crab-cake eggs benedict could not have been better ." ]	[['service', 'outstanding', 'positive'], ['crab-cake eggs benedict', 'could not have been better', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The place 's decor and hidden bathrooms made for a good laugh ." ]	[['decor', 'good laugh', 'positive'], ['bathrooms', 'good laugh', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Its location is good and the fact that Hutner College is near and their prices are very reasonable , makes students go back to Suan again and again ." ]	[['location', 'good', 'positive'], ['prices', 'reasonable', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Deliveries often take up to an hour and the prices are higher than most other pizzerias in the area ." ]	[['prices', 'higher', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Because of the delicate thin crust , take-out pies get soggy in their boxes ." ]	[['take-out pies', 'soggy', 'negative'], ['crust', 'delicate', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "This place is always very crowded and popular ." ]	[['place', 'crowded', 'positive'], ['place', 'popular', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The selection changes frequently but the basic dishes are always available ." ]	[['selection', 'changes frequently', 'neutral'], ['basic dishes', 'available', 'neutral']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "I have to say that if this what makes it easier to get a saet a lunch -- I dont mind ." ]	[['lunch', 'easier', 'neutral']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "We were told that they were booked solid and no other table was available ." ]	[['table', 'available', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "After dealing with subpar pizza all over the Kensington neighborhood - I 've found little toninos ." ]	[['pizza', 'subpar', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "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 ." ]	[['meats', 'thin', 'neutral'], ['vegetables', 'various', 'neutral']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Judging from previous posts this used to be a good place , but not any longer ." ]	[['place', 'good', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "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 ." ]	[['staff', 'rude', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The food was lousy - too sweet or too salty and the portions tiny ." ]	[['food', 'lousy', 'negative'], ['food', 'too sweet', 'negative'], ['food', 'too salty', 'negative'], ['portions', 'tiny', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Avoid this place !" ]	[['place', 'Avoid', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "I have eaten at Saul , many times , the food is always consistently , outrageously good ." ]	[['food', 'good', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Saul is the best restaurant on Smith Street and in Brooklyn ." ]	[['Saul', 'best', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The duck confit is always amazing and the foie gras terrine with figs was out of this world ." ]	[['foie gras terrine with figs', 'out of this world', 'positive'], ['duck confit', 'amazing', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The wine list is interesting and has many good values ." ]	[['wine list', 'interesting', 'positive'], ['wine list', 'good values', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "I was very disappointed with this restaurant ." ]	[['restaurant', 'disappointed', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Food was okay , nothing great ." ]	[['Food', 'okay', 'neutral'], ['Food', 'nothing great', 'neutral']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Chow fun was dry ; pork shu mai was more than usually greasy and had to share a table with loud and rude family ." ]	[['Chow fun', 'dry', 'negative'], ['pork shu mai', 'greasy', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "I/we will never go back to this place again ." ]	[['place', 'never go back', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Service was devine , oysters where a sensual as they come , and the price ca n't be beat ! ! !" ]	[['Service', 'devine', 'positive'], ['oysters', 'sensual', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Everything is always cooked to perfection , the service is excellent , the decor cool and understated ." ]	[['service', 'excellent', 'positive'], ['decor', 'cool', 'positive'], ['decor', 'understated', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "I had the duck breast special on my last visit and it was incredible ." ]	[['duck breast special', 'incredible', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The only thing I moderately enjoyed was their Grilled Chicken special with Edamame Puree ." ]	[['Grilled Chicken special with Edamame Puree', 'enjoyed', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "I had never had Edamame pureed before but I thought it was innovative and tasty ( could 've used a bit more salt ) ." ]	[['Edamame pureed', 'innovative', 'positive'], ['Edamame pureed', 'tasty', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Their sake list was extensive , but we were looking for Purple Haze , which was n't listed but made for us upon request !" ]	[['sake list', 'extensive', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "We went around 9:30 on a Friday and it had died down a bit by then so the service was great !" ]	[['service', 'great', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Food awesome ." ]	[['Food', 'awesome', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Service friendly and attentive ." ]	[['Service', 'friendly', 'positive'], ['Service', 'attentive', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "the food is decent ." ]	[['food', 'decent', 'neutral']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "This place has got to be the best japanese restaurant in the new york area ." ]	[['place', 'best', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Food is great ." ]	[['Food', 'great', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Service is top notch ." ]	[['Service', 'top notch', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "We took advanatage of the half price sushi deal on saturday so it was well worth it ." ]	[['half price sushi deal', 'worth', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "In the evening , this place attracted a well dressed , with it , NY crowd ." ]	[['crowd', 'attracted', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "$ 6 and there is much tasty food , all of it fresh and continually refilled ." ]	[['food', 'tasty', 'positive'], ['food', 'fresh', 'positive'], ['food', 'refilled', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The drinks are a saving grace , but service staff , please , get over yourselves ." ]

[['drinks', 'saving grace', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "There is a downside if you 're ordering in -- the delivery guys have MAJOR attitude ." ]

[['delivery guys', 'downside', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The all-Italian staff is warm and engaging from the start ." ]

[['staff', 'warm', 'positive'], ['staff', 'engaging', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The prices are exceptionally reasonable for food of this caliber ." ]

[['prices', 'reasonable', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The filet mignon dish was superb !" ]

[['filet mignon dish', 'superb', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "I had been a regular due to the consistently good food and ease of getting a table ." ]

[['food', 'good', 'positive'], ['getting a table', 'ease', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "I did n't expect to like Nosh as much as I did , but the pastrami on challah sandwich I had was otherworldly , the soups are like Mom 's , and the knishes give Yonah Schimmel 's a run for its money ." ]

[['pastrami on challah sandwich', 'otherworldly', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The atmosphere is nothing special , but it feels like a Sushi establishment in Tokyo ." ]

[['atmosphere', 'nothing special', 'neutral']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Cozy romantic atomosphere with only around 15 tables at most ." ]

[['atomosphere', 'Cozy romantic', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "This place is worth going even if only for their beer ." ]

[['beer', 'worth going', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The ambience was so fun , and the prices were great , on top of the fact that the food was really tasty ." ]

[['ambience', 'fun', 'positive'], ['prices', 'great', 'positive'], ['food', 'tasty', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The sandwhiches are out of this world !" ]

[['sandwhiches', 'out of this world', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Decor is charming ." ]

[['Decor', 'charming', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The food was very well prepared ." ]

[['food', 'well prepared', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Good , because hey , it 's more food , but bad because dim sum is supposed to be smaller portions so you can try out more dishes and smaller so that each dish is cheap ." ]

[['dim sum', 'bad', 'negative'], ['dim sum', 'smaller', 'negative'], ['food', 'more', 'positive'], ['portions', 'smaller', 'negative'], ['dishes', 'cheap', 'neutral'], ['dish', 'cheap', 'neutral']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "While most people can attest to spending over $ 50 on drinks in New York bars and hardly feeling a thing , the drinks here are plentiful and unique ." ]

[['drinks', 'plentiful', 'positive'], ['drinks', 'unique', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "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 ." ]

[['stuff', 'Complimentary', 'positive'], ['staff', 'attentive', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The food arrived 20 minutes after I called , cold and soggy ." ]

[['food', 'cold', 'negative'], ['food', 'soggy', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "If you go for the pre-theatre menu , it 's an even greater deal ." ]

[['pre-theatre menu', 'greater', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "If you are someone who appreciates simplicity , elegance , and wonderfully presented and tasting seafood and vegetables regardless of portion size , Kai is your place ." ]

[['seafood', 'wonderfully presented', 'positive'], ['seafood', 'tasting', 'positive'], ['vegetables', 'wonderfully presented', 'positive'], ['vegetables', 'tasting', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "We usually just get some of the dinner specials and they are very reasonably priced and very tasty ." ]

[['dinner specials', 'reasonably priced', 'positive'], ['dinner specials', 'tasty', 'positive'], ['priced', 'reasonably', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Horrible food and horrible service ." ]

[['food', 'Horrible', 'negative'], ['service', 'horrible', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "They treated us well and the food was extremely fresh and well-prepared ." ]

[['food', 'fresh', 'positive'], ['food', 'well-prepared', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Their exotic salad is basic ly a delicious little green salad with a peanut sauce that is perfect before their sweet basil fried tofu ." ]

[['exotic salad', 'delicious', 'positive'], ['green salad', 'delicious little', 'positive'], ['peanut sauce', 'perfect', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Even if the food was n't this good , the garden is a great place to sit outside and relax ." ]

[['food', "was n't this good", 'positive'], ['garden', 'great', 'positive'], ['place', 'great', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Volare virgins or weekly regulars , everyone gets treated the same and you ca n't ask for more than that when the service is this friendly ." ]

[['service', 'friendly', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The food came out wrong , the waiter was no where to be found and the wine showed up at the end of the meal ." ]

[['food', 'wrong', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The chicken and steak were seasoned and cooked to perfection , and the lamb sandwhich is great for heartier appetites ." ]

[['chicken', 'seasoned', 'positive'], ['chicken', 'perfection', 'positive'], ['steak', 'seasoned', 'positive'], ['steak', 'perfection', 'positive'], ['lamb sandwhich', 'great', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The food was great and the service was even better ." ]

[['food', 'great', 'positive'], ['service', 'better', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "While this can hardly be called a restaurant , it is possibly the best deal in Manhatten : $ 4 for a plate heaped with rice and 2-3 entrees ." ]

[['rice', 'best', 'positive'], ['entrees', 'best', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "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 ." ]

[['Traditional French decour', 'pleasant', 'positive'], ['hall', 'noisy', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "My son and his girlfriend both wanted cheeseburgers and they were huge !" ]

[['cheeseburgers', 'huge', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "I really recommend the very simple Unda ( Egg ) rolls ." ]

[['Unda ( Egg ) rolls', 'recommend', 'positive'], ['Unda ( Egg ) rolls', 'simple', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Very good wine choices ." ]

[['wine choices', 'good', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "This is the only Thai place I go too in NYC , it 's wonderful , and live relaxed Jazz on certain nights ." ]

[['Jazz', 'relaxed', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "We were seated and ignored by waitstaff ." ]

[['waitstaff', 'ignored', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Tasty steak , pork loin , the works ." ]

[['steak', 'Tasty', 'positive'], ['pork loin', 'Tasty', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "I 'd highly recommend it for a special occasion -- it provides and intimate setting and nice service ." ]

[['setting', 'intimate', 'positive'], ['service', 'nice', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The burger was great , also ." ]

[['burger', 'great', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "they did give a 15 % discount at the end , was n't enough , as they knew the service was horrible ." ]

[['discount', "was n't enough", 'negative'], ['service', 'horrible', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The pizza was great ." ]

[['pizza', 'great', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "I had never had Edamame pureed before but I thought it was innovative and tasty ( could 've used a bit more salt ) ." ]

[['Edamame pureed', 'innovative', 'positive'], ['Edamame pureed', 'tasty', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "however , it 's the service that leaves a bad taste in my mouth ." ]

[['service', 'bad taste', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The price was extremely reasonable for the appetizers and food we ate ." ]

[['price', 'reasonable', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Do n't dine at Tamarind for the vegetarian dishes , they are simply not up to par with the non-veg selections ." ]

[['vegetarian dishes', 'not up to par', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "They need a kick out of it but until then the sushi is pretty good and the place is consistent ." ]

[['sushi', 'good', 'positive'], ['place', 'consistent', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "I 've had to wait only a few times during lunch but this place is definitely worth the wait ." ]

[['wait', 'worth', 'positive'], ['wait', 'worth the wait', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "All in all the food was above average and I would return to see how they operate with four or less dinners ." ]

[['food', 'above average', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Delicious food , excellent service , and a pretty atmosphere make this a great choice for dinner and the $ 5.99 lunch buffet makes it an even better choice for lunch !" ]

[['food', 'Delicious', 'positive'], ['service', 'excellent', 'positive'], ['atmosphere', 'pretty', 'positive'], ['lunch buffet', 'better', 'positive'], ['dinner', 'great', 'positive'], ['lunch', 'better', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "For appetizers , I recommend the shrimp fritters and dumplings ." ]

[['shrimp fritters', 'recommend', 'positive'], ['dumplings', 'recommend', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Such nice people working here - but I have to review the food ." ]

[['people', 'nice', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The restaurant is dark and not very attractive and then you have spot lights shining on you putting you in the worst light possible , reaching for sunglasses ." ]

[['spot lights', 'worst', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Great wine , great food ." ]

[['wine', 'Great', 'positive'], ['food', 'great', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The service was mediocre , and the lack of air conditioning made for a less than comfortable meal ." ]

[['service', 'mediocre', 'neutral'], ['air conditioning', 'lack', 'negative'], ['meal', 'comfortable', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The food and staff always surprise me with the new heights they are taken to ." ]

[['food', 'surprise', 'positive'], ['staff', 'surprise', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "honestly the worst sushi my husband and i had in our entire lives ." ]

[['sushi', 'worst', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "However , if you want great food at a great price and do n't mind the decor , you ca n't beat this place ." ]

[['food', 'great', 'positive'], ['price', 'great', 'positive'], ['decor', "do n't mind", 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "What makes this restaurant special are the authentic sichuan cooking and being the only one in NYC that offers authentic chongqing hotpot ." ]

[['sichuan cooking', 'authentic', 'positive'], ['chongqing hotpot', 'authentic', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Interesting other dishes for a change include chicken in curry sauce and salmon caserole ." ]

[['dishes', 'Interesting', 'positive'], ['salmon caserole', 'Interesting', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "One of my favorites though was the Angry Lobster , a cold lobster salad that was magnificent ." ]

[['Angry Lobster', 'favorites', 'positive'], ['cold lobster salad', 'magnificent', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Ask for Usha , the nicest bartender in manhattan ." ]

[['bartender', 'nicest', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The service is outstanding and my crab-cake eggs benedict could not have been better ." ]

[['service', 'outstanding', 'positive'], ['crab-cake eggs benedict', 'could not have been better', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The place 's decor and hidden bathrooms made for a good laugh ." ]

[['decor', 'good laugh', 'positive'], ['bathrooms', 'good laugh', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Its location is good and the fact that Hutner College is near and their prices are very reasonable , makes students go back to Suan again and again ." ]

[['location', 'good', 'positive'], ['prices', 'reasonable', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Deliveries often take up to an hour and the prices are higher than most other pizzerias in the area ." ]

[['prices', 'higher', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Because of the delicate thin crust , take-out pies get soggy in their boxes ." ]

[['take-out pies', 'soggy', 'negative'], ['crust', 'delicate', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "This place is always very crowded and popular ." ]

[['place', 'crowded', 'positive'], ['place', 'popular', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The selection changes frequently but the basic dishes are always available ." ]

[['selection', 'changes frequently', 'neutral'], ['basic dishes', 'available', 'neutral']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "I have to say that if this what makes it easier to get a saet a lunch -- I dont mind ." ]

[['lunch', 'easier', 'neutral']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "We were told that they were booked solid and no other table was available ." ]

[['table', 'available', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "After dealing with subpar pizza all over the Kensington neighborhood - I 've found little toninos ." ]

[['pizza', 'subpar', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "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 ." ]

[['meats', 'thin', 'neutral'], ['vegetables', 'various', 'neutral']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Judging from previous posts this used to be a good place , but not any longer ." ]

[['place', 'good', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "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 ." ]

[['staff', 'rude', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The food was lousy - too sweet or too salty and the portions tiny ." ]

[['food', 'lousy', 'negative'], ['food', 'too sweet', 'negative'], ['food', 'too salty', 'negative'], ['portions', 'tiny', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Avoid this place !" ]

[['place', 'Avoid', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "I have eaten at Saul , many times , the food is always consistently , outrageously good ." ]

[['food', 'good', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Saul is the best restaurant on Smith Street and in Brooklyn ." ]

[['Saul', 'best', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The duck confit is always amazing and the foie gras terrine with figs was out of this world ." ]

[['foie gras terrine with figs', 'out of this world', 'positive'], ['duck confit', 'amazing', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The wine list is interesting and has many good values ." ]

[['wine list', 'interesting', 'positive'], ['wine list', 'good values', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "I was very disappointed with this restaurant ." ]

[['restaurant', 'disappointed', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Food was okay , nothing great ." ]

[['Food', 'okay', 'neutral'], ['Food', 'nothing great', 'neutral']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Chow fun was dry ; pork shu mai was more than usually greasy and had to share a table with loud and rude family ." ]

[['Chow fun', 'dry', 'negative'], ['pork shu mai', 'greasy', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "I/we will never go back to this place again ." ]

[['place', 'never go back', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Service was devine , oysters where a sensual as they come , and the price ca n't be beat ! ! !" ]

[['Service', 'devine', 'positive'], ['oysters', 'sensual', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Everything is always cooked to perfection , the service is excellent , the decor cool and understated ." ]

[['service', 'excellent', 'positive'], ['decor', 'cool', 'positive'], ['decor', 'understated', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "I had the duck breast special on my last visit and it was incredible ." ]

[['duck breast special', 'incredible', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The only thing I moderately enjoyed was their Grilled Chicken special with Edamame Puree ." ]

[['Grilled Chicken special with Edamame Puree', 'enjoyed', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "I had never had Edamame pureed before but I thought it was innovative and tasty ( could 've used a bit more salt ) ." ]

[['Edamame pureed', 'innovative', 'positive'], ['Edamame pureed', 'tasty', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Their sake list was extensive , but we were looking for Purple Haze , which was n't listed but made for us upon request !" ]

[['sake list', 'extensive', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "We went around 9:30 on a Friday and it had died down a bit by then so the service was great !" ]

[['service', 'great', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Food awesome ." ]

[['Food', 'awesome', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Service friendly and attentive ." ]

[['Service', 'friendly', 'positive'], ['Service', 'attentive', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "the food is decent ." ]

[['food', 'decent', 'neutral']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "This place has got to be the best japanese restaurant in the new york area ." ]

[['place', 'best', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Food is great ." ]

[['Food', 'great', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Service is top notch ." ]

[['Service', 'top notch', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "We took advanatage of the half price sushi deal on saturday so it was well worth it ." ]

[['half price sushi deal', 'worth', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "In the evening , this place attracted a well dressed , with it , NY crowd ." ]

[['crowd', 'attracted', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "$ 6 and there is much tasty food , all of it fresh and continually refilled ." ]

[['food', 'tasty', 'positive'], ['food', 'fresh', 'positive'], ['food', 'refilled', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]