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	[ "its just a fun place to go , not a five star restaraunt ." ]	[['restaraunt', 'five star', '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 think the pizza is so overrated and was under cooked ." ]	[['pizza', 'overrated', 'negative'], ['pizza', 'under cooked', '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	[ "Had no flavor and the staff is rude and not attentive ." ]	[['staff', 'rude', 'negative'], ['staff', 'not attentive', '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 love this place" ]	[['place', 'love', '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 quick and friendly ." ]	[['service', 'quick', 'positive'], ['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	[ "I ordered the vitello alla marsala and I was pretty impressed ." ]	[['vitello alla marsala', 'impressed', '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 veal and the mushrooms were cooked perfectly ." ]	[['veal', 'perfectly', 'positive'], ['mushrooms', 'perfectly', '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 potato balls were not dry at all ... in fact it was buttery ." ]	[['potato balls', 'not dry', 'positive'], ['potato balls', 'buttery', '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 immature bartender , didnt know how to make specific drinks , service was so slowwwww , the food was not fresh or warm , waitresses were busy flirting with men at the bar and werent very attentive to all the customers ." ]	[['bartender', 'immature', 'negative'], ['service', 'slowwwww', 'negative'], ['food', 'not fresh or warm', 'negative'], ['waitresses', 'werent very attentive', '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 would never recommend this place to anybody even for a casual dinner ." ]	[['place', 'never recommend', '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 is always fresh ..." ]	[['food', 'fresh', '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	[ "overpriced japanese food with mediocre service" ]	[['japanese food', 'overpriced', 'negative'], ['service', 'mediocre', '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	[ "food was luke warm ." ]	[['food', 'luke warm', '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 excellent as well as service , however , I left The Four Seasons very dissappointed ." ]	[['food', 'excellent', 'positive'], ['service', 'excellent', 'positive'], ['The Four Seasons', 'dissappointed', '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	[ "Red Dragon Roll - my favorite thing to eat , of any food group - hands down" ]	[['Red Dragon Roll', 'favorite', '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	[ "Favorite Sushi in NYC" ]	[['Sushi', 'Favorite', '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	[ "An unpretentious spot in Park Slope , the sushi is consistently good , the service is pleasant , effective and unassuming ." ]	[['spot', 'unpretentious', 'positive'], ['sushi', 'good', 'positive'], ['service', 'pleasant', 'positive'], ['service', 'effective', 'positive'], ['service', 'unassuming', '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 Dancing , White River and Millenium rolls are musts ." ]	[['Dancing , White River and Millenium rolls', 'musts', '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	[ "Gross food – Wow-" ]	[['food', 'Gross', '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	[ "And $ 11 for a plate of bland guacamole ?" ]	[['guacamole', 'bland', '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	[ "Oh , and I never write reviews -- I just was so moved by how bad this place was , I felt it was my duty to spread the word ." ]	[['place', 'bad', '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 good , the place was clean and affordable ." ]	[['food', 'good', 'positive'], ['place', 'clean', 'positive'], ['place', 'affordable', '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 noticed alot of indian people eatting there which is a great sign for an indian place !" ]	[['indian 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	[ "The staff is very good ." ]	[['staff', '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	[ "I highly recommend this beautiful place ." ]	[['place', 'recommend', 'positive'], ['place', 'beautiful', '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	[ "Nice view of river and NYC ." ]	[['view of river and NYC', '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	[ "Great survice" ]	[['survice', '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	[ "Raymond the bartender rocks !" ]	[['Raymond', 'rocks', '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	[ "Pacifico is a great place to casually hang out ." ]	[['Pacifico', '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 omlette for brunch is great ..." ]	[['omlette for brunch', '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 spinach is fresh , definately not frozen ..." ]	[['spinach', 'fresh', '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	[ "quacamole at pacifico is yummy , as are the wings with chimmichuri ." ]	[['quacamole', 'yummy', 'positive'], ['wings with chimmichuri', 'yummy', '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	[ "A weakness is the chicken in the salads ." ]	[['chicken in the salads', 'weakness', '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	[ "Also , I personally was n't a fan of the portobello and asparagus mole ." ]	[['portobello and asparagus mole', 'fan', '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	[ "Overall , decent food at a good price , with friendly people ." ]	[['food', 'decent', 'positive'], ['people', '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	[ "Best Indian Restaurant in the City" ]	[['Indian Restaurant', '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	[ "This small Astoria souvlaki spot makes what many consider the best gyros in New York ." ]	[['gyros', '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	[ "What really makes it shine is the food , which is aggressively seasoned with Cyrpriot spices , and all made in-house ( even the gyro meat and sausages ) , and made of much higher quality ingredients that might otherwise be expected ." ]	[['food', 'shine', 'positive'], ['gyro meat', 'in-house', 'positive'], ['sausages', 'in-house', 'positive'], ['ingredients', 'higher quality', '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 the various Greek and Cypriot dishes are excellent , but the gyro is the reason to come -- if you do n't eat one your trip was wasted ." ]	[['Greek and Cypriot dishes', 'excellent', '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	[ "Best restaurant in Brooklyn" ]	[['restaurant', '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 veal was incredible last night ." ]	[['veal', '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	[ "This place is a must visit !" ]	[['place', 'must visit', '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 all shared so we get to order together and eat together ." ]	[['food', 'shared', '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 enjoyed 99 % of the dishes we 've ordered with the only exceptions being the occasional too-authentic-for-me dish ( I 'm a daring eater but not THAT daring ) ." ]	[['dishes', 'enjoyed', 'positive'], ['dish', 'too-authentic-for-me', '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 daughter 's wedding reception at Water 's Edge received the highest compliments from our guests ." ]	[["Water 's Edge", 'highest compliments', '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	[ "Everyone raved about the atmosphere ( elegant rooms and absolutely incomparable views ) and the fabulous food !" ]	[['atmosphere', 'raved', 'positive'], ['rooms', 'elegant', 'positive'], ['views', 'incomparable', 'positive'], ['food', 'fabulous', '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 was wonderful ;" ]	[['Service', 'wonderful', '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 ok but unfriendly , filthy bathroom ." ]	[['Service', 'ok', 'negative'], ['Service', 'unfriendly', 'negative'], ['bathroom', 'filthy', '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 stuff tilapia was horrid ... tasted like cardboard ." ]	[['stuff tilapia', 'horrid', '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	[ "oh speaking of bathroom , the mens bathroom was disgusting ." ]	[['mens bathroom', 'disgusting', '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 wine list was extensive - though the staff did not seem knowledgeable about wine pairings ." ]	[['wine list', 'extensive', 'positive'], ['staff', 'not seem knowledgeable', '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 , our main course was wonderful ." ]	[['main course', 'wonderful', '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 fish and my husband had the filet - both of which exceeded our expectations ." ]	[['fish', 'exceeded our expectations', 'positive'], ['filet', 'exceeded our expectations', '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 dessert ( we had a pear torte ) was good - but , once again , the staff was unable to provide appropriate drink suggestions ." ]	[['pear torte', 'good', 'positive'], ['staff', 'unable to provide', '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	[ "Not what I would expect for the price and prestige of this location ." ]	[['location', 'expect', '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	[ "All in all , I would return - as it was a beautiful restaurant - but I hope the staff pays more attention to the little details in the future ." ]	[['restaurant', 'beautiful', '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 boths are not as small as some of the reviews make them out to look they 're perfect for 2 people ." ]	[['boths', 'not as small', 'positive'], ['boths', '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	[ "The food was ok and fair nothing to go crazy ." ]	[['food', 'ok', 'neutral'], ['food', 'fair', '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	[ "Over all the looks of the place exceeds the actual meals ." ]	[['looks', 'exceeds', '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	[ "Subtle food and service" ]	[['food', 'Subtle', 'positive'], ['service', 'Subtle', '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	[ "Noodle pudding is exactly the type of service and food I enjoy ." ]	[['service', 'enjoy', 'positive'], ['food', 'enjoy', '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	[ "Servers are all different , Greg is my favorite ." ]	[['Greg', 'favorite', '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 go out to eat and like my courses , servers are patient and never rush courses or force another drink ." ]	[['servers', 'patient', '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	[ "amazing fresh dogs but best of all endless toppings ! ! !" ]	[['dogs', 'amazing fresh', 'positive'], ['toppings', 'best', 'positive'], ['toppings', 'endless', '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	[ "amazing fun for hot dog lovers of all ages PLEASE do yourself a favor and check this place out ! ! ! !" ]	[['hot dog', 'amazing fun', '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	[ "Stepping into Casa La Femme last night was a true experience unlike any other in New York !" ]	[['Casa La Femme', 'true', '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 have a great cocktail with Citrus Vodka and lemon and lime juice and mint leaves that is to die for !" ]	[['cocktail with Citrus Vodka and lemon and lime juice and mint leaves', '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	[ "We were drawn into the belly dancing show that captivated the crowd ." ]	[['belly dancing show', 'captivated', '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 never write on these sites but this restaurant is def worth commending !" ]	[['restaurant', '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	[ "I have worked in restaurants and cook a lot , and there is no way a maggot should be able to get into well prepared food ." ]	[['food', 'well prepared', '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	[ "For a restaurant with such a good reputation and that is usually so packed , there was no reason for such a lack of intelligent customer service ." ]	[['restaurant', 'good reputation', 'positive'], ['customer service', 'intelligent', '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 place , great value ." ]	[['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	[ "The food is flavorful , plentiful and reasonably priced ." ]	[['food', 'flavorful', 'positive'], ['food', 'plentiful', 'positive'], ['food', 'reasonably priced', '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 relaxed and casual ." ]	[['atmosphere', 'relaxed', 'positive'], ['atmosphere', 'casual', '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	[ "Sushi experience was unbelievable with my fiance ." ]	[['Sushi', 'unbelievable', '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 creative rolls !" ]	[['rolls', 'Good creative', '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 have great rolls , the triple color and norwegetan rolls , are awesome and filling ." ]	[['rolls', 'great', 'positive'], ['triple color and norwegetan rolls', 'awesome', 'positive'], ['triple color and norwegetan rolls', 'filling', '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 special roll and one regular roll is enough to fill you up , but save room for dessert !" ]	[['dessert', 'save room', 'positive'], ['special roll', 'enough', 'positive'], ['regular roll', 'enough', '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 have a delicious banana chocolate dessert , as well as a great green tea tempura ." ]	[['banana chocolate dessert', 'delicious', 'positive'], ['green tea tempura', '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 appetizers are also delicious !" ]	[['appetizers', 'delicious', '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	[ "Amazing food ." ]	[['food', '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	[ "Mazing interior ." ]	[['interior', 'Mazing', '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 food !" ]	[['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 atmosphere was pretty nice but had a bit lacking , which it tries to make up for with a crazy scheme of mirrors ." ]	[['atmosphere', 'nice', 'negative'], ['scheme of mirrors', 'crazy', '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	[ "Despite the confusing mirrors this will likely be my go-to for modern Japanese food for the foreseeable future ." ]	[['modern Japanese food', 'go-to for', 'positive'], ['mirrors', 'confusing', '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	[ "Indo Chinese food , pretty good ..." ]	[['Indo Chinese 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	[ "Not a very fancy place but very good Chinese style Indian food ." ]	[['place', 'fancy', 'neutral'], ['Chinese style Indian 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	[ "The chicken lollipop is my favorite , most of the dishes ( I have to agree with a previous reviewer ) are quite oily and very spicy , espeically the Chilli Chicken ." ]	[['chicken lollipop', 'favorite', 'positive'], ['dishes', 'oily', 'negative'], ['dishes', 'spicy', 'negative'], ['Chilli Chicken', 'oily', 'negative'], ['Chilli Chicken', 'spicy', '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 mom originally introduced me to this place , but even she ( being Indian ) feels the food can be somewhat over the top spicy and far too oily ." ]	[['food', 'spicy', 'negative'], ['food', 'oily', '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 was speechless by the horrible food ." ]	[['food', 'speechless', 'negative'], ['food', '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	[ "I attended a holiday dinner at the restaurant , and the food was majorly disappointing ." ]	[['food', 'disappointing', '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 is the MOST wonderful restaurant in all of New York City , not just Brooklyn ..." ]	[['restaurant', 'wonderful', '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 7 years they have put out the most tasty , most delicious food and kept it that way ..." ]	[['food', 'tasty', 'positive'], ['food', 'delicious', '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	[ "never swaying , never a bad meal , never bad service ..." ]	[['meal', 'never a bad', 'positive'], ['service', 'never bad', '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	[ "great food , great wine list , great service in a great neighborhood ..." ]	[['food', 'great', 'positive'], ['wine list', 'great', 'positive'], ['service', 'great', 'positive'], ['neighborhood', '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	[ "Patsy 's Pizza - true love" ]	[["Patsy 's Pizza", 'true love', '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	[ "Hands down the best pizza on the planet ." ]	[['pizza', '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	[ "great hot dogs ." ]	[['hot dogs', '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 hot dogs were juicy and tender inside and had plenty of crunch and snap on the outside ." ]	[['hot dogs', 'juicy', '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	[ "great toppings definitely a place you need to check out for late night munchies or a mid day boost !" ]	[['toppings', '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

[ "its just a fun place to go , not a five star restaraunt ." ]

[['restaraunt', 'five star', '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 think the pizza is so overrated and was under cooked ." ]

[['pizza', 'overrated', 'negative'], ['pizza', 'under cooked', '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

[ "Had no flavor and the staff is rude and not attentive ." ]

[['staff', 'rude', 'negative'], ['staff', 'not attentive', '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 love this place" ]

[['place', 'love', '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 quick and friendly ." ]

[['service', 'quick', 'positive'], ['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

[ "I ordered the vitello alla marsala and I was pretty impressed ." ]

[['vitello alla marsala', 'impressed', '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 veal and the mushrooms were cooked perfectly ." ]

[['veal', 'perfectly', 'positive'], ['mushrooms', 'perfectly', '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 potato balls were not dry at all ... in fact it was buttery ." ]

[['potato balls', 'not dry', 'positive'], ['potato balls', 'buttery', '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 immature bartender , didnt know how to make specific drinks , service was so slowwwww , the food was not fresh or warm , waitresses were busy flirting with men at the bar and werent very attentive to all the customers ." ]

[['bartender', 'immature', 'negative'], ['service', 'slowwwww', 'negative'], ['food', 'not fresh or warm', 'negative'], ['waitresses', 'werent very attentive', '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 would never recommend this place to anybody even for a casual dinner ." ]

[['place', 'never recommend', '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 is always fresh ..." ]

[['food', 'fresh', '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

[ "overpriced japanese food with mediocre service" ]

[['japanese food', 'overpriced', 'negative'], ['service', 'mediocre', '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

[ "food was luke warm ." ]

[['food', 'luke warm', '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 excellent as well as service , however , I left The Four Seasons very dissappointed ." ]

[['food', 'excellent', 'positive'], ['service', 'excellent', 'positive'], ['The Four Seasons', 'dissappointed', '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

[ "Red Dragon Roll - my favorite thing to eat , of any food group - hands down" ]

[['Red Dragon Roll', 'favorite', '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

[ "Favorite Sushi in NYC" ]

[['Sushi', 'Favorite', '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

[ "An unpretentious spot in Park Slope , the sushi is consistently good , the service is pleasant , effective and unassuming ." ]

[['spot', 'unpretentious', 'positive'], ['sushi', 'good', 'positive'], ['service', 'pleasant', 'positive'], ['service', 'effective', 'positive'], ['service', 'unassuming', '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 Dancing , White River and Millenium rolls are musts ." ]

[['Dancing , White River and Millenium rolls', 'musts', '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

[ "Gross food – Wow-" ]

[['food', 'Gross', '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

[ "And $ 11 for a plate of bland guacamole ?" ]

[['guacamole', 'bland', '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

[ "Oh , and I never write reviews -- I just was so moved by how bad this place was , I felt it was my duty to spread the word ." ]

[['place', 'bad', '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 good , the place was clean and affordable ." ]

[['food', 'good', 'positive'], ['place', 'clean', 'positive'], ['place', 'affordable', '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 noticed alot of indian people eatting there which is a great sign for an indian place !" ]

[['indian 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

[ "The staff is very good ." ]

[['staff', '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

[ "I highly recommend this beautiful place ." ]

[['place', 'recommend', 'positive'], ['place', 'beautiful', '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

[ "Nice view of river and NYC ." ]

[['view of river and NYC', '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

[ "Great survice" ]

[['survice', '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

[ "Raymond the bartender rocks !" ]

[['Raymond', 'rocks', '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

[ "Pacifico is a great place to casually hang out ." ]

[['Pacifico', '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 omlette for brunch is great ..." ]

[['omlette for brunch', '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 spinach is fresh , definately not frozen ..." ]

[['spinach', 'fresh', '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

[ "quacamole at pacifico is yummy , as are the wings with chimmichuri ." ]

[['quacamole', 'yummy', 'positive'], ['wings with chimmichuri', 'yummy', '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

[ "A weakness is the chicken in the salads ." ]

[['chicken in the salads', 'weakness', '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

[ "Also , I personally was n't a fan of the portobello and asparagus mole ." ]

[['portobello and asparagus mole', 'fan', '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

[ "Overall , decent food at a good price , with friendly people ." ]

[['food', 'decent', 'positive'], ['people', '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

[ "Best Indian Restaurant in the City" ]

[['Indian Restaurant', '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

[ "This small Astoria souvlaki spot makes what many consider the best gyros in New York ." ]

[['gyros', '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

[ "What really makes it shine is the food , which is aggressively seasoned with Cyrpriot spices , and all made in-house ( even the gyro meat and sausages ) , and made of much higher quality ingredients that might otherwise be expected ." ]

[['food', 'shine', 'positive'], ['gyro meat', 'in-house', 'positive'], ['sausages', 'in-house', 'positive'], ['ingredients', 'higher quality', '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 the various Greek and Cypriot dishes are excellent , but the gyro is the reason to come -- if you do n't eat one your trip was wasted ." ]

[['Greek and Cypriot dishes', 'excellent', '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

[ "Best restaurant in Brooklyn" ]

[['restaurant', '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 veal was incredible last night ." ]

[['veal', '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

[ "This place is a must visit !" ]

[['place', 'must visit', '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 all shared so we get to order together and eat together ." ]

[['food', 'shared', '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 enjoyed 99 % of the dishes we 've ordered with the only exceptions being the occasional too-authentic-for-me dish ( I 'm a daring eater but not THAT daring ) ." ]

[['dishes', 'enjoyed', 'positive'], ['dish', 'too-authentic-for-me', '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 daughter 's wedding reception at Water 's Edge received the highest compliments from our guests ." ]

[["Water 's Edge", 'highest compliments', '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

[ "Everyone raved about the atmosphere ( elegant rooms and absolutely incomparable views ) and the fabulous food !" ]

[['atmosphere', 'raved', 'positive'], ['rooms', 'elegant', 'positive'], ['views', 'incomparable', 'positive'], ['food', 'fabulous', '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 was wonderful ;" ]

[['Service', 'wonderful', '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 ok but unfriendly , filthy bathroom ." ]

[['Service', 'ok', 'negative'], ['Service', 'unfriendly', 'negative'], ['bathroom', 'filthy', '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 stuff tilapia was horrid ... tasted like cardboard ." ]

[['stuff tilapia', 'horrid', '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

[ "oh speaking of bathroom , the mens bathroom was disgusting ." ]

[['mens bathroom', 'disgusting', '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 wine list was extensive - though the staff did not seem knowledgeable about wine pairings ." ]

[['wine list', 'extensive', 'positive'], ['staff', 'not seem knowledgeable', '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 , our main course was wonderful ." ]

[['main course', 'wonderful', '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 fish and my husband had the filet - both of which exceeded our expectations ." ]

[['fish', 'exceeded our expectations', 'positive'], ['filet', 'exceeded our expectations', '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 dessert ( we had a pear torte ) was good - but , once again , the staff was unable to provide appropriate drink suggestions ." ]

[['pear torte', 'good', 'positive'], ['staff', 'unable to provide', '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

[ "Not what I would expect for the price and prestige of this location ." ]

[['location', 'expect', '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

[ "All in all , I would return - as it was a beautiful restaurant - but I hope the staff pays more attention to the little details in the future ." ]

[['restaurant', 'beautiful', '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 boths are not as small as some of the reviews make them out to look they 're perfect for 2 people ." ]

[['boths', 'not as small', 'positive'], ['boths', '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

[ "The food was ok and fair nothing to go crazy ." ]

[['food', 'ok', 'neutral'], ['food', 'fair', '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

[ "Over all the looks of the place exceeds the actual meals ." ]

[['looks', 'exceeds', '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

[ "Subtle food and service" ]

[['food', 'Subtle', 'positive'], ['service', 'Subtle', '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

[ "Noodle pudding is exactly the type of service and food I enjoy ." ]

[['service', 'enjoy', 'positive'], ['food', 'enjoy', '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

[ "Servers are all different , Greg is my favorite ." ]

[['Greg', 'favorite', '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 go out to eat and like my courses , servers are patient and never rush courses or force another drink ." ]

[['servers', 'patient', '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

[ "amazing fresh dogs but best of all endless toppings ! ! !" ]

[['dogs', 'amazing fresh', 'positive'], ['toppings', 'best', 'positive'], ['toppings', 'endless', '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

[ "amazing fun for hot dog lovers of all ages PLEASE do yourself a favor and check this place out ! ! ! !" ]

[['hot dog', 'amazing fun', '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

[ "Stepping into Casa La Femme last night was a true experience unlike any other in New York !" ]

[['Casa La Femme', 'true', '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 have a great cocktail with Citrus Vodka and lemon and lime juice and mint leaves that is to die for !" ]

[['cocktail with Citrus Vodka and lemon and lime juice and mint leaves', '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

[ "We were drawn into the belly dancing show that captivated the crowd ." ]

[['belly dancing show', 'captivated', '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 never write on these sites but this restaurant is def worth commending !" ]

[['restaurant', '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

[ "I have worked in restaurants and cook a lot , and there is no way a maggot should be able to get into well prepared food ." ]

[['food', 'well prepared', '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

[ "For a restaurant with such a good reputation and that is usually so packed , there was no reason for such a lack of intelligent customer service ." ]

[['restaurant', 'good reputation', 'positive'], ['customer service', 'intelligent', '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 place , great value ." ]

[['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

[ "The food is flavorful , plentiful and reasonably priced ." ]

[['food', 'flavorful', 'positive'], ['food', 'plentiful', 'positive'], ['food', 'reasonably priced', '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 relaxed and casual ." ]

[['atmosphere', 'relaxed', 'positive'], ['atmosphere', 'casual', '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

[ "Sushi experience was unbelievable with my fiance ." ]

[['Sushi', 'unbelievable', '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 creative rolls !" ]

[['rolls', 'Good creative', '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 have great rolls , the triple color and norwegetan rolls , are awesome and filling ." ]

[['rolls', 'great', 'positive'], ['triple color and norwegetan rolls', 'awesome', 'positive'], ['triple color and norwegetan rolls', 'filling', '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 special roll and one regular roll is enough to fill you up , but save room for dessert !" ]

[['dessert', 'save room', 'positive'], ['special roll', 'enough', 'positive'], ['regular roll', 'enough', '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 have a delicious banana chocolate dessert , as well as a great green tea tempura ." ]

[['banana chocolate dessert', 'delicious', 'positive'], ['green tea tempura', '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 appetizers are also delicious !" ]

[['appetizers', 'delicious', '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

[ "Amazing food ." ]

[['food', '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

[ "Mazing interior ." ]

[['interior', 'Mazing', '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 food !" ]

[['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 atmosphere was pretty nice but had a bit lacking , which it tries to make up for with a crazy scheme of mirrors ." ]

[['atmosphere', 'nice', 'negative'], ['scheme of mirrors', 'crazy', '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

[ "Despite the confusing mirrors this will likely be my go-to for modern Japanese food for the foreseeable future ." ]

[['modern Japanese food', 'go-to for', 'positive'], ['mirrors', 'confusing', '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

[ "Indo Chinese food , pretty good ..." ]

[['Indo Chinese 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

[ "Not a very fancy place but very good Chinese style Indian food ." ]

[['place', 'fancy', 'neutral'], ['Chinese style Indian 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

[ "The chicken lollipop is my favorite , most of the dishes ( I have to agree with a previous reviewer ) are quite oily and very spicy , espeically the Chilli Chicken ." ]

[['chicken lollipop', 'favorite', 'positive'], ['dishes', 'oily', 'negative'], ['dishes', 'spicy', 'negative'], ['Chilli Chicken', 'oily', 'negative'], ['Chilli Chicken', 'spicy', '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 mom originally introduced me to this place , but even she ( being Indian ) feels the food can be somewhat over the top spicy and far too oily ." ]

[['food', 'spicy', 'negative'], ['food', 'oily', '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 was speechless by the horrible food ." ]

[['food', 'speechless', 'negative'], ['food', '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

[ "I attended a holiday dinner at the restaurant , and the food was majorly disappointing ." ]

[['food', 'disappointing', '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 is the MOST wonderful restaurant in all of New York City , not just Brooklyn ..." ]

[['restaurant', 'wonderful', '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 7 years they have put out the most tasty , most delicious food and kept it that way ..." ]

[['food', 'tasty', 'positive'], ['food', 'delicious', '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

[ "never swaying , never a bad meal , never bad service ..." ]

[['meal', 'never a bad', 'positive'], ['service', 'never bad', '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

[ "great food , great wine list , great service in a great neighborhood ..." ]

[['food', 'great', 'positive'], ['wine list', 'great', 'positive'], ['service', 'great', 'positive'], ['neighborhood', '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

[ "Patsy 's Pizza - true love" ]

[["Patsy 's Pizza", 'true love', '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

[ "Hands down the best pizza on the planet ." ]

[['pizza', '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

[ "great hot dogs ." ]

[['hot dogs', '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 hot dogs were juicy and tender inside and had plenty of crunch and snap on the outside ." ]

[['hot dogs', 'juicy', '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

[ "great toppings definitely a place you need to check out for late night munchies or a mid day boost !" ]

[['toppings', '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']]