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generation
aste-data-v2
[ "A++ The service was good to excellent along with the attitude ." ]
[['service', 'good', 'positive'], ['attitude', '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
[ "The food is awesome - definitely try the striped bass ." ]
[['food', 'awesome', 'positive'], ['striped bass', 'try', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "black white shakes came out good also ." ]
[['black white shakes', '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
[ "It 's simply the best meal in NYC ." ]
[['meal', '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
[ "We go on Mondays for the prix fixe and our experience with the food has been comparable to Blue Ribbon ." ]
[['food', 'comparable', '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
[ "However , they 've got the most amazing pastrami and the soups hit the spot ." ]
[['pastrami', 'amazing', 'positive'], ['soups', 'hit the spot', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 bagels made the old-fashioned way ." ]
[['bagels', '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
[ "This is some really good , inexpensive sushi ." ]
[['sushi', 'good', 'positive'], ['sushi', 'inexpensive', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 personal favorite is an everything bagel with lox spread , but all the bagles are unbeliavably good ." ]
[['bagel with lox spread', 'favorite', 'positive'], ['bagles', 'unbeliavably 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 would n't even have complained at all if the food at least tasted good but the quality of food was crappy , too ." ]
[['quality of food', 'crappy', '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 the next hour and a half we stood in the crowded lobby area of this touristy restaurant listening to all types of explanations of why we were not being seated ." ]
[['lobby area', 'crowded', 'negative']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "The pizza is delicious and the proprietor is one of the nicest in NYC ." ]
[['pizza', 'delicious', 'positive'], ['proprietor', 'nicest', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Also good for client lunch meetings , esp ." ]
[['lunch meetings', 'good', '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
[ "The decor is dark , cool and soothing , while the food 's presentation is spectacular , considering the low prices ." ]
[['decor', 'dark', 'positive'], ['decor', 'cool', 'positive'], ['decor', 'soothing', 'positive'], ['prices', 'low', 'positive'], ["food 's presentation", 'spectacular', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 Waitstaff were very nice and suggested swordfish for my husband he enjoyed his meal ." ]
[['Waitstaff', 'nice', 'positive'], ['swordfish', 'suggested', 'positive'], ['meal', 'enjoyed', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "The setting is casual and romantic ." ]
[['setting', 'casual', 'positive'], ['setting', 'romantic', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Terrible , terrible management - deserves to be shut-down ." ]
[['management', 'Terrible', 'negative'], ['management', 'terrible', '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 friendly service , Fast seating , Fast Delivery , Excellent sushi ." ]
[['service', 'Great friendly', 'positive'], ['seating', 'Fast', 'positive'], ['Delivery', 'Fast', 'positive'], ['sushi', '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
[ "The Italian food has flavor ( that can be sort of surprising on the UES ) , and the service turns from a nightmare to attentive , they sort of remind me of the NY Yankees of the late 90 's , no matter how bad it look , you knew that there was a rally just around the corner ..." ]
[['Italian food', 'surprising', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Mizu is home to creative and unique rolls not to found anywhere else ." ]
[['rolls', 'unique', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Baluchi 's has solid food and a nice decor at reasonable prices ." ]
[['food', 'solid', 'positive'], ['decor', 'nice', 'positive'], ['prices', 'reasonable', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Moules were excellent , lobster ravioli was VERY salty !" ]
[['Moules', 'excellent', 'positive'], ['lobster ravioli', 'salty', '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
[ "A cheap eat for NYC , but not for dosa ." ]
[['dosa', 'but', 'negative'], ['eat', 'cheap', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 seafood is amazing , there 's a good wine list , and the ever-changing menu always offers some great surprises ." ]
[['seafood', 'amazing', 'positive'], ['wine list', 'good', 'positive'], ['menu', 'ever-changing', 'positive'], ['menu', 'great surprises', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 just OK , at least for what food was available ." ]
[['food', 'OK', '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 waitress was very patient with us and the food is phenomenal !" ]
[['waitress', 'patient', 'positive'], ['food', 'phenomenal', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "The ambience was nice , but service was n't so great ." ]
[['ambience', 'nice', 'positive'], ['service', "was n't so great", '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
[ "Solid wine list , knowledgeable staff , friendly owners and an adventurous , ever-changing menu keep us coming back ." ]
[['wine list', 'Solid', 'positive'], ['staff', 'knowledgeable', 'positive'], ['owners', 'friendly', 'positive'], ['menu', 'adventurous', 'positive'], ['menu', 'ever-changing', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 people that work there are always so friendly you forget you are in New York sometimes ." ]
[['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
[ "The location and ambience is Ok but the food is what makes up for it ." ]
[['location', 'Ok', 'neutral'], ['ambience', 'Ok', 'neutral'], ['food', 'makes up', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 and I know gourmet food by excellence !" ]
[['gourmet food', 'love', 'positive'], ['gourmet food', 'excellence', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 plan to come here again and look forward to trying their assortment of bruschetta , panini 's ... .." ]
[['bruschetta', 'look forward', 'positive'], ['panini', 'look forward', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Two people in our party felt like something else , and Volare immediately obliged with two great dishes that were not in their regular menu ." ]
[['dishes', 'great', 'positive'], ['menu', 'regular', '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
[ "He offers subpar service and has no personality ." ]
[['service', 'subpar', 'negative']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "The waitress remembers me and is very friendly , she knows what my regular is and that 's the fried mini buns with the condensed milk and the assorted fruits on beancurd ." ]
[['waitress', 'friendly', 'positive'], ['fried mini buns with the condensed milk and the assorted fruits on beancurd', 'regular', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Diner food at bistro prices is a bummer ... ." ]
[['food', 'bummer', 'negative'], ['prices', 'bummer', '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
[ "While we thoroughly enjoyed the food , it was annoying to scream across the table for conversation ." ]
[['food', 'enjoyed', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "The portions are large and the servers always surprise us with a different starter ." ]
[['portions', 'large', 'positive'], ['servers', 'surprise', 'positive'], ['starter', 'different', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "delicious bagels , especially when right out of the oven ." ]
[['bagels', '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
[ "This is one great place to eat pizza more out but not a good place for take-out pizza ." ]
[['pizza', 'great', 'positive'], ['take-out pizza', 'good', 'negative']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Try green curry with vegetables ." ]
[['green curry with vegetables', 'Try', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "First of all , this place is *not* romantic , as claimed by Citysearch 's editorial review ." ]
[['place', '*not* romantic', '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 second you walk through the heavy vault like door , with people anticipating your arrival you get the sense that you are going to have the dining ride of a lifetime ." ]
[['door', 'heavy', '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
[ "Much more reasonably priced too !" ]
[['priced', 'reasonably', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "The food was not very tasty , the portioins were tiny even for such a high quality restaurant ." ]
[['food', 'not very tasty', 'negative'], ['portioins', 'tiny', 'negative']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "The Pad Thai is excellent here , as well ." ]
[['Pad Thai', '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
[ "I do not recommend lunch specials just because it tasts the same with other regular chinese restaurant ." ]
[['lunch specials', 'not 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
[ "We parked on the block of Nina 's the place looked nice , with people obviously enjoying their pizzas ." ]
[['place', 'nice', 'positive'], ['pizzas', 'enjoying', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 o.k. , but not any better than what you get at a good neighborhood restaurant ." ]
[['food', 'o.k. ,', 'neutral'], ['food', 'not any better', 'neutral']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "We had the pot-stickers which were great and a tempura dish that was great ." ]
[['pot-stickers', 'great', 'positive'], ['tempura dish', 'great', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "I think the stuff was better than Disney ." ]
[['stuff', 'better', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "While the $ 20 entree range is not overly expensive , in New York City , there is definitely better food in that range , and so Sapphire , despite it 's lovely atmosphere , will most likely not be a restaurant to which I will return ." ]
[['food', 'better', 'negative'], ['atmosphere', 'lovely', 'positive'], ['entree range', 'not overly expensive', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Orsay , is without a doubt one of the best values for authentic French food in NYC ." ]
[['French food', 'authentic', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Well , their deliveries take for ever and the food is usually cold ." ]
[['deliveries', 'for ever', 'negative'], ['food', 'cold', '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 really large portions ." ]
[['portions', 'large', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 a great Thai restaurant with a very friendly staff ." ]
[['staff', '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 smoked salmon and roe appetizer and it was off flavor ." ]
[['smoked salmon and roe appetizer', 'off flavor', 'negative']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "We went here for lunch a couple of weeks ago on a Saturday , and I was thoroughly impressed with the food ." ]
[['food', '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
[ "I recommend the garlic shrimp , okra ( bindi ) , and anything with lamb ." ]
[['garlic shrimp', 'recommend', 'positive'], ['lamb', 'recommend', 'positive'], ['okra ( bindi )', 'recommend', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "The food is great and authentic ." ]
[['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
[ "Good for casual dinner with jeans and sneakers ." ]
[['casual dinner', '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
[ "Anyway , the food is good , the price is right and they have a decent wine list ." ]
[['food', 'good', 'positive'], ['price', 'right', 'positive'], ['wine list', 'decent', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "This place has many different styles of pizza and they are all amazing ." ]
[['styles of pizza', 'different', 'positive'], ['styles of pizza', 'amazing', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "The food was great ." ]
[['food', 'great', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Pair you food with the excellent beers on tap or their well priced wine list ." ]
[['beers on tap', 'excellent', 'positive'], ['wine list', 'well', 'positive'], ['priced', 'well', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "If you like your music blasted and the system isnt that great and if you want to pay at least 100 dollar bottle minimun then you 'll love it here ." ]
[['music', 'like', 'negative'], ['bottle minimun', 'love', '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
[ "Metrazur has a beautiful spot overlooking the main terminal ." ]
[['spot', '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 restaurant is rather small but we were lucky to get a table quickly ." ]
[['table', 'quickly', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Quality of food is excellent and price is cheap , stick to pork , fish , chicken , lamb and vegetables ." ]
[['Quality of food', 'excellent', 'positive'], ['price', 'cheap', 'positive'], ['pork', 'cheap', 'positive'], ['fish', 'cheap', 'positive'], ['chicken', 'cheap', 'positive'], ['lamb', 'cheap', 'positive'], ['vegetables', 'cheap', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "The place is a little tight and on a cold day , the seating by the entranceway can be pretty drafty ." ]
[['seating', 'drafty', 'negative'], ['place', 'tight', '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
[ "But , they were too big for the bun ." ]
[['bun', 'too big', '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
[ "The food is fresh , delicious , and reasonably priced ." ]
[['food', 'fresh', 'positive'], ['food', 'delicious', 'positive'], ['priced', 'reasonably', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Raga stands out with an interesting fusion of French and Indian cooking ." ]
[['fusion of French and Indian cooking', 'interesting', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "The bagels are fabulous ." ]
[['bagels', '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
[ "Oh yes , and they lie on the phone , claiming they have seating in the garden , then of course the seats are not available ." ]
[['seating in the garden', 'lie', 'neutral'], ['seats', 'not available', 'neutral']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Although they do the typical what kind of water would you like questions the service was good and overall very relaxing to place to eat ." ]
[['service', 'good', 'positive'], ['place', 'relaxing', 'positive'], ['water', 'typical', '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
[ "The food was very good , a great deal , and the place its self was great ." ]
[['food', 'good', 'positive'], ['place', 'great', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Probably much busier for lunch , it 's seldom crowded for dinner ( too close to downtown ) ." ]
[['lunch', 'busier', 'neutral'], ['dinner', 'seldom crowded', '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
[ "Their calzones are horrific , bad , vomit-inducing , YUCK ." ]
[['calzones', 'horrific', 'negative'], ['calzones', 'bad', 'negative'], ['calzones', 'vomit-inducing', 'negative'], ['calzones', 'YUCK', '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
[ "It takes forever to get a drink and they almost always forget to bring something ( although they dont forget to charge you for it ." ]
[['drink', 'forever', '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
[ "The place itself is beautiful the bar scene seems to be happening ." ]
[['place', 'beautiful', 'positive'], ['bar scene', 'happening', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Saturday , Nov. 6th I had a group from work come in with about 35 people and the staff was amazing to accomodate us ." ]
[['staff', '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
[ "Good spreads , great beverage selections and bagels really tasty ." ]
[['spreads', 'Good', 'positive'], ['beverage selections', 'great', 'positive'], ['bagels', 'tasty', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Also , top the meal with a delicious and perfect slice of tiramisu ." ]
[['tiramisu', 'delicious', 'positive'], ['tiramisu', '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
[ "Check out the secret back room ." ]
[['secret back room', 'Check out', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "It 's also attached to Angel 's Share , which is a cool , more romantic bar ..." ]
[['bar', 'cool', 'positive'], ['bar', 'romantic', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "I am amazed by the poor reviews- I find this place to be standout Italian in an area flooded with Italian- great prices , great atmosphere , good service and a wonderful wine list ." ]
[['prices', 'great', 'positive'], ['atmosphere', 'great', 'positive'], ['service', 'good', 'positive'], ['wine list', '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
[ "With the theater 2 blocks away we had a delicious meal in a beautiful room ." ]
[['meal', 'delicious', 'positive'], ['room', '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 food is great and reasonably priced ." ]
[['food', 'great', 'positive'], ['food', 'reasonably priced', 'positive'], ['priced', 'reasonably', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Over the years the host , Vittorio , and his crew , have always treated me as family -- although with all the business this not-so-little gem does , it amazing he 's even able to remember a consistent but not-so-frequent visitor ." ]
[['crew', 'amazing', 'positive'], ['host', 'amazing', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "The restuarant itself is not large , but seems to have several round tables to accomodate large groups hoping to save a buck to eat authentic Taiwanese ." ]
[['round tables', 'several', 'positive'], ['Taiwanese', 'authentic', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "My husband said he could 've eaten several more , the portion was fine for me he even exclaimed that the french fries were the best he has had ." ]
[['french fries', '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
[ "It is the type of place to run into old friends and have a late , raucous dinner ." ]
[['dinner', 'raucous', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 delicious - from the specials to the regular menu-fare , the dishes are never a disappointment ." ]
[['food', 'delicious', 'positive'], ['dishes', 'never a disappointment', 'positive'], ['specials', 'delicious', 'positive'], ['specials', 'never a disappointment', 'positive'], ['regular menu-fare', 'delicious', 'positive'], ['regular menu-fare', 'never a disappointment', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 combination of fresh tomato sauce , fresh mozz cheese , basil and the dough they make with imported flour , makes this is one of the better pizza 's in NY ." ]
[['fresh tomato sauce', 'fresh', 'positive'], ['fresh mozz cheese', 'fresh', 'positive'], ['pizza', 'better', 'positive'], ['flour', 'imported', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 all of you new to Indian food , try the Paneer Roll , it is a piece of heaven ." ]
[['Paneer Roll', 'heaven', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 looked very appetizing and delicious since it came on a variety of fancy plates ." ]
[['food', 'appetizing', 'positive'], ['food', 'delicious', 'positive'], ['plates', 'fancy', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Both the fresh mozzerella slices and the Plain Cheese slice are phenomenal ." ]
[['fresh mozzerella slices', 'fresh', 'positive'], ['fresh mozzerella slices', 'phenomenal', 'positive'], ['Plain Cheese slice', 'phenomenal', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 terrible and overall , I would have to say avoid at all costs ." ]
[['food', 'terrible', '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
[ "It 's constantly open , catering to the Pakistani cabbies lined up on Crosby St. , so there 's more turnover with the food than you 'd expect ( i.e. , surprisingly fresh ) ." ]
[['food', 'surprisingly 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']]