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generation
aste-data-v2
[ "Drinks way over priced ." ]
[['Drinks', 'over priced', '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 pizza for lunch place ." ]
[['pizza', 'Great', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Service was quick ." ]
[['Service', 'quick', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "The pizza was great ." ]
[['pizza', 'great', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Whenever you need a Sushi fix , Mizu will be there with quality fish and great service ." ]
[['fish', 'quality', 'positive'], ['service', 'great', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Delivery is fast too ." ]
[['Delivery', 'fast', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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
[ "Ess-A-Bagel ( either by Sty-town or midtown ) is by far the best bagel in NY ." ]
[['bagel', '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 bagels always warm , soft on the inside , crispy on the outside and enormous in size ." ]
[['bagels', 'warm', 'positive'], ['bagels', 'soft', 'positive'], ['bagels', 'crispy', 'positive'], ['bagels', 'enormous', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 huge selection of different cream cheeses and all of their salads are great ." ]
[['salads', 'great', 'positive'], ['cream cheeses', 'huge', 'positive'], ['cream cheeses', '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
[ "Not impressed with the food ." ]
[['food', 'Not impressed', '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
[ "Prices too high for this cramped and unappealing resturant ." ]
[['resturant', 'cramped', 'negative'], ['resturant', 'unappealing', '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
[ "Zero ambiance to boot ." ]
[['ambiance', 'Zero', '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 thought this place was totally overrated ." ]
[['place', 'overrated', '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 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
[ "This is the BEST Shabu-Shabu Restaurant in the Try-State Area ." ]
[['Shabu-Shabu 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
[ "Thius is a must for anyone who loves Shabu-Shabu ." ]
[['Shabu-Shabu', 'loves', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "The atmosphere is nothing special , but it feels like a Sushi establishment in Tokyo ." ]
[['atmosphere', 'nothing special', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 owner and staff are all Japanese as well and that adds to the entire ambiance ." ]
[['ambiance', 'adds', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 a slightly limited menu , everything prepared is done to perfection , ultra fresh and a work of food art ." ]
[['menu', 'limited', '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
[ "Taxan delicious !" ]
[['Taxan', '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
[ "The location and ambience is Ok but the food is what makes up for it ." ]
[['location', 'Ok', 'neutral'], ['ambience', 'Ok', '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
[ "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
[ "I had the best ravioli ever ." ]
[['ravioli', '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 quaint and romantic trattoria is at the top of my Manhattan restaurant list ." ]
[['trattoria', 'quaint', 'positive'], ['trattoria', '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
[ "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
[ "Although the tables may be closely situated , the candle-light , food quality and service overcompensate ." ]
[['candle-light', 'overcompensate', 'positive'], ['food', 'overcompensate', 'positive'], ['service', 'overcompensate', 'positive'], ['tables', 'closely situated', 'negative']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "If you go , try the marinara/arrabiatta sauce , the mozzarella en Carozza is mmmmmmmm ... .. everything is just delicious ." ]
[['marinara/arrabiatta sauce', 'try', 'positive'], ['marinara/arrabiatta sauce', 'delicious', 'positive'], ['mozzarella en Carozza', '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
[ "Check out the secret back room ." ]
[['back room', 'secret', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 found the food , service and value exceptional everytime I have been there ." ]
[['food', 'exceptional', 'positive'], ['service', 'exceptional', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 authentic ." ]
[['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
[ "The service was excellent - friendly and attentive ." ]
[['service', 'excellent', 'positive'], ['service', 'friendly', 'positive'], ['service', 'attentive', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Very good wine choices ." ]
[['wine choices', 'good', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Who has room for Cheesesticks with the best pizza in NYC !" ]
[['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
[ "Always great service !" ]
[['service', 'great', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "The food is good , I ca n't lie ." ]
[['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
[ "But the staff was so horrible to us ." ]
[['staff', '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
[ "This place is pricey , and yes , the food is worth it ; but the service makes you feel like you should be paying a quater of the price ." ]
[['place', 'pricey', 'negative'], ['food', '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
[ "Amma is nothing special ." ]
[['Amma', 'nothing special', 'neutral']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "I ate here a week ago and found most dishes average at best and too expensive ." ]
[['dishes', 'average', 'negative'], ['dishes', 'too expensive', '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
[ "Do n't dine at Tamarind for the vegetarian dishes , they are simply not up to par with the non-veg selections ." ]
[['vegetarian dishes', 'not up to par', 'negative']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Decor is nice though service can be spotty ." ]
[['Decor', 'nice', 'positive'], ['service', 'spotty', '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
[ "Most importantly , food is excellent ." ]
[['food', '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 am happy i did the food was awsome ." ]
[['food', 'awsome', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Haru on Park S is simply disgusting ." ]
[['Haru on Park S', '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 fish was not fresh and the rice tasted old and stale ." ]
[['fish', 'not fresh', 'negative'], ['rice', 'old', 'negative'], ['rice', 'stale', '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
[ "Quite frankly , this is some of the worst sushi I have ever tried ." ]
[['sushi', 'worst', 'negative']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "honestly the worst sushi my husband and i had in our entire lives ." ]
[['sushi', 'worst', 'negative']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "not sure why this restaurant would be rated that highly ." ]
[['restaurant', 'highly', 'negative']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "the all-u-can-eat sushi is definitely in very poor quality ." ]
[['all-u-can-eat sushi', 'poor quality', '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
[ "limited menu , no-so-fresh ingredients , thinly-sliced fish , fall-apart rice ." ]
[['menu', 'limited', 'negative'], ['ingredients', 'no-so-fresh', 'negative'], ['fish', 'thinly-sliced', 'negative'], ['rice', 'fall-apart', '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 only things u could really taste are the very salty soy sauce ( even its low sodium ) , the vinegar-soaked rice , and the scallion on top of the fish ." ]
[['soy sauce', 'salty', 'negative'], ['rice', 'vinegar-soaked', '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 waitstaffs are nice though ." ]
[['waitstaffs', '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
[ "Both times I was extremely dissappointed by the service , which was boarderline rude ." ]
[['service', 'dissappointed', 'negative'], ['service', 'rude', 'negative']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "The dinner was ok , nothing I would have again ." ]
[['dinner', '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
[ "I had their eggs benedict for brunch , which were the worst in my entire life , I tried removing the hollondaise sauce completely that was how failed it was ." ]
[['eggs benedict', 'worst', 'negative']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "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 service was attentive ." ]
[['service', 'attentive', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Planet Thai is great !" ]
[['Planet Thai', '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 love the food , drinks , and atmosphere !" ]
[['food', 'love', 'positive'], ['drinks', 'love', 'positive'], ['atmosphere', '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 svc can be a bit rude at times , esp if you have big group , but overall the restaurant is a must !" ]
[['svc', 'rude', 'negative'], ['restaurant', 'must', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 the Pad Thai , it 's fabulous and their prices are so cheap !" ]
[['Pad Thai', 'Try', 'positive'], ['Pad Thai', 'fabulous', 'positive'], ['Pad Thai', '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
[ "Just because it 's cheap does NOT mean the portions are small or the food is nasty , IT IS GREAT !" ]
[['portions', 'small', 'positive'], ['food', 'nasty', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Eating in , the atmosphere saves it , but at your desk , it 's a very disappointing experience ." ]
[['atmosphere', 'saves', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 seats are uncomfortable if you are sitting against the wall on wooden benches ." ]
[['seats', 'uncomfortable', '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
[ "Patroon features a nice cigar bar and has great staff ." ]
[['cigar bar', 'nice', 'positive'], ['staff', '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 tasty and portion sizes are appropriate ." ]
[['food', 'tasty', 'positive'], ['portion sizes', 'appropriate', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 nice restaurant if you are looking for a good place to host an intimate dinner meeting with business associates ." ]
[['restaurant', '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
[ "Not a great place for family or general dining ." ]
[['place', 'Not a 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
[ "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
[ "Waitstaff are very friendly ." ]
[['Waitstaff', '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
[ "Mermaid Inn is an overall good restaurant with really good seafood ." ]
[['seafood', 'good', 'positive'], ['Mermaid Inn', '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 menu is limited but almost all of the dishes are excellent ." ]
[['menu', 'limited', 'negative'], ['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
[ "The lobster sandwich is good and the spaghetti with Scallops and Shrimp is great ." ]
[['lobster sandwich', 'good', 'positive'], ['spaghetti with Scallops and Shrimp', 'great', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "The service is good and ambience is good for a date or group outing ." ]
[['service', 'good', 'positive'], ['ambience', '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 only fallback on this restaurant is the prices ." ]
[['restaurant', 'fallback', '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
[ "Even though its good seafood , the prices are too high ." ]
[['seafood', '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
[ "The lobster sandwich is $ 24 and although it was good it was not nearly enough to warrant that price ." ]
[['lobster sandwich', 'good', 'negative'], ['lobster sandwich', 'not nearly enough to warrant that price', '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 delicious ( I had a halibut special , my husband had steak ) , and the service was top-notch ." ]
[['food', 'delicious', 'positive'], ['service', 'top-notch', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Truly the mark of an attentive waiter ." ]
[['waiter', 'attentive', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "I highly recommend the restaurant based on our experience last night ." ]
[['restaurant', '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
[ "We ate at this Thai place following the reviews but very unhappy with the foods ." ]
[['foods', 'unhappy', '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 recommend the jelly fish , drunken chicken and the soupy dumplings , certainly the stir fry blue crab ." ]
[['jelly fish', 'recommend', 'positive'], ['drunken chicken', 'recommend', 'positive'], ['soupy dumplings', 'recommend', 'positive'], ['stir fry blue crab', '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
[ "Have frequented 'ino for several years and the food remains excellent ." ]
[['food', '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
[ "Cheese plate is a varied delight and great bargain at $ 10 ." ]
[['Cheese plate', 'varied delight', 'positive'], ['Cheese plate', 'great bargain', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 asparagus , truffle oil , parmesan bruschetta is a winner ! )" ]
[['asparagus , truffle oil , parmesan bruschetta', 'winner', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Wine list is extensive without being over-priced ." ]
[['Wine list', 'extensive without being over-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
[ "I loved this place ! !" ]
[['place', 'loved', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 almost hesititate to write a review because the atmosphere was so great and I would hate for it too become to crowded ." ]
[['atmosphere', 'great', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "The food was 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
[ "The wait staff is very freindly , they make it feel like you 're eating in a freindly little european town ." ]
[['wait staff', 'freindly', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 like Cafe Noir dont get me wrong , it is jsut that the people who work there are evil and incompetent ! !" ]
[['people', 'evil', 'negative'], ['people', 'incompetent', 'negative'], ['Cafe Noir', 'like', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 terrible , we had to wait for everything and ask several of different people for the same thing before we were allowed to be served ." ]
[['service', '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
[ "The whole set up is truly unprofessional and I wish Cafe Noir would get some good staff , because despite the current one this is a great place ." ]
[['staff', 'good', 'negative'], ['Cafe Noir', '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
[ "Pizza here is consistently good ." ]
[['Pizza', '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
[ "You should pass on the calamari ." ]
[['calamari', 'pass', '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
[ "Decor is charming ." ]
[['Decor', 'charming', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Service is average ." ]
[['Service', 'average', '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
[ "What a great place ." ]
[['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 ambience was so fun , and the prices were great , on top of the fact that the food was really tasty ." ]
[['ambience', 'fun', 'positive'], ['food', 'tasty', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]