task_type
stringclasses
1 value
dataset
stringclasses
1 value
input
sequence
output
stringlengths
28
294
situation
stringclasses
1 value
label
stringclasses
1 value
extra
stringclasses
1 value
instruction
stringclasses
1 value
generation
aste-data-v2
[ "I was here a few weeks back and we had the worst customer service experience at a restaurant ever ." ]
[['customer service', '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
[ "Excellent atmosphere , delicious dishes good and friendly service ." ]
[['atmosphere', 'Excellent', 'positive'], ['dishes', 'delicious', 'positive'], ['service', 'good', 'positive'], ['service', 'friendly', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "The wine list is also really nice ." ]
[['wine list', '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
[ "I would highly recommend this place !" ]
[['place', '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
[ "I have been to Casimir over 5 times and I have always had a great time there ." ]
[['Casimir', 'great time', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "The staff has been nice , but they seemed really stressed and the unisex bathroom needs to be cleaned more often ." ]
[['staff', 'nice', 'negative'], ['staff', 'stressed', 'negative'], ['unisex bathroom', 'stressed', '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
[ "From the spectacular caviar to the hospitable waitstaff , I felt like royalty and enjoyed every second of it ." ]
[['caviar', 'spectacular', 'positive'], ['caviar', 'enjoyed', 'positive'], ['waitstaff', 'hospitable', 'positive'], ['waitstaff', '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
[ "Considering we were the last patrons there and it was after the closing time , the waitstaff did not rush us at all and made us feel comfortable and relaxed ." ]
[['waitstaff', 'comfortable', 'positive'], ['waitstaff', 'relaxed', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "I highly recommend Caviar Russe to anyone who wants delicious top grade caviar and fantastic service ." ]
[['caviar', 'delicious top grade', 'positive'], ['service', 'fantastic', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Fresh ingredients and everything is made to order ." ]
[['ingredients', 'Fresh', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Friendly staff that actually lets you enjoy your meal and the company you 're with ." ]
[['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 found the food to be outstanding , particulary the salmon dish I had ." ]
[['food', 'outstanding', 'positive'], ['salmon dish', 'outstanding', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 friends settled for rice dishes , but we came back the following day to try the dim sum , which was good ... not outstanding , but good ." ]
[['dim sum', 'good', 'neutral'], ['dim sum', 'not outstanding', '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 ate out in the back patio , which is worth it as it 's cool and the music is hear well there ." ]
[['back patio', 'worth', 'positive'], ['back patio', 'cool', 'positive'], ['music', '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
[ "Overall , excellent restaurant !" ]
[['restaurant', '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 was good ." ]
[['food', 'good', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "but the service was a bit slow ." ]
[['service', 'slow', '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 buffet had a nice selection ." ]
[['buffet', 'nice', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "The food was average or above including some surprising tasty dishes ." ]
[['food', 'average or above', 'positive'], ['dishes', '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
[ "Service was also very good ." ]
[['Service', '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 got an excellent piece of cheesecake and we had several other nice pastries ." ]
[['cheesecake', 'excellent', 'positive'], ['pastries', '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
[ "I would recommend Roxy 's for that , but not for their food ." ]
[['food', '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
[ "My son and his girlfriend both wanted cheeseburgers and they were huge !" ]
[['cheeseburgers', 'huge', 'neutral']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "This place is really trendi but they have forgotten about the most important part of a restaurant , the food ." ]
[['food', 'forgotten', 'negative'], ['place', 'trendi', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 last two times I ordered from here my food was soo spicy that I could barely eat it , and the spice took away from the flavor of the dish ." ]
[['food', 'spicy', 'negative']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "And the Tom Kha soup was pathetic ." ]
[['Tom Kha soup', 'pathetic', '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 want good authentic Thai this place is not the place to go ." ]
[['Thai', 'good authentic', '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
[ "The pesto pizza was excellent , thin-crust pizza with a nice amount of spicy Italian cheese that I 'd never heard of before ." ]
[['pesto pizza', 'excellent', 'positive'], ['spicy Italian cheese', '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
[ "We had the lobster sandwich and it was FANTASTIC ." ]
[['lobster sandwich', 'FANTASTIC', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 ." ]
[['portion', 'fine', 'positive'], ['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
[ "We had the scallops as an appetizer and they were delicious and the sauce was wonderful ." ]
[['scallops', 'delicious', 'positive'], ['sauce', '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
[ "We waited at the bar and had martinis that were just right ." ]
[['martinis', 'right', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 the food ." ]
[['food', '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
[ "it 's the only place you can get yummy authentic japanese comfort food ." ]
[['japanese comfort food', 'yummy 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
[ "Great food , good size menu , great service and an unpretensious setting ." ]
[['food', 'Great', 'positive'], ['menu', 'good size', 'positive'], ['service', 'great', 'positive'], ['setting', 'unpretensious', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 dishes offered were unique , very tasty and fresh from the lamb sausages , sardines with biscuits , large whole shrimp to the amazing pistachio ice cream ( the best and freshest I 've ever had ) ." ]
[['dishes', 'unique', 'positive'], ['dishes', 'tasty', 'positive'], ['dishes', 'fresh', 'positive'], ['pistachio ice cream', '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
[ "I 'm glad I was introduced to this place and this is a rare gem in NY ." ]
[['place', 'glad', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 freshest , best variety , and the fastest delivery ." ]
[['delivery', 'fastest', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 and the food was delicious ." ]
[['service', 'excellent', 'positive'], ['food', 'delicious', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "We are very particular about sushi and were both please with every choice which included : ceviche mix ( special ) , crab dumplings , assorted sashimi , sushi and rolls , two types of sake , and the banana tempura ." ]
[['sushi', 'particular', 'positive'], ['ceviche mix ( special )', 'please', 'positive'], ['crab dumplings', 'please', 'positive'], ['assorted sashimi', 'please', 'positive'], ['rolls', 'please', 'positive'], ['banana tempura', 'please', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Definitely a great spot for a nice occasion or date ." ]
[['spot', '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
[ "Average to good Thai food , but terrible delivery ." ]
[['Thai food', 'Average to good', 'positive'], ['delivery', '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 food arrived 20 minutes after I called , cold and soggy ." ]
[['food', 'cold', 'negative'], ['food', 'soggy', 'negative']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "This is a wonderful place on all stand points especially value ofr money ." ]
[['place', '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
[ "An excellent service" ]
[['service', '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
[ "We were greeted promptly by the waiter who was very nice and cordial ." ]
[['waiter', 'nice', 'positive'], ['waiter', 'cordial', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "She was very helpful in suggesting us drinks and helped us in ordering a lot of good dishes since we knew nothing about Indian food ." ]
[['dishes', '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 food looked very appetizing and delicious since it came on a variety of fancy plates ." ]
[['food', 'appetizing', 'positive'], ['food', 'delicious', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Service here was great , food was fantastic ." ]
[['Service', 'great', 'positive'], ['food', 'fantastic', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Guacamole+shrimp appetizer was really great , we both had the filet , very good , did n't much like the frites that came with , but the filet was so good , neither of us cared ." ]
[['Guacamole+shrimp appetizer', 'great', 'positive'], ['filet', '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 can not go wrong with this place ." ]
[['place', 'wrong', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 outstanding and the service is quick , friendly and very professional ." ]
[['food', 'outstanding', 'positive'], ['service', 'quick', 'positive'], ['service', 'friendly', 'positive'], ['service', 'professional', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 a nice crowd , but never loud ." ]
[['crowd', 'nice', 'positive'], ['crowd', 'never loud', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "By far , the best pizza in Manhattan ." ]
[['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
[ "The crust is thin , the ingredients are fresh and the staff is friendly ." ]
[['crust', 'thin', 'positive'], ['staff', 'friendly', 'positive'], ['ingredients', 'fresh', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "The fish was really , really fresh ." ]
[['fish', 'fresh', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "We all agreed that mare is one of the best seafood restaurants in New York ." ]
[['mare', '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
[ "I stumbled upon this great pizzeria as I explored my new neighborhood ." ]
[['pizzeria', '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
[ "All of the pizzas are terrific and the price is even better !" ]
[['pizzas', 'terrific', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 Sophia pizza ." ]
[['Sophia pizza', '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 was mediocre at best but it was the horrible service that made me vow never to go back ." ]
[['food', 'mediocre', 'negative'], ['service', 'horrible', 'negative']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "For the people who want great food plus great service , Roxy is a place to AVOID !" ]
[['food', 'great', 'negative'], ['service', '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
[ "The first time the sushi was outstanding , the second time it was a little bland ." ]
[['sushi', 'outstanding', 'negative'], ['sushi', 'bland', 'negative']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "The blond wood decor is very soothing , the premium sake is excellent and the service is great ." ]
[['blond wood decor', 'soothing', 'positive'], ['premium sake', 'soothing', '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
[ "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
[ "Not only is the cuisine the best around , the service has always been attentive and charming ." ]
[['cuisine', 'best', 'positive'], ['service', 'attentive', 'positive'], ['service', '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
[ "Warning : You may find it difficult to dine at other Japanese restaurants after a visit to Mizu !" ]
[['Mizu', 'difficult', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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
[ "The entree was bland and small , dessert was not inspired ." ]
[['entree', 'bland', 'negative'], ['entree', 'small', 'negative'], ['dessert', 'not inspired', '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
[ "Wonderful strawberry daiquiries as well !" ]
[['strawberry daiquiries', '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
[ "delicious simple food in nice outdoor atmosphere ." ]
[['food', 'delicious simple', 'positive'], ['outdoor atmosphere', '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
[ "Delicious crab cakes too ." ]
[['crab cakes', '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
[ "Even if the food was n't this good , the garden is a great place to sit outside and relax ." ]
[['garden', 'great', 'positive'], ['food', "was n't this 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
[ "Great neighborhood joint ." ]
[['joint', '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 a nice pizza place with good selection of thin crust pizza including the Basil slice ." ]
[['selection of thin crust pizza', 'good', 'positive'], ['pizza place', 'nice', 'positive'], ['Basil slice', '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
[ "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
[ "The counter service is bad ." ]
[['counter service', 'bad', 'negative']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "The dosas are skimpy , unattractive and drip with grease , and personally I 'd drink popcorn topping before I 'd eat another one of these ." ]
[['dosas', 'skimpy', 'negative'], ['dosas', 'unattractive', '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 sandwiches are dry , tasteless and way overpriced ." ]
[['sandwiches', 'dry', 'negative'], ['sandwiches', 'tasteless', 'negative'], ['sandwiches', 'overpriced', '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
[ "Calling the place Hampton Chutney Co. does warn you that these folks offer more style than substance , but in this unattractive room with unhelpful clerks there was a dearth of the former too ." ]
[['place', 'unattractive', 'negative'], ['room', 'unattractive', 'negative'], ['clerks', 'unhelpful', '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
[ "Seriously , this place kicks ass ." ]
[['place', 'kicks ass', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "Best Italian food I ever had ( and being Italian , that means alot ) ." ]
[['Italian food', '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 restaurant looks out over beautiful green lawns to the Hudson River and the Statue of Liberty ." ]
[['restaurant', 'beautiful', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation
aste-data-v2
[ "The food is good , especially their more basic dishes , and the drinks are delicious ." ]
[['food', 'good', 'positive'], ['basic dishes', 'good', 'positive'], ['drinks', '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 a great place to take out-of-towners , and perfect for watching the sunset ." ]
[['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
[ "Unique apppetizers ." ]
[['apppetizers', '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
[ "Try sushimi cucumber roll ." ]
[['sushimi cucumber roll', '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
[ "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
[ "The service is awful ." ]
[['service', 'awful', '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 will be out with friends and all of a sudden I am hungry and I only crave one thing ... their Pizza ." ]
[['Pizza', 'crave', 'positive']]
none
Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 tiny Williamsburg spot is always pleasantly surprising ." ]
[['Williamsburg spot', '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
[ "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
[ "The cream cheeses are out of this world and I love that coffee ! !" ]
[['cream cheeses', 'out of this world', 'positive'], ['coffee', '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
[ "Bagels are ok , but be sure not to make any special requests !" ]
[['Bagels', '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
[ "the turkey burgers are scary !" ]
[['turkey burgers', 'scary', '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 sushi was awful !" ]
[['sushi', 'awful', '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
[ "Furthermore , the rice had no seasoning , so the sushi was bland and disgusting ." ]
[['sushi', 'bland', 'negative'], ['sushi', '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
[ "Good , fast service ." ]
[['service', 'Good', 'positive'], ['service', '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']]