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generation
mams
[ "We had to ask for water even after we were asked what type we preferred, and then the busboy spilled it while he was pouring it out." ]
[['food', 'neutral'], ['staff', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Arriba Arriba has much better food, margs, and atmosphere with slightly higher prices, but well worth it." ]
[['food', 'positive'], ['price', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Corner Bistro, despite the hoopla and critical praise, is nothing more than a burger joint with long lines." ]
[['food', 'neutral'], ['miscellaneous', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "I was thinking I am gonna have a nice dinner in that place that a friend of mine recommended to me , but beside the expensive prices that it has was nothing more." ]
[['food', 'positive'], ['price', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Despite almost flawless service, I had my birthday there for a party of 15 and we were given a private area on the top floor, which was so cold, we had to keep our jackets on throughout the entire meal." ]
[['service', 'negative'], ['place', 'negative'], ['miscellaneous', 'neutral'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Trish, our waitress was really great - the food was mediocre." ]
[['staff', 'positive'], ['food', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The Food Mi Nidito's menu offers a considerable array of Mexican standards, with a separate page for seafood, such as King crab enchiladas, and another for vegetarian dishes such as almond-sauteed vegetables." ]
[['menu', 'neutral'], ['miscellaneous', 'positive'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "After finally choosing banana-macadamia nut pancakes (a Hawaiian favorite of mine) after being unable to decide between 4 or 5 dishes that all sounded spectacular, I sat back and enjoyed the (complementary) tall shot glass of the smoothie of the day." ]
[['food', 'neutral'], ['miscellaneous', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Taci then moved to NYU, to a space as warm as an igloo, with an equally cold atmosphere, an attempt at a more upscale menu, and with all the charm of a pizza joint." ]
[['place', 'positive'], ['ambience', 'positive'], ['menu', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "and although the service is a little slow, the lax atmosphere allows you to drink and eat away the afternoon or evening and not even care." ]
[['service', 'negative'], ['ambience', 'positive'], ['miscellaneous', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Although Sweet Melissa's food and pastries are very tasty, the unfriendly folks who work there sour the experience." ]
[['food', 'positive'], ['miscellaneous', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "from drinks at the bar, to our perfect round table!" ]
[['place', 'neutral'], ['miscellaneous', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The food is pretty good, and so is the service, though on my first visit I told the waitress I wanted my tuna black-and-blue and she had no idea what that was." ]
[['food', 'positive'], ['staff', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "We sat in the garden out back, and the calm atmosphere with the waterfall rock wall on the side completed the setting." ]
[['place', 'neutral'], ['ambience', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "To complain about waiting for a table, etc." ]
[['service', 'negative'], ['miscellaneous', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Unlike some of the other reviews here, the reservation was upheld, the waiter took the time to explain each dish and frequently asked if we wanted more of anything (which we did, several times)." ]
[['miscellaneous', 'positive'], ['staff', 'positive'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "In addition, our waiter seemed to have short-term memory loss because he kept forgetting to bring us our drink order even after I asked him on three separate occasions." ]
[['staff', 'negative'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Anyway the food was really good, the portions are not big however very filling and exceptionally good." ]
[['food', 'positive'], ['miscellaneous', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "After arriving an hour early for our reservation for 2 and politely asking for a table near the band we were promptly seated at one of the worst tables in the place." ]
[['miscellaneous', 'neutral'], ['staff', 'neutral'], ['place', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "I found my dinner to be a bit on the heavy side and blamed the large portions." ]
[['food', 'neutral'], ['miscellaneous', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "While the environment is still fun and diverse, the food quality has been sliding lately." ]
[['ambience', 'positive'], ['food', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "I agree with the other poster who wrote about the service: the waiter challenged every single dish we ordered with a special (I've never had a more money hungry waiter) and after waiting 20 minutes for the check we had to call the manager over; who was unapologetic." ]
[['service', 'negative'], ['food', 'neutral'], ['staff', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "After all that, the waiter tried to backpedal saying its too hard to time the cooking of miso soup with the sushi bar offerings." ]
[['staff', 'negative'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Good atmosphere, the service is so-so and there is a long wait if you don't have reservations." ]
[['ambience', 'positive'], ['service', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "That bastion of authentic Mexican food in Spanish Harlem that earned raves by white reviewers, leading other gringos to nervously venture to Spanish Harlem and pretend they're trendy to pay too much for food that is only marginally better than the place around the corner." ]
[['food', 'positive'], ['staff', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "We sat, missing a place setting for a while before the waitress came to ask if we wanted water and then ran away." ]
[['ambience', 'neutral'], ['staff', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The last two didn't come to the people who ordered them until they already had there food ( in which then we had to remind the staff of)." ]
[['food', 'neutral'], ['staff', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "When I walked back to the counter, the two staff people immediately retreated to the back room, glanced back at me attempting to get their attention and immediately returned to wasting time." ]
[['place', 'neutral'], ['staff', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Expect to get average food, a big bill and lots of attitude from the service." ]
[['food', 'neutral'], ['price', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The bartender ignored us for 10 minutes before asking what we'd like to drink although we were the only people waiting for a table when we walked in." ]
[['staff', 'negative'], ['food', 'neutral'], ['service', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "it did fill up pretty quickly for lunch, but nobody seemed to have to wait too long, and i'm guessing they might be less busy for dinner." ]
[['food', 'neutral'], ['service', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "My roommate says she has had good food here at night, at the bar." ]
[['food', 'positive'], ['place', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "I made a reservation on-line quickly got a call saying that the resturant was under renovation, but the kitchen was still open and was still more than welcome to come enjoy dinner in their lounge." ]
[['miscellaneous', 'neutral'], ['place', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "I would say it's suitable for a romantic date or quiet family meal, as there is no bar so the atmosphere is a little quiet." ]
[['food', 'positive'], ['place', 'neutral'], ['ambience', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Once in the oven (electric, mind you), he shifts pies every few seconds to attain nicely-charred, chewy crust perfection." ]
[['food', 'neutral'], ['miscellaneous', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The restauarnt is Ok in terms of decor, but the food was really lacking - things were not cooked to order." ]
[['place', 'positive'], ['ambience', 'positive'], ['food', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The head waiter made some lame excuse about how the chef had asked the hostess to revise the menu but it had not been changed." ]
[['staff', 'negative'], ['menu', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The Food Surprisingly tasty Texas-style barbecue gives this place culinary flexibility beyond that of most wrap-and-burrito shacks." ]
[['food', 'positive'], ['place', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "cause, I was bored by the club scene and too overdressed for the local bar." ]
[['miscellaneous', 'negative'], ['place', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "After 10 minutes of waiting, he finally returned to the table and snootily explained to us that the wine he had opened was actually better and more expensive (not yet on the menu, of course), but he would charge us the price of the bottle we had originally ordered." ]
[['service', 'neutral'], ['miscellaneous', 'neutral'], ['food', 'negative'], ['menu', 'neutral'], ['price', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Room is impressive, but service is slow and taste was almost like fast food." ]
[['place', 'positive'], ['service', 'negative'], ['food', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "We had to flag the waitress down to get a drink refill and waited an extrodinarily long time for our entrees." ]
[['staff', 'negative'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "I can't speak on the food, but I went there for a show the other week and here is my experience: one of the friendliest servers ever (no attitude); the drinks were avg." ]
[['food', 'neutral'], ['staff', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Not the most beautiful environment, but the food is consistently delicious and the barbeque is fun and tasty." ]
[['ambience', 'negative'], ['food', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The owner was rude to us from the moment we sat down until he told us we had to leave because he had another table waiting, and this despite ordering the pricier entrees from the menu and a bottle of wine that we hadn't yet finished." ]
[['staff', 'negative'], ['menu', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "I took a few clients for lunch and the service was lackluster, food was fair at best, and the prices were outrageous - Don't wast your time with this place !" ]
[['food', 'neutral'], ['service', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The menu ranged from standard (steak, duck and mussels-all fantastic) to curious (ostrich-awesome, and tartare-smoked not raw but still so good." ]
[['menu', 'neutral'], ['food', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Hoegardden on tap is an added bonus if you're not drinking from the well versed wine menu." ]
[['miscellaneous', 'neutral'], ['menu', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Nothing beats being served platters of shrimp and wings and pitchers of beer, by the HOTTEST waitstaff in NY!!!!" ]
[['food', 'neutral'], ['staff', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Oh yeah, the food's just alright for the price." ]
[['food', 'positive'], ['price', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "It's a great place, the terrific service carried out throughout the night as we sat and got some appetizers and then decided to stay for a bottle too!" ]
[['service', 'positive'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "When we followed the waiter to get back the card, the Manager explained that their machine did work, but someone else's bill was charged on our card (total charge=$140)." ]
[['staff', 'neutral'], ['miscellaneous', 'positive'], ['price', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Even with reservations, checking in, and a generally quiet night, the hostess forgot that we were there and gave our table to her friends." ]
[['miscellaneous', 'neutral'], ['staff', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Fresh, original, creative, absolutely delicious - Perhaps I would chose a table at this cozy Italian corner versus an NYC top 5?" ]
[['miscellaneous', 'neutral'], ['place', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "My experience at the The Pearl Room was like no other place in Bay Ridge, you walk into a dimly lit atomsphere and a well dressed crowd." ]
[['place', 'neutral'], ['miscellaneous', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The service was warm, but it took forever to get the check." ]
[['service', 'positive'], ['price', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The atmosphere was a+, until a friend and I were rudely interrrupted and rushed out by the attendant at the door when the check was only returned to us just 5 mins." ]
[['miscellaneous', 'negative'], ['price', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "I had to ask the waiter a couple of times to clear our empty glasses." ]
[['staff', 'negative'], ['miscellaneous', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "I had the item that they forgot to put on the menu; some very tasty fish over jasmine rice with shrimp." ]
[['menu', 'neutral'], ['food', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Waiter had to lean on my husband to give people next to us their food." ]
[['staff', 'negative'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The wait staff pushed us to get desserts immediately after we finished our main course and we had to continuously tell them we are not ready yet." ]
[['staff', 'negative'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Go have a drink there the space is beautiful and buy an appetizer maybe, but pass on dinner, not well cooked and small portions." ]
[['place', 'positive'], ['food', 'neutral'], ['miscellaneous', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "i've had practically everything on their menu as i dine out alot but their burgers and mussels with fries are what bring me there every friday night." ]
[['menu', 'neutral'], ['food', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The entertainment is awesome - and believe it or not, I was so impressed with one of their musicians/singers (named Alessandro) that I even had him play during my cocktail hour." ]
[['ambience', 'positive'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "This is authentic Japanese food - California roll is not on the menu." ]
[['food', 'positive'], ['menu', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Space aside, service is ok but the food is really well done." ]
[['place', 'neutral'], ['food', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "When you feel like eating again an hour later (portions are small) at least you won't feel as regretful about ordering take-out." ]
[['miscellaneous', 'negative'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "There was only one server on duty and we waited a while for menus." ]
[['staff', 'positive'], ['menu', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Evening started out nice w/ complimentary glass of champagne, but turned sour as mussels were extremely overcooked, steak came in kid size portion smothered with sauce and owner recommended a wine special off the standard wine menu that was double the price of the most expensive bottle but made no effort to describe the wine as extremely special or significantly more expensive that what they typically serve." ]
[['food', 'positive'], ['staff', 'negative'], ['price', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The place is not fancy, but their food is wonderful." ]
[['place', 'negative'], ['food', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "This is a don't miss if you are anywhere close to the area, but if you're going for lunch, be there by noon to avoid a wait." ]
[['miscellaneous', 'neutral'], ['food', 'neutral'], ['service', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "' When I reasoned with them that my dining partner already received her hot entree and was halfway done eating, and all I ordered was two rolls, the wait staff finally got the idea that maybe they should be trying to get me my order." ]
[['food', 'neutral'], ['staff', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Had an OK dinner that was made better by the attention the owners pay to the patrons." ]
[['food', 'neutral'], ['staff', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "It's just nice to have a place like this - a sit down place with a lot of food choices, not centered on a particular ethnicity and a bar - as an option here." ]
[['food', 'positive'], ['place', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "We had to wait 20 minutes before getting a beer, and we never got our burger order." ]
[['food', 'neutral'], ['miscellaneous', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ ") Service was good not great, waiters stood around,didn't ask how everything was." ]
[['service', 'positive'], ['staff', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The menu had more selections, price points that fit all our budgets and a new Sushi menu that went over huge with the table." ]
[['menu', 'positive'], ['miscellaneous', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The menu features mild versions of Lone Star state favorites, from double-basted baby back ribs and steak fajitas to red-beef chili and deep-fried onions." ]
[['menu', 'neutral'], ['food', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "he politely asked about what happened, we told him about the hostess behaviour, the manager apologized for the her behavior and treated us to a drink at the bar." ]
[['staff', 'positive'], ['food', 'neutral'], ['place', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Aside from the fact the maitre de claimed the dining room was 'full', we were seated at a great table overlooking the lobby of the hotel and ordered the 5 course tasting menu." ]
[['staff', 'neutral'], ['place', 'neutral'], ['menu', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "I've heard such wonderful things about Pluck U and had the pleasure of trying their infamous chicken while having learned a few things: 1) rushed service 2) limited menu 3) semi-reasonable 4) overly popular." ]
[['food', 'positive'], ['menu', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "nice and cozy place but the soup was cold, the pizza was cold." ]
[['place', 'positive'], ['food', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The Food There's a trimmed-down version of the regular Blue Ribbon menu--all manner of sandwiches, and a solid selection of American main courses--but the real attraction is the vast, well-edited range of cheese, fish and vegetable portions (goodies like foie gras terrine aside, the meat selections are disappointingly indistinct)." ]
[['food', 'positive'], ['menu', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Still, after all the fuss, the food makes you forget about the wait." ]
[['food', 'positive'], ['service', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The wait staff was attentive without being overbearing, and our waiter gave thoughtful advice on dishes that would be suitable for the children." ]
[['staff', 'positive'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Dim, candlelit dining room is accented by a funky star pointed bar and multi-colored ceiling lamps, with trendy upbeat music in the background." ]
[['place', 'neutral'], ['miscellaneous', 'positive'], ['ambience', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The prices weren't bad though - dinner ended up at $80 with tip and we had a couple drinks as well." ]
[['price', 'positive'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "They always greet me and my friends warmly, deliver food promptly, are happy to answer questions about the menu, and they almost always throw in a free dessert at the end of the meal!" ]
[['food', 'positive'], ['menu', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "$45 a head with tip for bad gnocchi, mediocre wine (as recommended by a condescending waiter, who thought himself oh-so-nice) and the feeling that our companions (at our shared table) were listening in on all our chatter." ]
[['food', 'negative'], ['miscellaneous', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Our cocktails were ok but at ridiculous dance club prices." ]
[['food', 'positive'], ['price', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "We (naturally) asked for a discount when the bill came, and our waitress disappeared for a moment and offered us." ]
[['price', 'neutral'], ['staff', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Luckily, I made reservations for our group or else it would have been a long wait." ]
[['miscellaneous', 'neutral'], ['service', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The decor isn't the best and the place is very modest, but if you're around Ditmars Blvd." ]
[['ambience', 'negative'], ['place', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The food is great and I found it to be fresh and the prices are below to average compared to other Greek Restaurants." ]
[['food', 'positive'], ['price', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Once we eventaully got seated (all tables are practically on top of each other), we were hustled through our meal by a waitstaff that clearly knows how quickly they need to turn the table over." ]
[['place', 'neutral'], ['food', 'neutral'], ['staff', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "I went for dinner at Lucy the other night with five friends and it was the best experience I've had in a long time." ]
[['food', 'neutral'], ['miscellaneous', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Didn't get a call so I thought all was ok-they didn't have a reservation and wouldn't seat us for over an hour even though no one else was waiting and I saw several empty tables." ]
[['miscellaneous', 'neutral'], ['place', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "When we were finally seated about half an hour after my reservation, the waitress took her time taking our order." ]
[['miscellaneous', 'neutral'], ['staff', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The only apparent flavor in any of the dishes was heat, and a table of four gourmands left at least half of our meals on our plates." ]
[['ambience', 'negative'], ['miscellaneous', 'neutral'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "impressive balcony seating and while they forgot to give us the cold appetizers, the waiter and maitre'd more than made up for it by being most accomodating to us." ]
[['place', 'neutral'], ['staff', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]