task_type stringclasses 1
value | dataset stringclasses 1
value | input list | output stringlengths 40 314 | situation stringclasses 1
value | label stringclasses 1
value | extra stringclasses 1
value | instruction stringclasses 2
values |
|---|---|---|---|---|---|---|---|
generation | mams | [
"The prixe fix menu was a deal to boost downtown restaurants, atleast we didn't pay the full price."
] | [['menu', '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... | ||
generation | mams | [
"The steak au poivre certainly lives up to its lofty reputation, but it shuoldn't overshadow many of the other delicacies on the menu, such as the crab cakes and the frisee salad."
] | [['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... | ||
generation | mams | [
"Waiter was a strange bird and when told we wanted to enjoy our dining experience and not be rushed through dinner, he assured us it takes 30 minutes to get entrees once food was ordered."
] | [['staff', '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... | ||
generation | mams | [
"This is not haute cuisine, but that' part of what I love about it - it has an honest, intimate feel with no pretensions, just like eating in an Italian family's home."
] | [['food', 'negative'], ['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... | ||
generation | mams | [
"The food was so-so and you would think it was a french resturant, the portions were so tiny."
] | [['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... | ||
generation | mams | [
"Eventually another waiter cleaned up the table and allowed us to sit there."
] | [['staff', '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... | ||
generation | mams | [
"However the hostess completely ignored us, we waited 40 min at the bar (even with reservation), our waitress was incredibly uninterested in us (never even offered dessert menus) and the somelier could have taken a look at the label before he made a mistake about his favorite wine."
] | [['staff', 'negative'], ['place', 'neutral'], ['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... | ||
generation | mams | [
"seems everyone ordered sushi there were tons of delivery orders (we can tell as we sat near the back)."
] | [['food', 'neutral'], ['service', '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... | ||
generation | mams | [
"small price to pay to have dinner on a Saturday night in downtown Manhattan."
] | [['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... | ||
generation | mams | [
"The Scene Flanked by a diner-style bar on one side and glass cases of sweets on the other, General Store resembles a cozy mom-and-pop rest stop on the way through Pennsylvania Dutch country--minus the cheesy gift shop."
] | [['miscellaneous', '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... | ||
generation | mams | [
"Since it's a small place, it's best to get there early for dinner as the wait can be quite long if you don't make a reservation."
] | [['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... | ||
generation | mams | [
"The interior is understated making it special enough to take a date but easy enough to stop in anytime for dinner or snack."
] | [['place', '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... | ||
generation | mams | [
"The prices are incredibly reasonable, especially considering the HUGE portions - by noodle soup could have fed both my husband and myself."
] | [['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... | ||
generation | mams | [
"There is a huge line, usually a 45 minute wait; they take no reservations and no tables of more than five people."
] | [['service', 'neutral'], ['miscellaneous', 'negative'], ['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... | ||
generation | mams | [
"The pizzas are a MUST TRY, hence the name."
] | [['food', '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... | ||
generation | mams | [
"The situation was verified by taking 3 dishes that were over an hour late off the bill and free desserts and coffee but the experience left most of us never wanting to go to the supposed hip cool 66 ever again."
] | [['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... | ||
generation | mams | [
"I went there with family and even though we had reservations, we were seated 30 minutes late, the food took 45 minutes to arrive and when I got the wrong order, I had a hard time trying to find the server."
] | [['miscellaneous', 'neutral'], ['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... | ||
generation | mams | [
"The wait was much shorter than the hostess quoted, which was great."
] | [['service', '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... | ||
generation | mams | [
"Though the menu is brief, entrees range from a deeply satisfying, wintry seared calf's liver with oven-dried tomatoes to a much lighter striped bass drizzled with textbook perfect beurre blanc."
] | [['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... | ||
generation | mams | [
"When we got our food, the waitress barely said a word as she placed our take-out on the table and grabbed the check."
] | [['food', 'neutral'], ['staff', '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... | ||
generation | mams | [
"Dropped in for a quick bite with a friend -- like the previous reviewer it took more than 15 minutes for any kind of service at all (including getting water) and then another 45 minutes to get a burger (which admittedly was good)."
] | [['service', '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... | ||
generation | mams | [
"However, it takes ages to get seated (even with a reservation), and the waiters don't seem very knowledgeable about the menu (or receptive to questions)."
] | [['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... | ||
generation | mams | [
"The only complaint I have is that the tables for 2 along the booth are very close together so it wasn't as romantic a dinner as we wanted but all in all, we were in our own world, more like in heaven."
] | [['place', 'neutral'], ['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... | ||
generation | mams | [
"Ok the manager did stand at the bar the whole time looking like his wife left him, he lost all his money at the track and had been drinking the rest of the day."
] | [['staff', '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... | ||
generation | mams | [
"We complained to our waiter serveral times about this and the stares continued and to top it all off as the manager walked around to each table asking if they enjoyed their dinner, he conveniently did not ask us!"
] | [['staff', 'neutral'], ['miscellaneous', '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... | ||
generation | mams | [
"He is a gracious chef who comes to the table and greets the guests."
] | [['staff', '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... | ||
generation | mams | [
"By dessert, I gave up and sat there hopelessly watching as my rice pudding was snatched away half eaten, only to be replaced immediately with a hefty bill."
] | [['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... | ||
generation | mams | [
"The waiter said they mixed it up because there were three similar things on the menu."
] | [['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... | ||
generation | mams | [
") Scores of employees walking around, but no one seems to clear a plate or offer more drinks."
] | [['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... | ||
generation | mams | [
"The manager also managed to insult one of my dining partners, even using an expletive to mock his last name when returning his credit card."
] | [['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... | ||
generation | mams | [
"Once we were seated our water order was taken promptly but they never came back with a menu."
] | [['miscellaneous', '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... | ||
generation | mams | [
"The waiter told us that he had checked with the kitchen because he noticed that we had not gotten our dinners and they said it would be out shortly, shouldn't someone have said something to us?"
] | [['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... | ||
generation | mams | [
"First of all, I think our service person was miffed that we couldn't order much for apps or drinks since we had already started at the bar."
] | [['service', 'negative'], ['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... | ||
generation | mams | [
"You have to be comfortable eating with your hands, sharing the same plate with your friends and be able to handle spicy food (not as spicy as some thai dishes though)."
] | [['miscellaneous', '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... | ||
generation | mams | [
"however, we went for lunch and were the only ones eating there and yet the service seemed eager for us to be done and to get out."
] | [['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... | ||
generation | mams | [
"Although the service was top notch, all of the food was disappointing: burnt octopus, bland ravioli, odd tasting mint love letters."
] | [['service', '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... | ||
generation | mams | [
"The portions were overly generous for both the apps and entrees without sacrificing the quality."
] | [['miscellaneous', '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... | ||
generation | mams | [
"We arrived on a Thursday night at 6:30 and were seated immediately (they don't take reservations), but, this small place filled up very quickly, and the bar was overflowing with people when we left."
] | [['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... | ||
generation | mams | [
"The place was packed, but it didn't effect our service or getting our food/drinks promptly."
] | [['place', 'negative'], ['service', '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... | ||
generation | mams | [
"The menu is slightly different from downtown, but they still have my favorites -- madai salad with hot sesame oil, shrimp kanzuri, the diamond roll, the crispy shrimp roll."
] | [['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... | ||
generation | mams | [
"But servers, attentive if slightly unpolished, gladly direct inquisitors to menu strengths--like rum-flambeed dessert bananas foster--and allow leisurely enjoyment."
] | [['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... | ||
generation | mams | [
"SO I ASKED, TO SPEAK TO THE MANAGER, AND ONE OF THE OWNER WHO MANAGES THE PLACE CAME TO MY TABLE, TOLD ME THAT THE CEVICHE WAS FRESH."
] | [['staff', '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... | ||
generation | mams | [
"It is far more popular as a bar than as a restaurant, with only a few tables and the waiter being the bartender, but we greatly enjoyed the unobtrusive atmosphere."
] | [['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... | ||
generation | mams | [
"Spoke with the manager about comping a round, after we had already paid for 2 rounds waiting for the table."
] | [['staff', 'negative'], ['service', 'neutral'], ['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... | ||
generation | mams | [
"For example, we had ordered a 2nd bottle of red wine, the waitress gave me a new glass to taste the wine, but filled up my existing glass (mixing two different bottles in one glass)."
] | [['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... | ||
generation | mams | [
"As for the main attraction, the pies are known for their crisp outer edge and gooey middle, and feature the unorthodox layering of sauce over mozzarella."
] | [['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... | ||
generation | mams | [
"The high prices and small portions reflect the hype of a new Battali restaurant as well as the cache that comes with having to make a reservation a week in advance only to wait to be seated."
] | [['price', '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... | ||
generation | mams | [
"I've never been during the dinner rush, whence I think most of the service complaints originate."
] | [['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... | ||
generation | mams | [
"the atmosphere is trendy, i think it's better to come here for a drink rather than dinner."
] | [['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... | ||
generation | mams | [
"Our dinner took over two hours because of the slow service."
] | [['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... | ||
generation | mams | [
"Weekday lunch is less crowded and the staff cheerfully tolerated a 3-year-old."
] | [['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... | ||
generation | mams | [
"Although the prices is a bit on the high, you do get big portions for it."
] | [['price', 'negative'], ['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... | ||
generation | mams | [
"It was my birthday and although they came out with of a bottle of bub, I felt embarrassed about the lack of service."
] | [['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... | ||
generation | mams | [
"Favorites include the Curry Shrimp w/ Mushrooms, Watercress Salad (not listed on menu), and Kao Soy noodle soup with chicken."
] | [['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... | ||
generation | mams | [
"The staff beginning with the tall gentleman at the door, waiters, etc."
] | [['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... | ||
generation | mams | [
"The food and service was top notch, only the complain is that this place is so small that some seats are not made for a big guy."
] | [['food', 'positive'], ['service', 'positive'], ['miscellaneous', 'negative'], ['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... | ||
generation | mams | [
"No bar only a waiting area with about 10 tables where you can have drinks prior to dinner."
] | [['place', '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... | ||
generation | mams | [
"The hostess was condescending and the waiter was somewhat absent and unaccomodating (sure, we made a reservation to sit outside but when I asked to be moved indoors after I heard thunder he didn't even try to make it happen, giving me a blank stare and a shrug when I asked what we would do if it rained)."
] | [['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... | ||
generation | mams | [
"The pieces were small but the fish was good quality and there wasn't a lot of rice to mess with."
] | [['food', 'negative'], ['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... | ||
generation | mams | [
"Miyagi is my sushi restaurant of choice in the Village; it's never insanely crowded, the service is very sweet (I've never experienced any of the nastiness described in prior reviews), and the tabs are small."
] | [['service', '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... | ||
generation | mams | [
"although the food was good, the wait was so long; extremely snobby about seating you, we waited 45 min + for our reservation."
] | [['food', 'positive'], ['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... | ||
generation | mams | [
"I was told(very snottily) no, but then not even 10 minutes later another group of people came in, asked the same thing and because the same woman waiter knew them she gave them regular menus!"
] | [['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... | ||
generation | mams | [
"It's so out there that it works--black-clad raver waiters and all--and even the most normal of groups love getting together for dinner and popular brunching on the palm-lined backyard patio spread."
] | [['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... | ||
generation | mams | [
"The waitress came to our table and told us about their tempting specials."
] | [['staff', 'positive'], ['miscellaneous', '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... | ||
generation | mams | [
"We asked the server for two glasses with a splash of Southern Comfort and Grand Marnier."
] | [['staff', '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... | ||
generation | mams | [
"throughout the whole meal, all I kept thinking was AVERAGE, AVERAGE, AVERAGE until the bill came, which was a little more than average,to say the least."
] | [['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... | ||
generation | mams | [
"We hung out by the bar mostly to ourselves, not an overwelming social crowd, but there were some georgous groups of hipsters looking like it was their meeting up before going out to the clubs (a few of the girls looked like top models), but the vibe was real chill."
] | [['place', '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... | ||
generation | mams | [
"The food is right out of heaven, arrive hungry because the portions are huge but not the prices."
] | [['food', 'positive'], ['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... | ||
generation | mams | [
"Went to celebrate my sisters birthday on 9/11 was 1st taken back on the waiters rude answering of a question we had about the menu."
] | [['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... | ||
generation | mams | [
"There is no bar so therefore no place to wait except the lounge that was packed so after wondering where to stand the hostess grabbed us."
] | [['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... | ||
generation | mams | [
"Before leaving the server gave us takeout 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... | ||
generation | mams | [
"Service is one thing but a restaurant like Craft needs to have much better quality food for the price they charge."
] | [['service', '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... | ||
generation | mams | [
"I would recommend going at off-times (before 7 perhaps) to avoid the crowds as it gets packed and there isn't much room by the 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... | ||
generation | mams | [
"The service was polite, friendly and prompt, the characters walking around entertained the kids but werent intrusive to our meal."
] | [['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... | ||
generation | mams | [
"If you've been out partying and have a yen for quality Korean food at 3:00am, there's a table waiting for you at Kang Suh Restaurant."
] | [['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... | ||
generation | mams | [
"And that is a shame as the restaurant is a pizzeria with a very limited menu outside of pizza."
] | [['menu', '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... | ||
generation | mams | [
"The waiter just slapped my food down and then never returned until he slapped my check down."
] | [['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... | ||
generation | mams | [
"The bartenders could have been a lot nicer but the drinks they shook up kind of made up for their poor attitude."
] | [['staff', 'negative'], ['food', '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... | ||
generation | mams | [
"there's always people waiting to be seated and the chairs are not comfortable."
] | [['service', '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... | ||
generation | mams | [
"Hillarious lighting and ecclectic side dishes make you want to love the place, but the meal on the whole was abyssmal."
] | [['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... | ||
generation | mams | [
"The waiter returned seconds later to complain that dozens of people wanted our table then poured her beer into a paper cup-- presumably to encourage us to leave faster."
] | [['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... | ||
generation | mams | [
"The Food The menu ably pulls off Bistro 101: The generous cheese plate makes a big enough starter for at least three people to share, and French onion soup is rich and decadent."
] | [['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... | ||
generation | mams | [
"However for the price I paid to have dinner there, you would have thought I ate a horse."
] | [['price', '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... | ||
generation | mams | [
"All this Asian fusion craze leaves one feeling like they should've went to an authentic Thai or Indian restaurant for probably 1/3 of the price of Spice Market."
] | [['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... | ||
generation | mams | [
"I went with a friend from out the town - the best thing on the menu was the Veal."
] | [['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... | ||
generation | mams | [
"The waitstaff is helpful and they'll get your favorite meats to circle your table more often if you just ask."
] | [['staff', 'positive'], ['food', '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... | ||
generation | mams | [
"One server came and gave us food that turned out to be someone else's."
] | [['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... | ||
generation | mams | [
"The food is not large and I could have had a few slices of pizza after I left."
] | [['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... | ||
generation | mams | [
"Our experience consistently reflected a lazy attitude by the house towards cooking technique and customer care."
] | [['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... | ||
generation | mams | [
"It appeared that they used a cheese pizza cooked earlier that day or the day before and just added the raw topping to it, then delivered it."
] | [['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... | ||
generation | mams | [
"The wine did not come until we were half way through our entree and the waitress overcharged us by a bottle of wine."
] | [['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... | ||
generation | mams | [
"service is good although a bit in your face, we were asked every five mins if food was ok, but better that than being ignored."
] | [['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... | ||
generation | mams | [
"Enjoy the food, because it is remarkable, but don't be too willing to be gratuitis to a server that does not deserve it."
] | [['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... | ||
generation | mams | [
"The waiter placed the wrong entree in front of us each time."
] | [['staff', 'neutral'], ['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... | ||
generation | mams | [
"The Romano family is very hands on with the father supervising the kitchen and Santo, the son, running the room with a high degree of personal attention."
] | [['miscellaneous', '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... | ||
generation | mams | [
"Gia Lam I' s service is not much better but the food was."
] | [['service', '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... | ||
generation | mams | [
"The atmosphere was warm, sexy, and very romantic but the lighting wasn't good for reading the menu."
] | [['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... | ||
generation | mams | [
"Forget the phony yuppies of Areos and The Pearl Room, and ENJOY the down home service and OUTSTANDING food here."
] | [['place', 'neutral'], ['service', 'positive'], ['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... | ||
generation | mams | [
"The wait was long which is understandable but the waiters were rude to us while we waited, rushed us to order, ignored us while we ate and needed more drinks, and rushed us when they wanted the table for another couple."
] | [['staff', 'negative'], ['food', 'neutral'], ['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... | ||
generation | mams | [
"The Chinese menu is gone, along with most of the good dishes."
] | [['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... |
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