diff --git "a/Generation/ACSA/train.jsonl" "b/Generation/ACSA/train.jsonl" new file mode 100644--- /dev/null +++ "b/Generation/ACSA/train.jsonl" @@ -0,0 +1,3149 @@ +{"task_type": "generation", "dataset": "mams", "input": ["It might be the best sit down food I've had in the area, so if you are going to the upright citizen brigade, or the garden, it could be just the place for you."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Hostess was extremely accommodating when we arrived an hour early for our reservation."], "output": "[['staff', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were a couple of minutes late for our reservation and minus one guest, but we didn't think we deserved the attitude we got from the hostess."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Though the service might be a little slow, the waitresses are very friendly."], "output": "[['service', 'negative'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Although we arrived at the restaurant 10 min late, the hostess did not have a table for us."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I like the smaller portion size for dinner."], "output": "[['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The bill was surprisingly inexpensive considering we each had appetizers, an entree, dessert and drinks (alcoholic and non) we also had 3 rounds of shots for the entire table."], "output": "[['food', 'neutral'], ['price', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": [") other food is served in too-small portions, but at least it leaves room for dessert."], "output": "[['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It was very loud, I felt too crowded, the man chair's next to me made it impossible for the waiters to pass."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After ordering drinks, we both decided on the Paella Vallenciana, brought out on hot plates."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Portions are fairly generous and the staff brings out multiple little bites and treats throughout dinner."], "output": "[['miscellaneous', 'positive'], ['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I had to ask for bread for the table (several times)."], "output": "[['food', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Specialty drinks--alcoholic and non--arrive in skull mugs or mini-canteens, nifty take-home souvenirs."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After reading other reviews I was expecting poor service and ambience but was pleasantly surprised by our more than helpful waiter."], "output": "[['service', 'negative'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I was told by the hostess that a specific table would be mine once the customers left and I waited 45 minutes for that to happen."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Towards the end of our meal, a server came out, apparently our orders had been double-filled."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food The casual Middle Eastern menu looks familar, but the food--made to order in the open kitchen--is a notch above its peers."], "output": "[['menu', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Upon entering, I was impressed by the room while the food on other peoples' tables seemed enticing."], "output": "[['food', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The beginning of the meal wasnt bad, the hostess was very nice, we got our drinks about every 10 minutes and the appetizers we good."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I found that the food variety was great, and the waitress was very accommodating to my vegan boyfriend describing all items' ingredients and how you may request more of what YOU like, creating a unique experience."], "output": "[['food', 'positive'], ['staff', 'positive'], ['ambience', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Came recommended to us, but we found the food to be so-so, the service good, but we were told we could not order desert since the table we were at had a reservation waiting."], "output": "[['food', 'negative'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waitress couldn't tell us what was in the seafood special, forgot to put in our oyster order so it came at the same time as the main meals, wasn't able to provide a confident recommendation from the menu, and had to be flagged several times for drinks."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I went back (with my cold soups) They said they would have to make me another dish since they couldn't scrape off the unwanted ingredients."], "output": "[['food', 'neutral'], ['ambience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Server's were extremely nice, yet were socializing too much with friends that were having drinks at the bar and it was difficult to get their attention."], "output": "[['staff', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["And there wasn't much room for the people at the bar to stand either, as the restaurant attempted to squeeze as many tables into the restaurant as they could, forcing those dining to have to shift in their chairs every time a waiter attempted to get by."], "output": "[['place', 'neutral'], ['food', 'neutral'], ['miscellaneous', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Went for an early V-Day dinner, only to be highly disappointed by the service."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Before our food arrived I asked our waitress if we could be moved and she just stared blankly at me."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service is excellent -- the staff is attentive and the waitress was well-informed about the menu."], "output": "[['service', 'positive'], ['staff', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I still go often, but the prices went up a little and the service is even slower now that they're always full during dinner hours."], "output": "[['price', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It is the only all Austrian wine list in the country and the waitress gladly broke it down for me, so I could find just the right wine for my meal."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["its a cool place to come with a bunch of people or with a date for maybe a mild dinner or some drinks."], "output": "[['place', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The final blow was when the waiter brought us the check before we had even finished dessert--never mind that the only reason we were taking a long time to finish the meal was because of the extreme delay in the service of our food."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["worst margaritas in town,if you are going to order a battle of (white wine)they served hot."], "output": "[['food', 'negative'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They served the main course before the appetizers eventhough we asked for the latter first, to which our waiter responded that they don't serve them separately without telling us beforehand while ordering."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After requesting to be seated at an empty table, the waitress (who was so terribly burdened when we asked to move from the bar to the table to have dinner) asked us to get up from our seats and wait for a smaller table because a party of 3 just walked in."], "output": "[['staff', 'negative'], ['place', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The place wasn't at all busy, and we were shown a table in the back, given our menus, and promptly forgotten about."], "output": "[['place', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Although the service can be a bit brusque at times, the food is always good, hearty and hot."], "output": "[['service', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food Despite a menu that seems larger than the restaurant, great care goes into the preparation of every dish."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Cornelia Street looks like a Broadway set for West Side Story and the inside of Po is so cool quaint you really can't top the setting for a romantic dinner in NYC."], "output": "[['ambience', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Be warned that this place can get pretty crowded, though the $3 bloody mary's at the bar and the killer DJ make the wait more than bearable."], "output": "[['place', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["As if that wasnt enough, after another in the group mentioned that a portion of the sushi on her plate was not what she had ordered, the waiter came back with chopsticks and started to remove it (as she was eating!)"], "output": "[['miscellaneous', 'neutral'], ['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We started with the guacamole and this is by far the best I've ever had bar none."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If you eat here, just keep in mind that the specials are much higher than the regular menu when ordering."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter was just throwing our dishes on the table without even clearing the appetizer plates and then they started clearing the food when we weren't even finished yet."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Before we can even order desert, the waitress comes and tells us we have to leave because the host wanted our table."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the tables are in the back and the ambience was less to be desired."], "output": "[['place', 'neutral'], ['ambience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["While service is still ok, the food has been not up to par on my last few visits."], "output": "[['service', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After the wine experience, I actually expected worse than what was served."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I dined in the Main Dining Room which is surrounded by authentic Spanish decorations."], "output": "[['place', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our server did not check on us, ask if we needed anything, refill our water or get our dessert order right."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["On ouor visit, our reservation was ignored and then we were asked to move from our seats at the bar, where we were told to wait, because we were not drinking enough."], "output": "[['miscellaneous', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food at Cafe Asean is to die for, and the prices are unmatchable."], "output": "[['food', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene The entrance leads into a dim, narrow bar decorated with sake bottles, exposed brick and a beautiful arched wooden ceiling."], "output": "[['miscellaneous', 'positive'], ['place', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It also has great ice cream and spumoni ices."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["However, the drinks are very good and this place is alright for brunch, if you don't mind sitting in a very cramped spot and/or waiting on line."], "output": "[['food', 'positive'], ['miscellaneous', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The ONLY negative was when we asked the waiter to secretly bring birthday cake and some other desserts for the table."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Sometimes, the take-out and seating lines can be long, but the staff help move things along."], "output": "[['food', 'neutral'], ['miscellaneous', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I went to Sushiden on a Friday night around 8:00, the place was pretty empty, we had reservations, but we didnt need them."], "output": "[['place', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["THE DECOR HAS BEEN UPDATED TO A FULL BLOWN RESTAURANT BUT THE QUALITY AND THE QUANTITY HASN'T CHANGED."], "output": "[['ambience', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["A+ was planning a party for my staff, and was treated rudely by another restaurant when trying to add more people to reservation (a simple no would have worked)."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food Regulars swear by the tamales, which are spongy, well-seasoned and pulled from steaming crocks on the counter."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Unfortunately, the food along with the unhelpful service doesn't make up for the atmosphere."], "output": "[['food', 'neutral'], ['service', 'negative'], ['ambience', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They expanded the seating with a cozy new back section, added some great new dishes (I had the most fantastic j erk Shrimp and exciting maize crusted salmon) but kept everything that was good (amazing staff and Mac Jack!)"], "output": "[['place', 'neutral'], ['food', 'positive'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Not to mention that the busboy spilled 2 glasses of water on my back and the Manager was NOWHERE TO BE SEEN."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Smiling servers quiz diners with movie trivia, but forget to fill their water glasses."], "output": "[['staff', 'positive'], ['price', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter was miffed when we decided to order dessert (and I must say we were eating the courses as they arrived, no lingering)."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Heck even if they had awful service and atmosphere I would still come to this place for their dumplings, luckly that is not the case."], "output": "[['service', 'negative'], ['ambience', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Chef Anthony is warm and is always fixing up something unique and tasty in the kitchen to send to your table."], "output": "[['staff', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu features classic French bistro fare, like steamed mussels with French fries and hangar steak with a green peppercorn sauce."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Had an after-work drink at the bar with a date, loved the place so much we came back for brunch the next morning."], "output": "[['food', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food was served promptly and was really hot."], "output": "[['food', 'positive'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The kitchen is open and surrounded by bar seating (the only kind of seating), and they have a nice set-up where the waitress stays behind the bar and the chefs deliver your food after you have watched them prepare it."], "output": "[['place', 'positive'], ['service', 'neutral'], ['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I had been to Blue Fin previously for drinks and appetizers and thought the atmosphere was very good (expecially for people watching)."], "output": "[['food', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The bar downstairs is a lot of fun, so if you get stuck waiting, just have drink."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere was nice (tables were a bit too close together) and trendy, but waiters seemed rushed."], "output": "[['ambience', 'positive'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We recently had brunch at this establishment with two other couples and I have to say I was majorly dissapointed with the service and how we were treated."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Although our waitress was pleasant and accomdating, the overpriced food was quite the opposite."], "output": "[['staff', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Their desserts were limited - I mean REALLY limited to 2 items (nothing like the online menu)."], "output": "[['food', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My group got charged an outrageuos $63/person for a family-style dinner, including a 23% tip added for the horrible service."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Bartenders look like model wannabes and threw out my friend's beer before he was finished (about 1/4 left)."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Perhaps if the owner manager would concentrate more on service then acting as a dj this restaurant would run better."], "output": "[['staff', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food at Parish was tasy and well-prepared, but the portions were absurdly miniscule, especially in proportion to the prices."], "output": "[['food', 'positive'], ['miscellaneous', 'negative'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["There is actually space to breathe and the decor sets the tone for an intimate dinner."], "output": "[['place', 'neutral'], ['ambience', 'positive'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere was really nice and inviting but our waiter was awful!"], "output": "[['ambience', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I always listen to the waiters' recommendations, because they're always awesome - either a special or just one of their faves off the menu."], "output": "[['staff', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The decor is sparse and elegant, the service warm (though my waitress was occasionally difficult to find), and the sushi fresh."], "output": "[['ambience', 'positive'], ['service', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I waited 15 minutes for the waiter to take the bill from me and finally I got fed up with him walking past our table I had to start waving the bill in the air and finally some other waitress took our bill."], "output": "[['staff', 'negative'], ['ambience', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Yes, the wait is long and ridiculous as times, especially as you watch others gobble down their food."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["considering the prices on the menu, i'd rather go somewhere else where they know how to refill water and real chairs for everyone, something you can even get at mcdonald's."], "output": "[['price', 'neutral'], ['menu', 'neutral'], ['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It was practically impossible to get the waitstaff's attention to order another bottle of wine."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After spending over $500 on a business dinner, a manager knelt down at our table and asked us to quote, wrap it up and move to the bar."], "output": "[['food', 'neutral'], ['staff', 'negative'], ['miscellaneous', 'neutral'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Friendly staff happily accepted a reservation (for 10), and when only 6 showed up, they couldn't have been more understanding!"], "output": "[['staff', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["At our table we didn't get any bread until 30 minutes into the seating, which may I emphasize the waiter took really long to come to our table, about 20 minutes."], "output": "[['place', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Recently I purchased a dish to go, and found that all of my meal contained just one large piece of ginger root."], "output": "[['food', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The numbness in your lower legs from sitting on old wood chairs is more than compensated by the wonderful food."], "output": "[['miscellaneous', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were able to reserve a spot at the chef tasting bar with Morimoto who actually called in sick that night, but we were still charged full price."], "output": "[['place', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Went here for a casual Sunday night dinner at 7:45pm; dinner was served at 10:15pm!"], "output": "[['miscellaneous', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Then, the waitress gave my wife coffee with regular milk in it even though my wife specifically requested Soy Milk."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I thought I'd give the new place a try since it had an expanded menu and a more legit look."], "output": "[['place', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["*There is a pre-theatre dinner menu for early diners that is of great value."], "output": "[['menu', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The prixe fix menu was a deal to boost downtown restaurants, atleast we didn't pay the full price."], "output": "[['menu', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['staff', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['food', 'negative'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food was so-so and you would think it was a french resturant, the portions were so tiny."], "output": "[['food', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Eventually another waiter cleaned up the table and allowed us to sit there."], "output": "[['staff', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['staff', 'negative'], ['place', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["seems everyone ordered sushi there were tons of delivery orders (we can tell as we sat near the back)."], "output": "[['food', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["small price to pay to have dinner on a Saturday night in downtown Manhattan."], "output": "[['price', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['miscellaneous', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['service', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The interior is understated making it special enough to take a date but easy enough to stop in anytime for dinner or snack."], "output": "[['place', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The prices are incredibly reasonable, especially considering the HUGE portions - by noodle soup could have fed both my husband and myself."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["There is a huge line, usually a 45 minute wait; they take no reservations and no tables of more than five people."], "output": "[['service', 'neutral'], ['miscellaneous', 'negative'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The pizzas are a MUST TRY, hence the name."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['food', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['miscellaneous', 'neutral'], ['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The wait was much shorter than the hostess quoted, which was great."], "output": "[['service', 'positive'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When we got our food, the waitress barely said a word as she placed our take-out on the table and grabbed the check."], "output": "[['food', 'neutral'], ['staff', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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)."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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)."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['place', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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!"], "output": "[['staff', 'neutral'], ['miscellaneous', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["He is a gracious chef who comes to the table and greets the guests."], "output": "[['staff', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['food', 'neutral'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter said they mixed it up because there were three similar things on the menu."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": [") Scores of employees walking around, but no one seems to clear a plate or offer more drinks."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Once we were seated our water order was taken promptly but they never came back with a menu."], "output": "[['miscellaneous', 'positive'], ['menu', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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?"], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['service', 'negative'], ['food', 'neutral'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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)."], "output": "[['miscellaneous', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Although the service was top notch, all of the food was disappointing: burnt octopus, bland ravioli, odd tasting mint love letters."], "output": "[['service', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The portions were overly generous for both the apps and entrees without sacrificing the quality."], "output": "[['miscellaneous', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['miscellaneous', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The place was packed, but it didn't effect our service or getting our food/drinks promptly."], "output": "[['place', 'negative'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["But servers, attentive if slightly unpolished, gladly direct inquisitors to menu strengths--like rum-flambeed dessert bananas foster--and allow leisurely enjoyment."], "output": "[['staff', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['staff', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['place', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Spoke with the manager about comping a round, after we had already paid for 2 rounds waiting for the table."], "output": "[['staff', 'negative'], ['service', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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)."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['price', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I've never been during the dinner rush, whence I think most of the service complaints originate."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the atmosphere is trendy, i think it's better to come here for a drink rather than dinner."], "output": "[['ambience', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our dinner took over two hours because of the slow service."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Weekday lunch is less crowded and the staff cheerfully tolerated a 3-year-old."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Although the prices is a bit on the high, you do get big portions for it."], "output": "[['price', 'negative'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It was my birthday and although they came out with of a bottle of bub, I felt embarrassed about the lack of service."], "output": "[['miscellaneous', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Favorites include the Curry Shrimp w/ Mushrooms, Watercress Salad (not listed on menu), and Kao Soy noodle soup with chicken."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The staff beginning with the tall gentleman at the door, waiters, etc."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['food', 'positive'], ['service', 'positive'], ['miscellaneous', 'negative'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["No bar only a waiting area with about 10 tables where you can have drinks prior to dinner."], "output": "[['place', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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)."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The pieces were small but the fish was good quality and there wasn't a lot of rice to mess with."], "output": "[['food', 'negative'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['service', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["although the food was good, the wait was so long; extremely snobby about seating you, we waited 45 min + for our reservation."], "output": "[['food', 'positive'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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!"], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitress came to our table and told us about their tempting specials."], "output": "[['staff', 'positive'], ['miscellaneous', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We asked the server for two glasses with a splash of Southern Comfort and Grand Marnier."], "output": "[['staff', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['food', 'neutral'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['place', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food is right out of heaven, arrive hungry because the portions are huge but not the prices."], "output": "[['food', 'positive'], ['miscellaneous', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['place', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Before leaving the server gave us takeout menus."], "output": "[['staff', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Service is one thing but a restaurant like Craft needs to have much better quality food for the price they charge."], "output": "[['service', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['miscellaneous', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service was polite, friendly and prompt, the characters walking around entertained the kids but werent intrusive to our meal."], "output": "[['service', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['food', 'positive'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["And that is a shame as the restaurant is a pizzeria with a very limited menu outside of pizza."], "output": "[['menu', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter just slapped my food down and then never returned until he slapped my check down."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The bartenders could have been a lot nicer but the drinks they shook up kind of made up for their poor attitude."], "output": "[['staff', 'negative'], ['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["there's always people waiting to be seated and the chairs are not comfortable."], "output": "[['service', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Hillarious lighting and ecclectic side dishes make you want to love the place, but the meal on the whole was abyssmal."], "output": "[['place', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["However for the price I paid to have dinner there, you would have thought I ate a horse."], "output": "[['price', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['food', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I went with a friend from out the town - the best thing on the menu was the Veal."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitstaff is helpful and they'll get your favorite meats to circle your table more often if you just ask."], "output": "[['staff', 'positive'], ['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["One server came and gave us food that turned out to be someone else's."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food is not large and I could have had a few slices of pizza after I left."], "output": "[['food', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our experience consistently reflected a lazy attitude by the house towards cooking technique and customer care."], "output": "[['service', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['food', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The wine did not come until we were half way through our entree and the waitress overcharged us by a bottle of wine."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['service', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Enjoy the food, because it is remarkable, but don't be too willing to be gratuitis to a server that does not deserve it."], "output": "[['food', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter placed the wrong entree in front of us each time."], "output": "[['staff', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['miscellaneous', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Gia Lam I' s service is not much better but the food was."], "output": "[['service', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere was warm, sexy, and very romantic but the lighting wasn't good for reading the menu."], "output": "[['ambience', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Forget the phony yuppies of Areos and The Pearl Room, and ENJOY the down home service and OUTSTANDING food here."], "output": "[['place', 'neutral'], ['service', 'positive'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Chinese menu is gone, along with most of the good dishes."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the waiter was unable to identify whether certain cheeses from the cheese course were cow or goat milk."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Ziti Bolognese is baked in a similar sauce, with ground meat mixed in and cheese melted on top--the menu offers many variations on this theme."], "output": "[['food', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I just got back from dinner from this UES hotspot - it is like a home away from home - delicious meals and a salad dressing that sometimes they let me have a tiny container of for my lunch at work salads - the price/ atmosphere/ cocktails (FULL BAR!!!"], "output": "[['food', 'positive'], ['ambience', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Food was served very promptly, but our wait for drinks was surprisingly long."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["While waiting there was no room for standing and the bar staff and their drinks were horrendous."], "output": "[['service', 'neutral'], ['staff', 'negative'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The word chicken was barely out of my mouth when the waiter rushed away from my table without asking me about side orders or a drink."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The scene is pretty cool and the drinks are OK, but the food and service were pretty weak."], "output": "[['miscellaneous', 'positive'], ['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The decor maybe great for young kids but as an adult this place was an horrible experiance, it didn't bring the kid in me."], "output": "[['ambience', 'positive'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Del Frisco's is pricey and I was seated in a leper locker room area, but the food was totally fantastic."], "output": "[['place', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitress was no where to be found at all throughout the course of the meal, did not refill a single drink nor did she bother to inquire about my satisfaction with the food or even bring the check at the conclusion of the meal."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The four of us were seated in the outdoors patio(not requested) and suffered through a muddled menu, indifferent food, a below average waiter, as well as excessive noise, wind and cold."], "output": "[['menu', 'negative'], ['staff', 'negative'], ['ambience', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter was rude to my friend when she asked for a small plate to share an appetizer."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service was slow (10 minutes for drinks??)"], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["True, the menu doesn't offer a wide range of choices and portions are not la all-you-can-eat, buffet style (but is that a negative thing after all?"], "output": "[['menu', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter, though he was charming,was too busy to truly take care of us properly and the food was over priced."], "output": "[['staff', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The staff forgot my girlfriend's food altogether as she waited for half an hour."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We decided to get out of there and go to a safe place with bigger portions and normal food."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["One oversight: the gf wanted tea to go along with the plate of yummies they gave me, but the server forgot to bring it since we took our time to finish the wine."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I have tried everything available on the AYCE menu, it has all been quite good (although I am not one to be especially particular with food, sushi in particular."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service was not the greatest, but the place is huge and it has a nice setting."], "output": "[['service', 'negative'], ['place', 'positive'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service is not very good, but I find that we try Atlantic Grill at least once a year."], "output": "[['service', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["straining to read the menu under the low-lighting-tag-sale-chandelier motif, we were able to order a salad, tapas, and entrees from the first of several waiters, none of whom were able to introduce themselves, recommend dishes, present silverware, remove plates, or deliver water when asked."], "output": "[['menu', 'neutral'], ['food', 'neutral'], ['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I came here b/c someone gave a trashy review to my favorite coffee place (Grey Dog's) and compared it to this place so I had to see for myself what was so great about 71."], "output": "[['place', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["One night we landed at the bar for a late night dinner, and the hanger steak and frites w/ marjoram aioli was the BEST."], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I have to agree with the previous review that the atmosphere isn't much, but Mister Falafel can't be beat for quick, delicious, cheap takeout."], "output": "[['ambience', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["However, you don't even really need the menu, because the daily specials are always tempting and delicious."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service is ok since it is new and the staff didn't know the food items too well."], "output": "[['service', 'positive'], ['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Another hostess came by and told us that since we were now 5 we were a different table and couldnt' stay."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were even able to call in advance to make sure there was space at the bar because I was on crutches and the owner reserved the seats til we got there."], "output": "[['place', 'neutral'], ['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Charming atmosphere that seats probably no moroe than 35."], "output": "[['ambience', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We orderes and our food took about 1 hour to get it, after the long wait."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Be warned - between the pizza and spumoni the place is packed nightly in the summer."], "output": "[['food', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We had hot buffalo tenders for an appetizer, and the waitress didn't bother to come back to check on how we were doing on drinks."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The actors try to draw your attention away from the better stuff that is happening below."], "output": "[['miscellaneous', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The small single room--wood panelling, large mirrors, white tablecloths, dim lighting--has few frills."], "output": "[['place', 'negative'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["our waiter forgot a dish and we were constantly checked on afterwards and treated to a complimentary dessert for the mix up."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The staff had apparently booked the room for 2 groups with a 30 minute overlap."], "output": "[['staff', 'negative'], ['place', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["And price is over value for two persons dinner $ 90."], "output": "[['price', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The owners are incredibly nice too, comping pitchers of margaritas if you sit there and eat for a couple of hours."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere would have been almost perfect if it werent for the fact that we were seat right naext to the noisy kitchen but I guess the speedy service comes with a price."], "output": "[['place', 'negative'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After my friend and I were seated, we were greeted by a gorgeous waitress, who helped us make our way through the large selection of choices on the menu."], "output": "[['staff', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter was completely unfamiliar with the menu and did not bother to tell us that they were out of several items (even though we arrived at 7 pm on a Saturday night!)"], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Food was at best, mediocre and when the bill finally came they had nerve to add on 20% gratuity even though there was nothing stated on the menu or anywhere that gratuity was included for a party of 5 (usually a party of 6 is gratuity inclusive)."], "output": "[['price', 'neutral'], ['menu', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service is sweet and attentive, the wine is delicious and the new wine bar around the corner has the most amazing selection, as well as cheeses and tapas."], "output": "[['service', 'positive'], ['place', 'neutral'], ['miscellaneous', 'positive'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food The Portuguese knack for exploration couldn't be more apparent on the expansive menu, which moves beyond classics like bacalhau to encompass a world of former colonies along with the motherland."], "output": "[['menu', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["And when I received my $9 glass of wine, I had to ask the waitress if she planned on putting more in -- there was hardly any liquid in the glass!"], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were seated next to some obnoxious women who bogarted the server's time and attention, so he bought us drinks."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["From chicken wings and smoked beef brisket to pulled pork and Texas links, the menu features many barbecue favorites."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food The menu seems quirky, but upon a closer look ingredients are familiar and made into appealing combinations, with influences from Maine to the Mediterranean."], "output": "[['food', 'positive'], ['menu', 'positive'], ['ambience', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["While admitably, the seating is a bit cramped, and the menu a tad pricey, the staff does its best to remedy concerns."], "output": "[['place', 'negative'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I couple of weeks ago we went to Supper in the east village and it was so bad that we got up and left and the only way to save the evening of horrible food was to go to Blue Ribbon Bakery and have at least one thing off the menu."], "output": "[['food', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["employees not fighting with each other in front of clients 3 having ALL the ingredients for the meals they have on there menue."], "output": "[['staff', 'negative'], ['ambience', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["A hard-drinking, upscale crowd, holding conversations over loud Latin jazz music, packs the small, open dining room and attached bar."], "output": "[['ambience', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The decor reminds me of Miami nightclubs, and we sat in a cool communal strip, where you share your table with people."], "output": "[['ambience', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Beautifull people, and a dj that was making me just want to stay and drink more!"], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Good place for groups of four or large parties but it is not a cozy/intimate setting for 2 although the jazz helps!"], "output": "[['place', 'positive'], ['ambience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We got seated right away, We got a nice starter from the kitchen, unfortunately the waiter that brought it could not explain what it was, it was delicious though."], "output": "[['food', 'positive'], ['place', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Her attitude put a damper on the evening, as did the stares from some servers when we took a peek into the cheese cellar."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After a short 30 minutes of chatting and enjoying our drinks we were approached by the very pretentious Maitre D' who RUDELY demanded we order as our table was needed."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We had to ask the busboy if bread came with our meal, which it did and we received after waiting about 30 minutes."], "output": "[['staff', 'neutral'], ['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Yet the maitre d still sat us next to the bar."], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We arrived, were greeeted and sked by the hostess I think if we were there for the Brunch, that was starting up again on today(3/12) the cost $25 per person."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu includes the usual Chinese restaurant staples, but also includes a fairly diverse selection of other dishes not typically found in your average noodle house."], "output": "[['menu', 'neutral'], ['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["And once the bill was paid, the bartender kept on giving us drinks."], "output": "[['price', 'neutral'], ['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The bartender had offered us ONE beer on the house for our troubles."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We had to request water and chips (tostades) and salsa three times (the third time my date had to go and track down the waitress) before finally being served (by the busser) and the place wasn't even a quarter full."], "output": "[['food', 'neutral'], ['staff', 'negative'], ['service', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When we ordered our Margaritas, the waiter said $10, so we gave him a 20 and waited, and when he didn't give us our change, we asked and he said - Happy Hour's over, they're $10 each."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We objected at the ill flavor of the drinks and the manager was not understanding at all."], "output": "[['ambience', 'negative'], ['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Great tasting meat, intimate if slightly noisy ambience and the service is slightly less attentive than it could be but is done with charm."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["This pizza shop is one o fhte best places ever and is a hiden gem in a small community."], "output": "[['food', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Tasting menu a mixed bag: lobster soup amuse with grapefruit intriguing, but marred by excess bitterness as prepared."], "output": "[['menu', 'positive'], ['miscellaneous', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["In addition, I've always found the waiters helpful with the wine selection, and there is always a good selection of wines by the glass."], "output": "[['staff', 'positive'], ['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I STRONGLY recommend to try something other than typical menu items and go for the short ribs over rice, black cod, sea bass, or duck (there are two dishes that are great)."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Although the portions seemed a little diminutive at first, they turned out to be the perfect size once the dinner was over."], "output": "[['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food was great but the music was loud and hip-hop and the wait was ridiculous and the prices were out of this world."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Invited by friends to discuss business, I checked out the bar first, and didn't give my nme which was known to the owners Scott Heather."], "output": "[['place', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["There were a lot of scensters who couldnt afford dinner hanging in the waiting area so we got bumped around a lot."], "output": "[['food', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I had high hopes for this high-ranked wonder, only to be let down by inattentive service doubled by LONG food and drink wait times."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["In any case, the food was quite yummy and on monday nights, they have a prix fixe $25 dinner which is definitely a deal."], "output": "[['food', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu might have well been written in a foreign language and the wait staff didnt have a translation dictionary!"], "output": "[['menu', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food There's something for fish fans of every stripe on the lengthy menu."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["At one point, we tried to get our waitresses attention and she ignored us and than we asked for more biscuits and never got them."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["One would think we'd get an apology or complimentary drinks - instead, we got a snobby waiter wouldn't even take our order for 15 minutes and gave us lip when we asked him to do so."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Staff would not change a meal to accomadidate food allegeries."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food will eventually make you outweigh Anna Nicole Smith."], "output": "[['food', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The manager finally came by to apologize and offered to give us a greek salad on the house."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Helpings are HUGE and most come with choice of rice and beans, or salad and plantains."], "output": "[['service', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Sometimes when I come home from work I stop at the bar to have a plate of oysters and something delicious for dinner."], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter was pretty anxious to get us in-and-out, although there were ample tables and my friend and I opted to sit at the bar."], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitress waited until I went to the bathroom to ask my friend to order more food."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I was NOT told this before when I made the reservation and explained to the manager RICHARD who has the poorest customer service ever and rude and said he didn't believe me."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food is decent but small portions so expect to order a lot."], "output": "[['food', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Everything on the menu is worth trying at least once, from the calamari/zucchini appetizer, to the homemade cavatelli, to the rib eye steak (like butter!)"], "output": "[['menu', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["For the high price you would pay (dinner for the two could run $80), you sure do get alot."], "output": "[['price', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["This time, the service was decent and the food was mediocre at best."], "output": "[['service', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The garden is lovely, too, but the staff seems a bit condescending."], "output": "[['place', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The advertised unlimited mimosas and bloody marys is too good to be true until you realize that they keep down your drink count because the service is so slow."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I have seen the crowd go from ultra hip to BT and I still love it becuause of the food."], "output": "[['miscellaneous', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["finally, onto dessert, wherebv the waiter told us he would have to scrape the bottom to give us any ice cream."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Great place for either appetizers and drinks at the bar, a romantic dinner or late night partying."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Not ony did our waiter impose on the dessert we were trying to enjoy to take the money -- he didn't even ask us if we wanted change -- nor did he bring us back any!!!"], "output": "[['staff', 'negative'], ['food', 'neutral'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The scene is a bit much some time, but the food is worth it."], "output": "[['miscellaneous', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["18 has a cozy romantic atmosphere that's very comfortable to enjoy myself in; whether I want to have a drink at the bar or get together with a group of friends for dinner, suitable accomodations are available."], "output": "[['ambience', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["As well, I haven't eaten animal products in over 6 years and the waiter was not sure which dishes had honey or casien in the food."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Even with reservation, it might take up to one hour to get a table and the staff might not even say a word about it."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When you crave comfort food, make a reservation and head to Piccolo Angolo, they never dissappoint."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My dinner partner ordered the angel hair with seafood - the portion was easily big enough for two."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were however seated right away and was immediately told by our waiter that they were out of sparking mineral water."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The limited number of toppings prevented the sogginess described by other reviewers and allowed the intense flavors from the fresh ingredients; sauce, mozarella, basil and black olives to really shine through, without being watered down from too many extra toppings."], "output": "[['ambience', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We went on a Monday night around 6:30pm and were seated right away in the backroom, which is dimly-lit, casual, cozy--kind of felt like you were sitting in a spacious dining galley of a ship or a cabin."], "output": "[['service', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["All dishes are an incredible dining experience."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service can be lacking at times, but the desserts and overall experience certainly counter this flaw."], "output": "[['service', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene Strictly Roots, which opened more than a decade ago as a dietary alternative to Harlem's more cholesterol- and fat-heavy fare, wears its philosophy on its facade: We serve nothing that crawls, walks, swims or flies."], "output": "[['miscellaneous', 'neutral'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["ONE OF THE BEST PIZZA IN BROOKLYN , NEED AN AC FOR SUMMER."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["As for the menu, I've never been disappointed, but the Margarita chicken salad is my favorite."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["At this level, I want my servers to know more than me about the food and I didn't get that sense."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Well i asked the server to describe a certain wine for me,he seemed like he knew what he was talking about,till i tasted it,it was totally the opposite of what he described."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu is limited: chicken, rice beans, frozen fish (shrimp, whiting, crab sticks), and french fries, but one receives EXCELLENT value for the money and it is SO WORTH walking down the block for."], "output": "[['menu', 'negative'], ['food', 'neutral'], ['miscellaneous', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["As to the fact that everyone else's sushi looked better: the waitresses are not responsible for offering you what is CLEARLY written on the menu as Omakase - Chef's Choice."], "output": "[['food', 'positive'], ['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Owner Mary Redding keeps things fish camp-y with rod-and-reel rental prices and a list of rules on the backs of the menus."], "output": "[['staff', 'neutral'], ['food', 'neutral'], ['price', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The other steaks on the menu were $30-$40, so the waiter really should have told them the price of the special."], "output": "[['menu', 'neutral'], ['staff', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["their Stella on tap was almost flat, i saw the bartender whisking our beers to give them any sort of head."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When I questioned the purpose of waiting on this line, I was asked to leave the bar."], "output": "[['service', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We waited forever for our bill but did have a nice conversation with one of our waitstaff during our meal."], "output": "[['price', 'negative'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I managed to get the last reservation at 11:15pm during the week, and, upon entering the restaurant, my boyfriend and I were seated next to each other, hardly a romantic atmosphere!"], "output": "[['miscellaneous', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Do not use this place unless you want to waste your money on horrible stale cheese and food, service which takes your drinks away from the table once you've placed it on the table, waiters that eat your desert while its on the table, non working faucets in the bathroom, and overall very unporfessional service and food."], "output": "[['food', 'negative'], ['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Then the food came- TINY portions and plates came out in 15 min intervals."], "output": "[['food', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Later two waiters decided to bodyguard our table; when my fork hits the plate it's snatched away."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The dramatic space complements the food and will wow out-of-towners."], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The ambiance is nice, but the wait staff was rude and unattentive."], "output": "[['ambience', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Management or one of the many busboys should have been monitoring the tables more closely to ensure consistency - we had to ask for olive oil for the flatbread, when it was on nearly every other table as well as salt and pepper."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter comes over and says You changed the salad and made us throw it out!"], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were a party of four, and after a long wait, were seated in a freezing corner."], "output": "[['service', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Husband and Wife owners are always pleasent and accomidating, food is top notch quality made with care, and now, recently renovated to accomidate more tables and a young fresh feel."], "output": "[['staff', 'positive'], ['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They overfill the reservation sheet so that the check is dropped off nearly with your food and they are rushing you out of your booth before you are finished."], "output": "[['miscellaneous', 'neutral'], ['food', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitress came to our table once for our order, but then we were tended to by who I thought was the hostess."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It took 1 1/4 hours to get our appetizers (how long does salad take) and when we complained to the manager, he barely listened."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["For such an expensive place, you can find much, much better in Manhattan; heck, you can find much better food for a lot cheaper!"], "output": "[['place', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Went there for a dinner; nice little place."], "output": "[['food', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the peanut sauce came in a tiny plastic cup smaller than a shot glass."], "output": "[['food', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Service was friendly, but not terribly attentive, took 30 minutes after dinner to clear our plates, and another 20 to get our check."], "output": "[['service', 'positive'], ['food', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Try Le Madeleine for a similar price but much better food."], "output": "[['price', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our server, Ben, was perhaps the best waiter I've ever had--he walked us through the menu to design our meal, and suggested what textures, tastes, and wines would complement each other."], "output": "[['staff', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["There is almost always an hour wait at dinner time, but this may be the best Japanese Sushi restaurant in NYC."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service was okay, fast seating (for two), looked like a group nearby had been there a long time."], "output": "[['place', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Nothing wrong with the service, either, but don't we all want something more from a dining experience than just average for above-average prices?"], "output": "[['service', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our bill total was only $30 and our waiter threw in a side of linguini (no charge) since the entrees don't come with pasta sides."], "output": "[['price', 'neutral'], ['staff', 'negative'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If you like a cleaner (more generic) flavor then other places may provide the norm."], "output": "[['ambience', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["But on a recent Sunday brunch excursion, I was greeted by a uniformly unfriendly staff - starting with the hostess and extending to foul faced wait staff."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["For far better fish at the same price (but less interesting roll combinations), try Yama, just around the corner."], "output": "[['food', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["For the most part I enjoyed my dining experience at Revival (not to be confused with the bar on 15th)."], "output": "[['miscellaneous', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Martinis from the bar are mixed at the size of 1 1/2 drinks, and the wait staff leaves the whole glass there, returning to pour you your remaining drink as your glass empties."], "output": "[['food', 'neutral'], ['place', 'neutral'], ['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food The menu lists affordable soul food and barbecue favorites."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It's unfortunate because the food is generally pretty good, although the waitstaff did try to convince us once that the flan they gave us was really creme brulee."], "output": "[['food', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We organized a party at this bar and have gotten very poor service."], "output": "[['place', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After taking unusually long to bring the wine, the waiter could not open the bottle and had to get a different one."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Mushroom appetizer was doused in a gross mayonnaise like sauce and had not been described that way on the menu."], "output": "[['food', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Always try one of the daily specials, in addition to all the tasty morsels on the menu."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When his to sons joined the mix they took Dads quest for the best food another step adding slowly to the menu a host of items that reflect the demigraphic of this still growing nabe."], "output": "[['miscellaneous', 'neutral'], ['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We waited to be seated for about 15-20 minutes for brunch, while it was quite obvious that there were plenty of empty tables right in front of us."], "output": "[['food', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When I asked the waitress, she told me they couldn't afford the salmon, and had changed the dish (though not on the menu)."], "output": "[['staff', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene Hunky waiters dub diners darling and it sounds like they mean it."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Waited 8 minutes for them to set up the table, another 10 to take our orders and 1 hr plus later for the waitress to say the food is coming in 2 minutes."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The restaurant has a Family feel, not least with regard to the portions which are enormous; the veal alone could have single-handedly solved third world famine."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The staff treated me as if I were a celebrity, which I am not and they did not make me feel uncomfortable as a single diner."], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My friend and I went out for a cigarette, and when we returned, our table had been given to another party- even though our drinks and unpaid bill were still on the table."], "output": "[['food', 'neutral'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["MY FATHER ASKED FOR A MARTINI MADE A CERTAIN WAY THE WAITER HAD NO CLUE WHAT HE WAS TALKING ABOUT."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["What does it say about an establishment and its chef when its policy forces the Price Fixed, Chefs Choice Menu on every party six or greater?"], "output": "[['price', 'negative'], ['staff', 'neutral'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I usually run the other way when I hear of an Italian restaurant with huge portions, because it's usually a lot of mediocre food."], "output": "[['miscellaneous', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I had a 9pm reservation and wound up sitting down closer to 10, but the bar was entertaining enough for the almost-an-hour wait (excellent martinis)."], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After taking our orders, another person came to the table to announce the special dishes which the waiter forgot prompting 2 in our party to cancel the original orders in favor of the specials."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I had reservations for a week but was seated at the worst table in the room,against a wall near the entrance to the kitchen,very claustaphobic."], "output": "[['miscellaneous', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["even if you have to wait for a spot at the bar to wait for your table, the music and design of the space create an ambiance that is simultaneously chic and comfortable - something extraordinarily difficult to find in this city."], "output": "[['miscellaneous', 'neutral'], ['place', 'positive'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["In Short Despite the tacky Hellenic decor, replete with faux columns and signs of the zodiac carved into plaster walls, this Greek restaurant and bar bursts with authenticity when it comes to menu and atmosphere."], "output": "[['ambience', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The table next to us had hummus which looked delicious, so we really should have stuck to appetizers and wine."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When we mentioned it to the waiter, he shrugged and asked what we expected from a glass wine."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Then we were seated at a large booth and it took the waiter 20 minutes to come back and take our order but I sort of expected that with a new restaurant."], "output": "[['place', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food was not terrible but with the prices as high as they are, I should expect better."], "output": "[['food', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I had dinner with my friend, and regardless of our $100 check, I overheard the waiter say that we had been there too long."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I had my brand new $15 lip gloss on the table and the waiter threw it away."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["One gentleman ignored us most of the time and would plunk the coffee down and spill it on the table without saying a word."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I walk in ask to take a look a the menu and was greeted by the a nasty not so passive aggressive hostess."], "output": "[['menu', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Plenty of tables avail for no reservation in bar areain case you want to go on an expensive date for not so great food."], "output": "[['place', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["07 menu was a deal to try this hip tribeca restaurant but the wrong dessert was sent to the table."], "output": "[['food', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The ambience and service here are great but the food was really awful."], "output": "[['service', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My water was filled like eight times, good, fast service."], "output": "[['food', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My husband doesn't like vegetables and made a point to ask the waiter if he could have a side of pasta instead."], "output": "[['food', 'negative'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["On my first visit, I asked the waiter to please wrap my leftovers and was refused adamantly (he told he wasn't allowed to package the low-priced food)."], "output": "[['staff', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I honestly do not understand how anyone can not love this place, unless they don't like real pizza."], "output": "[['place', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We had the 5 course tasting menu and had the waiter select a perfect bottle of wine to go with our selections."], "output": "[['staff', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Huge selection of farm roasted coffee served with a smile, absolutely no attitude, and accompanied with the best pastries in Manhattan."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When my (pregnant) friend asked about a non-alcoholic version of a drink, the answer was simply no, with no further suggestions."], "output": "[['food', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The $5 menu does have smaller portions, and I found the ravioli dish to be not too much better than a can of Chef Boyardee."], "output": "[['menu', 'neutral'], ['miscellaneous', 'negative'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I went to the Hudson bar with my boyfriend and the guy at the front door was extremely rude."], "output": "[['place', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["In Short A dark, narrow takeout area gives way to small tables in a cozy space decorated to resemble a Bedouin tent."], "output": "[['food', 'negative'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Since the menu is not organized in the way to describe the size of each dish, and there is no omakase nor a course, waiter's recommendation may be crucial to decide what to order, but he just recommended what he likes without considering appropriate amount for one person, and even served shellfish to whom who had mentioned she is allergic to shellfish!"], "output": "[['menu', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["A reservation did not save us from a wait at the bar, but the food was worth it; a grilled calamari appetizier with mushrooms was delicious as was a mixed seafood pasta main course."], "output": "[['miscellaneous', 'neutral'], ['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The bartender was skilled, the owners were very friendly, but the wait for my burrito was longer than I would have liked."], "output": "[['staff', 'positive'], ['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Their cappuccino's are served in a generous mug with a bit too much milk and too-sudsy foam."], "output": "[['service', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I go there to eat dinner, brunch, or to just drink and hang out at the bar with the friendly staff."], "output": "[['food', 'neutral'], ['place', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Went to dinner for a law firm recruiting event, and the service was abysmal."], "output": "[['food', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Showed up last Sunday night with girlfriends and no reservation, host was very helpful finding us a seats at bar after short wait."], "output": "[['staff', 'positive'], ['place', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Food - mostly steak and fish - is decent, but the portions are obscene - filet mignon and salmon were HUGE, but they don't come with any side dishes - you have to order and pay extra for them which is inconvenient and expensive."], "output": "[['food', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Justin our waiter, explained to us that the menu changes daily, more of a reason to return."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["So when i walked in i was just blown away by the lighting, flowers, wood and iron work, a reservationist, and a full bar."], "output": "[['ambience', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My entree was just some noodles in a butter sauce with no texture or color, except for a little bit of spinach which was more like a garnish."], "output": "[['food', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Unfortunately, our waiter set quite a different tone; he disappeared until the end of our meal, when we had to beg for coffees and desserts."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After two terrific meals in the dining room, we opted to sit at the bar on our third visit."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Decor is simple yet functional and although the staff are not the most attentive in the world, you don't feel rushed and the food is good, hot with decent portion sizes and a good selection to suit most tastes."], "output": "[['ambience', 'positive'], ['staff', 'negative'], ['food', 'positive'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The best thing though was when they messed up the fish order they not only gave us each a free glass of wine, but they took that fish order off our bill!!!"], "output": "[['food', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["This place is decent if you want to hang out with friends (who don't mind paying up) in a low-key atmosphere with good food, but don't mind putting up with sub-par level of service."], "output": "[['ambience', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The third time, after, an hour and a half of waiting, my friend went up to the host to check the status."], "output": "[['service', 'negative'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Frustrated, hand the check back to the server and said 'by the way, never got the dessert and he said i did not realize you wanted dessert'"], "output": "[['price', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We started at the bar with a round of mojitos, which were amazing, and went to our reserved table."], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["While the food was good, service tried way too hard."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Though the wait may be long because they only have 16 tables it is worth it, and it seems to go by fast after a drink or two at the bar."], "output": "[['service', 'negative'], ['place', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["we had to wait at the bar for a table, but the atmosphere is bustling and is well worth it."], "output": "[['place', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When the waitress brought the check after an hour, she finally noticed that I had been sitting without food and offered to get it for me."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I'd like to try their brunch - the menu looks good."], "output": "[['food', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Choppy service with a bit of attitude thrown in -when we asked for the restaurant week prix fix menus the aiter made a face."], "output": "[['service', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I KEPT WAITING FOR THE FLAVORS IN THIS RICH LOOKING SAUCE TO TAKE OVER, BUT THEY DID NOT, THE SCALLOP WAS A LITTLE RUBBERY."], "output": "[['ambience', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["And I pretty much had to tell the waiter that when dinner is late, you usually comp your guests something."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When we requested a table our bar tab was quickly transferred and the LOVELY hostess sat us at a table of our choice - we chose the corner."], "output": "[['staff', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Mixed drinks were Casino Quality we weren't sure if the sides on our tables were left from the previous diners, but when our steaks (Only one choice on the menu) arrived."], "output": "[['food', 'negative'], ['miscellaneous', 'neutral'], ['place', 'neutral'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My g/f and I walked in one night, the owner greeted us at the door and took our coats, sat us in the back room (non-smoking at the time)."], "output": "[['staff', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["But what would have been a pleasant experience was spoiled by the attitude and actions of the wait staff and the management."], "output": "[['service', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["All in all, I would not recommend for the food or drinks but I guess I can't expect better for the prices."], "output": "[['food', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They didn't have any salad and the waiter didn't tell us this very smoothly."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Everything that we tasted on the menu was great, particularly the shrimp tapas (if you don't order it yourself, the waiter will surely recommend it)."], "output": "[['menu', 'neutral'], ['food', 'positive'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Not very crowded, the wait staff seemed to be in full force except when you needed their attention for something like water or tea."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Karl the Bar Manager makes yummy special drinks for each season be sure to check out what's on his drink menu when you stop in."], "output": "[['staff', 'neutral'], ['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Although there was a 30 min wait I didn't mind because I was able to sit at the bar and have some drinks while talking to the beautiful, charming hostess there."], "output": "[['place', 'neutral'], ['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["All the food was carefully prepared and the presentation was a cut above."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food was good but it will not make up for the negligent, rude, condescending and hostile service with the full support of their management we received."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Two minutes later, the waitress said we NEED the table, you can not have the appetizer that you ordered."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If you're going with a date to a lounge on that street, stop there for a drink and a quick appetizer first."], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Went with a girlfriend, waited for over an hour while we had drinks, food was ok, service was terrible."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The best thing on the menu was probably the creamed spinach side and that's saying alot for a steakhouse."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My party of 8 had a seafood feast sampling Sammy's menu and we couldn't believe how great the food was."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu is divided up into several sections, and most of the dishes are smallish plates, like tapas."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["From having an appetizer, a glass of wine and reading a magazine to sitting by a table to work on my grades, to meeting other fellow teachers for a book club to partying with the owners all my experiences at Futura have always been extremely postive!"], "output": "[['food', 'neutral'], ['miscellaneous', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene With its yellow slat walls, nautical art and well-worn oak bar, this onetime fishermen's lair is now a snug little neighbor to both South Street Seaport and the glass sequoias of nearby Wall Street."], "output": "[['miscellaneous', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waitress was so helpful with the wine list."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After a 21/2 hour lunch in which our displeasure was apparent, we didn't receive an apology or an explanation from the waiter or manager."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["A hour passed until the waitress came over to give us menus and tell us she would be right back another hour later After trying to order fish she informed us that all fish entrees on the menu was sold out We took a minute to make a second choice and tried to order something else that we were told was also sold out."], "output": "[['staff', 'negative'], ['menu', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["One hour into our dinner, we were told by the hostess that we needed to hurry up and finish so that they could accommodate the next party's reservation."], "output": "[['food', 'neutral'], ['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We got so frustrated with our waitress, who stopped by twice over the course of 2 1/2 hours, that we had to order everything from the bar."], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["true I had to wait longer for my table, but the ambience and the food definitely made up for it."], "output": "[['miscellaneous', 'neutral'], ['ambience', 'positive'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service and surroundings couldn't have been better, but the food was very disapointing at best."], "output": "[['place', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The New Prospect Cafe pretends to be fancy and the prices indicate fancy, but the food is mediocre at best and the service is terrible."], "output": "[['price', 'positive'], ['food', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["While I love this place, I do recommend going here mostly for lunch or an early dinner because the crowd and long wait can be annoying."], "output": "[['food', 'neutral'], ['service', 'negative'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Decent value for decent chinese food for the area - obviously you can get cheaper down in chinatown."], "output": "[['miscellaneous', 'positive'], ['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter seemed truly disinterested (he forgot to bring the bread basket and the wine was served after he delivered the entrees."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["On your way out, pick up a bar of their Swiss chocolate."], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["During the day, the sushi bar can be backed up a bit (thanks to their unbeatable lunch specials) so order early."], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They have Boylan's root beer, coffee that's freshly ground that day, and a relaxed casual atmosphere with friendly waitresses."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive'], ['ambience', 'positive'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["some old drunk guy who claims he is an American born in France seems to be a regular at the bar, he sat down next to us, listened to our whole conversation then started aggressing us verbally, and the waiter took the longest time to intervene."], "output": "[['place', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The portions are now very small, the sauces are overly-ambitious usually inedible while the service is still good, the restaurant, due to its popularity, seems frantic."], "output": "[['miscellaneous', 'negative'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Bernard is a great host; it didn't bother me a bit that he recited the entire menu to my wife."], "output": "[['staff', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu could be a little bigger but my food as well as my boyfriend's was outstanding (and a lot less expensive than I expected)."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The fresh sliced mozzerella, the sweet roasted peppers, the hint of garlic and oil, are just some of the ingredients that produce the light otherworldly tasty pizza at Grimaldi's."], "output": "[['ambience', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I was told they had one(early) reservation; felt deceived b/c when I left the place was empty!"], "output": "[['miscellaneous', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["A collection of stormy sea paintings and two mermaid figureheads hoisting lights above the bar set a lulled maritime mood."], "output": "[['miscellaneous', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I was shocked by the amount of butter used in the pork and lamb dishes -- the smell of butter was literally wafting off the plate!"], "output": "[['food', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["About the wait - be prepared to - it isn't just anyplace offering top notch cuisine for about $25 all in."], "output": "[['service', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Great food, but tiny portions and inexcusable service - disorganized, amateurish and definitely overpriced by a long shot."], "output": "[['food', 'positive'], ['miscellaneous', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["while I think the menu could use better appetizers all of the main courses are DELICIOUS- also the service is so much better than the ratings."], "output": "[['menu', 'neutral'], ['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Minutes turned into an hour-long wait with non-existent standing room."], "output": "[['service', 'neutral'], ['miscellaneous', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waitress hardly spoken English - and not because she spoke French - and she spilled wine all over me and didn't try to make any amends."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Decor is sort of homey, with mismatched tables and plates."], "output": "[['ambience', 'positive'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["But wait, it gets even better, the mussels were so fishy that I had the server try one since he had a hard time believing that this was true."], "output": "[['service', 'neutral'], ['food', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu: HOT DOGS, that's it, nothing else."], "output": "[['menu', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The staff was gracious enough to keep her arrival a secret by letting us wait at the bar and holding our table for us until she and our father arrived 45 minutes late (delayed flight)."], "output": "[['staff', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The fish of the day can be prepared five different ways according to the menu, but fails to mention that those five different ways are just five different sauces that come out with the whole, deep fried fish."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Well, its bar is beginning to attract the high-heeled Forever 21 ladies and hair-gelled men-who-love-them crowd (alas) and yet I must admit-- the food is damn good."], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Seated just after 2; I commend them 'cause they were the only decent brunch spot that would take our reservation, and they did their best to seat us promptly."], "output": "[['place', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After being seated the waiter was prompt with coffee and taking my order."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Once the manager loudly referred to the customers patiently waiting at the all-you-can-eat buffet line as 'hungry animals attacking for food'"], "output": "[['staff', 'negative'], ['service', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Okay, so the bathroom is a little scary and the milieu brings to mind an old diner or cafeteria, but simply put, the food here is the best."], "output": "[['place', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Overall, the quality of the food won us over, but if there's one thing the management needs to work on, it's service."], "output": "[['staff', 'negative'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It was a crowded Wednesday night but we were seated near the kitchen right away, talked to all of the staff who were friendly and made the evening special for my date and I."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Now admittedly I went at lunch, when presumably the kitchen and waitstaff are less taxed than at dinner, but everything was fine."], "output": "[['place', 'neutral'], ['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My wife and I, from Houston, and another couple from Conneticut were visiting Manhattan for the weekend and I chose Shula's for dinner because I had heard that it was a good steak house."], "output": "[['food', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food is delish, you just have to know the manners to consume, if you don't want to be frustrated with the service."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["ten minutes after we ordered the waitress came to our table and told us we had ordered complicated entrees and we would be waiting for 45 minutes."], "output": "[['miscellaneous', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["For example, the flavor in each dish didn't really stand out and the spanish rice seemed more like uncle ben's with peas and corn mixed in."], "output": "[['ambience', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were never offered dessert because our waiter spent about 20 minutes at the bar calculating the checks instead."], "output": "[['food', 'neutral'], ['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["During dinner, we sat drinkless once again, as the server and owner never checked on us."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We preferred to gaze at our burgers while avoiding having to look at the wait staff, but no complaints."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If you're dining solo, you will feel completely at ease in the cozy environs; in fact, you're likely to see at least one other solo diner hunched over a book, sipping a glass of Chianti."], "output": "[['food', 'neutral'], ['ambience', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After I inquired why the food was taking so long, the waitress told us that the 2 dishes we ordered take a long time."], "output": "[['food', 'neutral'], ['staff', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Perfect place to bring a date before the theater, a mother/ grandmother/ or aunt for their birthday, or friend for lunch."], "output": "[['place', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food The French-Belgian menu is small, but everything on it is satisfyingly savory, from a simple pot of mussels in a choice of sauces (beer and bacon, creamy mushroom, or white wine and garlic broth), to beef stewed with beer and prunes; from a juicy croque monsieur and beyond."], "output": "[['food', 'negative'], ['menu', 'negative'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Waitress forgot drinks, and watched us begin our dinner without even water, strange."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Friendly service, and outdoor seating in the warm months, eases the crush."], "output": "[['service', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food At dinner, a nicely gamey chopped liver mousse, watercress salad with blue cheese and walnuts, and meat loaf with mashed potatoes stand out among the menu's bistro fare."], "output": "[['food', 'positive'], ['menu', 'neutral'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food An a la carte menu offers specialties like Kobe beef cooked on a hot rock, but the Kaiseki, a traditional multicourse tasting dinner served on gorgeous pottery and porcelain, promises dining adventure."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If the waitress had been remotely available or had come by to enquire about our food, I certainly would have sent it back, but since I was being taken out for a birthday dinner I did not want to make a fuss."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It's a place for the owner staff's friends, so if you're not one of them, you're in for a wait."], "output": "[['staff', 'negative'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The loud belly dancer with her scarf dragging across my food and table, almost knocked over my water glass."], "output": "[['food', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I'll second the recommedation for the Purity--which has much faster, better service at half the price and a whole lot more selection."], "output": "[['miscellaneous', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["No table space and one of the angry neighbors decided to take matters into his own hands by throwing a bucket of water out his window and onto the patrons waiting for their tables."], "output": "[['place', 'negative'], ['food', 'neutral'], ['service', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I requested a Riesling and the waiter recommended staying with the Sencere which didn't come by the glass according to the menu but he provided it to us any ways."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The jukebox is always playing good tunes, and the patrons are never shy about getting up and dancing in the aisles, or even on the bar."], "output": "[['miscellaneous', 'positive'], ['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["bartenders management and at first were a bit disappointed with food."], "output": "[['staff', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitress was unbelievably rude to my friend and myself when she realized that we were ordering appetizers as our entrees."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They have even just expanded to include lunch hours at very reasonable prices."], "output": "[['food', 'neutral'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The place was jumping on a Mon nite, as was the bar, but with a nice mixed crowd."], "output": "[['place', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["At one point my friend knocked over a glass and broke it to pieces, and the waitstaff was so forgiving of it."], "output": "[['miscellaneous', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["A sushi chef creating entrees of art that will have you talking as much as eating."], "output": "[['staff', 'positive'], ['food', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Intrigued by the ambience of the restaurant, some friends and I decided to have dinner at Paladar on Saturday night."], "output": "[['ambience', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Mango ice cream or coffee-flavored gelatin finishes the flavorful journey."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Service is coddling and correct and there's no sense of hurry, so diners linger over a cheese course or a round of liqueurs."], "output": "[['service', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When there are ten open tables in a room, the hostess insisted on seating peopl on top of each other."], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Never will you taste sicilian Pizza and Spumoni like LBs."], "output": "[['food', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The bartendars are very friendly and at service with you."], "output": "[['staff', 'positive'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Patrons are a mix of pre-theater and local regulars whose relaxed laughter and gesturing conversations add much to the restaurant's flavor."], "output": "[['food', 'neutral'], ['place', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["You might be lucky enough to hear your waiter say, May I take zee order from you, Pig Dog, while you're there."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["One waiter came by and literally threw the $36 salad on the table."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Asking for the menu is out of line and unusual where the staff is actually insulted if you choose not to rely on their expertise on average Chinese food selections."], "output": "[['menu', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["In a room decorated with beautiful Ottoman antiques and artwork you can pick exceptional mezzes (appetizers) from a selection presented by a super-friendly staff or order lip-smacking dishes (especially if you like lamb) from the menu."], "output": "[['staff', 'positive'], ['food', 'neutral'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Decent eggs (just about everything on the menu is coated in this amazing hollandaise)."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Food was good, but for the price of a plate of pasta here, four raviolis doesn't cut it as an entre for a big guy."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our dinner special included dessert, but our slow and unhelpful waitress didn't bother asking if we wanted any."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Walked in on Chinese New Year Sunday late in the afternoon, around 5 or 6 -- seating was not a problem the dim sum was deliciously fresh -- very likely a by-product of their not using carts."], "output": "[['place', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the waiter was extremely helpful, basically we gave him carte blanche to order small plates for us that he thought we'd like."], "output": "[['food', 'neutral'], ['miscellaneous', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Some of the waiters are lacking good communication skills, but that can be overlooked in light of the great food and prices."], "output": "[['staff', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["This is the only place that has great cheesecake in the Tri State area and they are famous for it."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene The windowed bar and front waiting area seems bright and airy compared to the somewhat stuffy main room."], "output": "[['miscellaneous', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The line moves quickly, perhaps because there are no alcoholic drinks, which cuts lingering at the tables to a minimum."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The other food they serve is also very good, but the pizza keeps calling me back!"], "output": "[['food', 'positive'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service was great -- my glass was refilled without having to ask, we were greeted by the manager that day to ask how our food was."], "output": "[['service', 'positive'], ['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["While the staff was kind and attentive, our waiter never once broke a smile, even when I told him it was my friend's birthday, although he did bring a dessert with a candle at the end of the meal."], "output": "[['staff', 'positive'], ['food', 'neutral'], ['ambience', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We would rather pay more prices and expect the better food and service."], "output": "[['price', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I agree that the wait staff wasn't very friendly, but the service was adequate and our food arrived without too much of a wait."], "output": "[['staff', 'negative'], ['service', 'positive'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Service was good, except for a very long gap between appetizers (which came out too quickly) and entree (whick took another 45 minutes to arrive)."], "output": "[['service', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I really like the decor and it made it feel like I was having drinks at a mansion."], "output": "[['ambience', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["No matter what, you should expect a wait, big deal, small price to pay for great food as far as I'm concerned."], "output": "[['service', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After being seated at an outdoor table on a 45 degree tilt, the surly waitress gave us menus."], "output": "[['service', 'neutral'], ['place', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service was only average - even with reservations we waited 40 minutes, and had to ask for our table, which had been ready, the hostess just never bothered to tell us."], "output": "[['service', 'negative'], ['miscellaneous', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["our waitress couldn't explain or describe the specials to us, and a group of five people seemed to overwhelm her."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I've sampled several other dim sum places here, and none feature the winning combination that Triple 8 offers: reasonable prices, large range of standard _and_ less common dim sum, little/no wait (not like the Mott St."], "output": "[['food', 'neutral'], ['price', 'positive'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The spacious bar, with its own menu of small plates and a lengthy list of wines by the glass, is a boon to single diners."], "output": "[['menu', 'neutral'], ['miscellaneous', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere is certainly unlike any other restaurant in all of Manhattan, but it is a pity that the food does not live up to the decor."], "output": "[['ambience', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The music is a mix of house radio as well as live band at the same time."], "output": "[['ambience', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The choices for vegetarians are extremely limited, unless one is content with side dishes."], "output": "[['miscellaneous', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Comfort is decidedly not a factor in the Arturo's experience--once patrons escape the bottleneck near the bar, they're shoehorned into a miniscule dining room."], "output": "[['ambience', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["For a normal dinner, I prefer a place that has a bit more room and that has a slightly more relaxed vibe."], "output": "[['food', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The meal was improperly served."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The ambience is horrible but the food is incredible."], "output": "[['ambience', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["People at the next table were complaining how horrible their house wine was."], "output": "[['miscellaneous', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The hostess was snooty since we did not have a reservation but the rest of the dining experience amply made up for it."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Reserve a cozy window seat for more privacy, or hop onto a stool at the bar to dine solo."], "output": "[['miscellaneous', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It wasn't until we spoke with management that we were able to finish our meal and get out of the restaurant, but already one of our party had to leave early and the rest of us were late for our afternoon engagements."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitress let us taste three wines before deciding (we were only ordering glasses) and then we chose to eat at the bar (same menu) since it was so comfortable."], "output": "[['staff', 'positive'], ['place', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["She asked for only a glass of water, and the waitress refused, to her face, twice."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Nostalgic lodgey bric-a-brac adorns the livelier front dining room and bar, while the dim, non-smoking back room is decorated with stained glass and modern, Mission-style chairs."], "output": "[['place', 'neutral'], ['ambience', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["To be fair, my husband's cheeseburger was quite good, but the waitress never apologized for the long wait or attempted to explain."], "output": "[['food', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["though the portions were smaller than average, the flavor and sauces that accompany them (truffle honey, cherries and peaches in mustard sauce) were all really good."], "output": "[['miscellaneous', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The matre de ignored what I said about my girlfriend having to look for a waiter to refill her glass (twice), I mentioned about my rice, he said, You should have spoken up."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I went with my sister and neither of us had wine so the final bill was a bit shocking."], "output": "[['food', 'neutral'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Needless to say I will rather go spend $400 on dinner somewhere else wirh better service."], "output": "[['food', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["i do agree with the comment about their waitstaff, they tend to make you feel like you have to rush through your meal."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The portions are not HUGE, but you are very full by the end of your meal."], "output": "[['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["While waiting we asked the bartender for at glass of red wine which he not only forgot to serve but when we asked him again 10min later he poured us white wine."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I didn't know what to expect from Frankie and Johnnie's when I made the reservation after my friend told me it was the best steak he had had."], "output": "[['miscellaneous', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The clean, sunny interior looks nothing like Jerry and the gang's dingy haunt, but it showcases fun ephemera like Seinfeld cast autographs and press clips on how the diner inspired the musical ode by Suzanne Vega."], "output": "[['place', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Did not get to dessert as it took a while to get the server's attention and we had a show to get to."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere was nice in the front room, but despite a reservation, we were relegated to the rear, where we were treated like stepchildren - we had to flag someone down to take our order, water with no ice, we had to ask for extras (as opposed to someone asking if we needed something else)."], "output": "[['ambience', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We ordered off the restaurant week menu, which at other establishments means automatic second-rate service, but not here."], "output": "[['menu', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["While the food was good enough (if old-fashioned - my meal tasted like it was out of a fancy 1950s cookbook, all creamy and rich) the environment was sort of bizarre - rich tapestries, yucky corner-grocer roses on the tables, and a strange '80s mirrored wall, which we sat against at the back of the restaurant."], "output": "[['food', 'positive'], ['ambience', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["it took forever for the waiter to take my order as he was too busy chatting at the bar."], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Waitress we had appered to be very impatient, didn't know the name of the fish in English, apptizer came when we were having entree and she made no apology."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The hostess did not verify/review the menu prices with us nor did they inform us of the logistics of the brunch."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I waited 10 minutes to get change for a drink I ordered at the bar, my friend had one of her drinks dumped all over the floor by the same waitress above who took too long to get me my change, and it took forever for that much to happen."], "output": "[['place', 'neutral'], ['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu sounded good but the grilled eggplant roll was oversauced with a pile of mint, pork chop was leathery, and everything just tasted wrong."], "output": "[['menu', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter could not have been more patient with us as we (okay, my wife) made her decision on appetizers."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We saw the waitress twice - once to tell us the night's specials and once to take our order."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["i think that the second floor is better if you prefer a quieter environment for dinner."], "output": "[['ambience', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Ate at the bar and started with an amazing bowl of french onion soup with 3 cheeses (3!)"], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Sometimes service was a bit slow, and we had to ask for salads, water, etc a couple of times, but this was all done with good humor and no resentment."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["But, quickly all would realize that most items on the menu are grease-laden, and the portions are so big that you'd get tired of the flavors before you finish half a plate."], "output": "[['menu', 'neutral'], ['miscellaneous', 'positive'], ['ambience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The view is the reason to go to this restaurant, not the food nor the service."], "output": "[['miscellaneous', 'positive'], ['food', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My only gripe was that the food was all in big bins, but that's expected for a lunch rush hour type crowd."], "output": "[['food', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["one waiter couldn't remember what we had to drink and we were the only people in the place."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Great wine list with an extra expensive selection for all you big spenders."], "output": "[['food', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After dinner and even a few times during the owner came upto us and asked us how we felt about the place and the food which doesn't happen often in Manhattan."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I expected there to be more options for tapas the food was mediocre but the service was pretty good."], "output": "[['food', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Only con was the cost -- our dinner for two was $400!"], "output": "[['price', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["On top of that, the portions were hearty enough that we barely had any appetite left for dessert."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Kids love the tabletop crayons and coloring books, but the real crowd-pleaser is raw pizza dough--lumps are available at the open kitchen window."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["To both our surprise, this inquiry was interpreted as a personal offense by the waiter who told my wife to leave the store if she didnt want the pastries."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Po has the best food in NY, if you don't mind a wait."], "output": "[['food', 'positive'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The prices are up there without being over the top but the quality of the food commands it."], "output": "[['price', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were a party of six and I had tried almost everything that was on the table, and had I been rich I would have hired the chef to cook only for me!"], "output": "[['miscellaneous', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene With flickering sconces and rough-hewn brick walls, Crispo may look like an elegantly restored Italian farmhouse, but frenzied servers, tight tables and wait-list hopefuls at the marble bar make it feel like a city-slick hotspot."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Their new style of all you can eat is: They bring barely enough food for the table, mostly just bread ,until you ask a waiter to bring some more."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["some sweaty so frazzled, when we returned both an app and entree, the manager didn't even come to speak to us."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitress was friendly but did not know the menu and had to run to the kitchen after each question."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When we asked the waiter for water - he gave us dirty looks and it took at least 15 minutes to get it."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["also you dont mind waiting because theres such a buzz around the bar it makes you feel like you are out for drinks."], "output": "[['service', 'positive'], ['place', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["On each table there's a variety of sauces and spices, which you're encouraged to add to your dish; by the end of the meal you mind up with something completely different in your bowl from you started, but it will still be so satisfying."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The chef/owner is always walking around making sure everyone is having a good time."], "output": "[['staff', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Once the waitress cursed our table for not tipping enough after we had waited an hour to order and another half an hour just to get a drink, on top of this I had to find my own cutlery."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I had to physically get out of my seat and find the waitress twice just to ask for more water."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food The free chips-and-salsa may suggest casual Tex-Mex cooking, but this menu is a couple notches above."], "output": "[['food', 'neutral'], ['menu', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After a couple of drinks upstairs before our meal, we slipped downstairs to a nice corner table that offered plenty of privacy in this 'loud' place."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Chances are the garden out back is hopping, with happy Slopers sipping wines that start less than $20 per bottle and munching on more than a dozen kinds of pressed sandwiches."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the waitress was slow and forgot our drinks about 3 times."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The other side of the menu offers chicken, veal, and seafood standards, including perfect saltimbocca and a huge, succulent veal chop."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My steak looked worse than the grizzle and fat John Candy had to finish in the Great Outdoors and the service, while friendly, was incredibly slow even though we were one of only 4 other tables."], "output": "[['food', 'negative'], ['place', 'positive'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Of course we went there with a large party and had to wait a bit to get seated (even with reservations), but we had all our dishes served at the same time and promptly."], "output": "[['miscellaneous', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Denny's serves a better Grand Slam breakfast--and at a quarter of the price (I paid $21 w/o tip for b-fast--I went back a second time, because the restaurant was highly touted and I thought the first bad experience was a fluke."], "output": "[['food', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Jackson Diner was my first intro to true Indian food and its been 10yrs since and I cannot go one month without some of this unbelievable food."], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Only reason to go is Eben, the most solicitious bartender in NYC (now) with drink knowledge and ability to spare."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The problem was that we waited for a long time to get our waitress, we had to ask the bus boy for refills for drinks, and we waited for a long time to pay for our check."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitress took about 20 minutes to bring us the menu."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["You cannot beat having the waiter spooning butter over your steak before you are served!!"], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The bar's waitresses seem to have a sixth sense for when customers have reached the bottom of a drink or are scratching their forks against empty plates."], "output": "[['place', 'neutral'], ['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["they didn't have to change anything about the menu except add a leg of chicken seperatley and the guy mumbled very rudely that I had already ordered and I should've decided earlier."], "output": "[['menu', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The staff were friendly, but the food just wasn't that great."], "output": "[['staff', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["There are no vegetarian items on the menu, but when I requested that the chef make something meat-free for me, he came through with a dish just as delicious and pretty as those my friends were eating."], "output": "[['menu', 'neutral'], ['staff', 'positive'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["To be honest, it cost $95 for two adults and a kid (including only two beers for the adults), and the only things worth eating were the raw oysters, information about which the staff was not too sure."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our oh-so-chic waitress obstained from half the items on the menu (give me a break) so she couldn't make subjective recommendations."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The place is small, the host was friendly and communicative -- we had to wait 45 minutes for a table but they don't take reservations and clearly it's a popular spot."], "output": "[['place', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Upon his arrival the staff checked in his bags and put them in the storage room, but when my bf asked for a check-in ticket, the host refused to give one and threw the bags back at us."], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Little Italy-style hambone performances by the waiters (actually saying fugettaboutit 4 times during specials) was embarassing and did nothing to hide the fact of of being charged for 4 bottles of wine when we only ordered 3."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The best dish is not listed on their menu - it is a special - the flat pasta with truffle mushroom sauce."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter recommended I choose a bottle for the entire meal."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["when our server accidentally spilled some wine at our table, he cleaned it up offered us another glass right away."], "output": "[['staff', 'positive'], ['food', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter was knowledgable about the menu and spirits, and guided me to all the right items to order given my budget and occasion."], "output": "[['staff', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The small shrimp were dry and rubbery and when I sent the dish back to the kitchen, the waitress returned saying that they use 'frozen shrimp so that is wny they have that texture."], "output": "[['food', 'negative'], ['place', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After the waiter finally took our order and gave us our food he never came back."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Even though we complained several times, they brought us the bill before dessert and the manager came to our table to mention he was closing the place for the night."], "output": "[['price', 'neutral'], ['food', 'neutral'], ['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["While getting a reservation upstairs can be a pain, stopping by on Saturday night for a dinner by the window is a fun way to experience Babbo without the long term planning."], "output": "[['miscellaneous', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We went at 1 am, we got food, fast service and Excellent drinks."], "output": "[['food', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I have been going to this restaurant for years, in the past the service was average and the food inconsistant."], "output": "[['service', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Service has improved drastically from the old days, you are now seated by a hostess instead of standing behind a nearby table waiting for them to finish."], "output": "[['service', 'positive'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Paying that high price, I could have dined at other places with better food and service."], "output": "[['price', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Upon explaining, the waiter confronted us as we left and spewed a stream of profanities at us as we walked out the door."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Everything from the salmon dip at the bar (while waiting for our table) to the dessert was perfect."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The dinner lasted about 3 hours, that waiter continued to refill our water even though we finished the whole meal(including desserts) an hour and half before."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Setting aside the interminable wait for food, the cheese omelet opened up on the way from the kitchen to the table so that when it arrived, it looked like a large yellow pancake with a slab of uncooked cheese sitting in the middle."], "output": "[['service', 'negative'], ['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the filet came out and was absolutely delicious, on a bed of julienned vegetables in a balsamic vinagarette sauce."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The owner and staff are all Japanese as well and that adds to the entire ambiance."], "output": "[['staff', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["There was live music at the bar, which made our wait for a table wonderful (we didn't have reservations)."], "output": "[['ambience', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were not offered the dessert menu and that waiter was so rude!~ I was very offended after a good meal."], "output": "[['menu', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I'm sorry, but the prices at Boi are outrageous for this type of cuisine."], "output": "[['price', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After the appetizers, which were the only saving grace (BBQ chips, spinach, fried bread), the servers descending and without asking started taking our plates away."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["There isn't a huge selection of food, but there's something on the menu for everyone to really enjoy."], "output": "[['food', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitress gave us attitude because we orderred the price fix and not the regular menu."], "output": "[['staff', 'negative'], ['price', 'neutral'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter made a huge production over what order he should deliver the food, as we all agreed the miso should be eaten with the sushi to aid digestion."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Would go back when I was ordering off the regular menu and give the steak a try."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Once we'd finished eating, it was another 15 minutes before we saw someone who would bring us the check - and after running my credit card, the waitress had the audacity to write cash only in the tip portion of the receipt!"], "output": "[['price', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene You'll have to knock to enter this hidden dining room, a luxe windowless space featuring four wall-sized murals depicting famous landmarks throughout the seasons, as well as a handful of finery-laden tables."], "output": "[['miscellaneous', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If you consider throwing food at your when they remember good service, then go for it."], "output": "[['food', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["While they adhere to a certain traditionality in serving their teas; eg: samovar for the russian, chinese tea sets for the green, the food labours under no such restrictions and there is nothing ordinary on the menu."], "output": "[['service', 'neutral'], ['food', 'neutral'], ['menu', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The worst service I have ever had - entered the restaurant and waited at the door for 5 minutes before deciding to push our way past the extremely small bar to find a waitress."], "output": "[['service', 'negative'], ['place', 'negative'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Hostess finally brought it, saying if we wanted dessert, we could move to another table."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The owner promised my party a table and bottle service and took care of it immediately as we all arrived."], "output": "[['staff', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Ignoring the merits of the cuisine (which was par at best), I see no reason why one would pay Da Umberto prices for an okay meal and below average ambience."], "output": "[['price', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Though there are a handful of Japanese a la carte offerings on the menu, the prix fixe is most popular by far."], "output": "[['menu', 'neutral'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Get there before 7:30 for dinner or get ready for a really long wait - this place doesn't take reservations."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter was very prompt and friendly, but the worst part of the experience was actually after the meal when I was leaving."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food was definitely good, but when all was said and done, I just couldn't justify it for the price (including 2 drinks, $100/person)."], "output": "[['price', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Went for restaurant week and surprisingly on the menu were entree options of Mahi, Mahi, Kobe Beef ribs, Salmon and some other things in very reasonable portions."], "output": "[['menu', 'neutral'], ['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter didn't go over the menu choices and at the end of the night we were so fed up we didn't even order dessert."], "output": "[['staff', 'negative'], ['menu', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["This place is good but food and service is presented for the masses, not much personalized service considering the price tag and that it is a full-evening-out type of dinner place."], "output": "[['food', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu reads well, and it sounds like the chef knows whats up."], "output": "[['menu', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the tasty food keeps luring me back, but after placing an order with who i assume must be the same rude sunday manager i keep hearing about, i'm not sure i will again."], "output": "[['food', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Portions were certainly substantial for lunch."], "output": "[['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiters do not pay any attention to the customers, instead sit at the bar and watch TV."], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Not 5 minutes passed before the server actually tapped us on the shoulder and, I swear to god, ASKED US TO LEAVE because they had a reservation."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When we asked a waiter for an explanation of the long wait with some many empty tables he had no answer so we asked for the manager."], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["You can spend $25 per entree at a much fancier place."], "output": "[['food', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Space gets kind of crowded in there--because it's so popular--but it's worth the wait because the food is very good."], "output": "[['place', 'negative'], ['service', 'positive'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["A few years ago I would have rated it much higher, but now - with other better choices such as Candle Cafe, Good Health Cafe and others, the dated menu, crowded atmosphere are spacey service is not the greatest choice."], "output": "[['menu', 'neutral'], ['ambience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Grabbed a lunch here on a weekday and it was reasonably priced, well-portioned and generally well-prepared."], "output": "[['food', 'neutral'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Setting The exposed brick and tangerine walls, flickering candles and tiny bar cast a formal mood across this cozy Park Slope trattoria, but the high ceiling fans and two glass walls (left open in warm weather) add a casual breeziness."], "output": "[['ambience', 'neutral'], ['food', 'neutral'], ['place', 'positive'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["great food, even better price, they also have a dj spinning great music, definitely a must try."], "output": "[['food', 'positive'], ['price', 'positive'], ['staff', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiters didn't clean it up until they brought our dessert."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The wait staff is friendly and helpful and kudos to the sushi chef Hero who serves up great dishes on and off the menu and is always wearing a smile."], "output": "[['staff', 'positive'], ['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the most expensive dish on the menu was $14!!!"], "output": "[['food', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["A very pretty setting to have a meal, but unfortunately the service and food don't match the atmosphere."], "output": "[['service', 'negative'], ['food', 'negative'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Although almost the entire back room had tables available, the owner made people wait to be seated while dragging waitresses around by the arm and loudly telling them they were doing things wrong."], "output": "[['place', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I visited the Park Slope location on Fifth Avenue, and was impressed with the menu, and that they offered chicken fried steak."], "output": "[['menu', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["i had a horrible experience with a waiter while trying to have breakfast friday morning."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["that the waiting is horrific but the food is great."], "output": "[['service', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["He hooted and hollered -- and told every staff person at the bar, not to serve us."], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["To finish, the cost of the dinner was over-priced."], "output": "[['price', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The caesar salad was a huge bowl of iceberg lettuce, a dressing that wasn't ceasar, 1 crouton and a few slices of thin chicken -- for $12."], "output": "[['food', 'positive'], ['ambience', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If you go for lunch as we did, get there when they open as seating is fairly limited."], "output": "[['food', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service isn't spectacular and neither is the ambience, but on a lunch hour, all you're looking for is a satisfied stomach."], "output": "[['service', 'negative'], ['ambience', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The problem is that if you want anything to continue the meal, if you need an extra minute to go over the menu, or if, horrors, you want the check, you might be in for a lengthy wait."], "output": "[['menu', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["She also has to beg for water refills squeeze her smallish rear-end between crowded tables."], "output": "[['food', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If you are expecting big portions, go find a Cheesecake Factory."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Pastas include shellfish-stocked linguine with tomato sauce, and an excellent homemade cheese ravioli--all are available in half portions."], "output": "[['food', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Good location, but tourist-y and poor quality food."], "output": "[['place', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu does not have much and what we did have - original pizza with pepperoni and sausage was not so great."], "output": "[['menu', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Their menu has just been updated featuring new rolls and more choices."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["A popular diner in the Metro Tch Brooklyn area catering to local brooklyn ites or the wall street financial back office employees of Metrotech."], "output": "[['place', 'positive'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Although the pricing is on the more expensive side, this is a must try restaurant for its food."], "output": "[['price', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["although the food was well-prepared, it was not worth the price, especially when it does not include dessert!"], "output": "[['food', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Watch out for the sesame noodles, though, and leave the complimentary pickled cabbage and carrots sitting on the table for the next customer to enjoy."], "output": "[['food', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menus took about 15 minutes to come, the menu were already set up for Valentines day the salad was good my dinner was a soup of about 2 or three shrimps, THAT'S IT!"], "output": "[['menu', 'neutral'], ['miscellaneous', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Menu had several fish selections (snapper, salmon, cod) but all were around $30 despite the fact that the portions would hardly fill a child's belly and the sides were 3 pieces of lettuce (literally)."], "output": "[['menu', 'neutral'], ['food', 'negative'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service can be a bit spotty since they are sometimes busy taking phone orders to attend to the restaurant patrons so make sure you have a lot of time to spare when you go there for dinner."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I find the attitude of the managers to be appallingly superior, and the food below average, at sky-high prices."], "output": "[['service', 'positive'], ['staff', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["mistake on the check, overly salty morels stuffed with foie gras) but overall, Daniel's dishes are revelations in taste."], "output": "[['price', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Particularly good is the chicken verde burrito with a refreshingly spicy salsa that avoids the heat overkill."], "output": "[['food', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food was pretty good but the portions were smaller than what I would expect for brunch."], "output": "[['food', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["While there's a strong Asian influence behind many of the plates, you can't pigeonhole the food into a single genre, as there are Thai, Chinese, Japanese, Italian and American dishes incorporated into this creative menu."], "output": "[['miscellaneous', 'neutral'], ['food', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The mussels and fries at this place were amazing!"], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I politely told our waitress about this and she was not only apologetic, but the manager came over a minute later and apologized and bought myself and my guest another round of drinks."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The hostess SLOWLY walked by our table scribbing something on paper."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Everything that could go wrong did starting with the set menu that I was not informed of at the time of the reservation, to trying to seat us 45 minutes late at a table that was not made up."], "output": "[['menu', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Great decor, expensive drinks but worth the price, but the music is bland and the crowd is very cheezy."], "output": "[['ambience', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Delivery wasn't the fastest, but the food was still hot so I won't complain."], "output": "[['service', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Bins of fresh bagels rest behind the counter, and there are always a few customers sitting at one of the few tables inside or on one of two wooden benches out front."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Ten minutes later: no burgers and no sign of our waiter."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter never once came by the table to ask us how our meal was."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["There is a bar right by the door, which is convenient while waiting in the long lines for a seat and be prepared to wait on the weekends."], "output": "[['place', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Upon entering we were promptly seated and ordered a few minutes after ordering the waiter came out and said they are completely out of crab, crab legs, crab claws everything."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["While the food is terrific, you must overlook the often apathetic service, and the sometimes downright rude Manager that seats people."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["As the waitress cleaned the table in a rush she knocked over a party bag containing a glass bottle with bath oil."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I went there for a late dinner last night with a friend and the service was aweful."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["For the price and quality of the food, the service should have been a lot better than it was."], "output": "[['price', 'neutral'], ['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Great place to get a good fulfilling meal but do not go for ambience or service."], "output": "[['food', 'positive'], ['ambience', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It's always exciting to see celebrities hiding in the corner banquettes or behind sunglasses at the bar, but the real draw is the chef's short ribs and the volumous wine list."], "output": "[['place', 'neutral'], ['staff', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Those waiting inside to get a free table and waitresses carlessly walking by only served to make matters worse."], "output": "[['service', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["So maybe I'm naive to the latest trends in dining, but I really didn't like it."], "output": "[['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["), we were not given bread though the couple next to us was, we asked twice for our check and when it came, they forced us to pay the tip in cash so they could get out of paying taxes!"], "output": "[['food', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The servers were prompt and attentive, but the food arrived lukewarm (maybe it was served so quickly because it was pre-cooked and had been sitting out for a while) and was not all that flavorful."], "output": "[['food', 'negative'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene The space, fit with imported giant urinals, zinc-topped bar, large antique mirrors, mosaic floor tiles and mahogany trim, looks like it's been around forever."], "output": "[['miscellaneous', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We then waited until 7:35 before any food arrived at our table, despite the fact that we kept reminding our waitress that we needed to leave by 7:45."], "output": "[['food', 'neutral'], ['miscellaneous', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When the pizza arrived it was definitely hot, however the topping was rather soggy from the moisture from the fresh tomatoes."], "output": "[['food', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service is almost stifling polite (they pushed in my chair behind me every time I returned from the bathroom), though the sushi chef preparing my food was casual and chatty."], "output": "[['miscellaneous', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I expected professionals, but was instead met with an amateur waitstaff that made several ominous errors during the course of the meal."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the hostess really underestimated the wait time for outdoor seating and never apologized, and our waitress was apathetic and unattentive."], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Service was inexcusably, excruciatingly slow- it took more than 30 min to get the first round of drinks, by which point our party was ready to walk out."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We got there early so there wasn't much of a wait -- otherwise, I usually sit at the bar and have a cocktail."], "output": "[['service', 'positive'], ['place', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The owner kindly gave us appetizers on the house to make our now, long wait, more pleasant, but of course they took forever to arrive and were insufficient."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The green hair table and seating at the front window was tacky and gimmicky, but figured it's the food that counts."], "output": "[['miscellaneous', 'negative'], ['place', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Myself along with every other patron were forced to wait in an overcrowded bar while employees carry chairs and such over our heads to prepare for dinner in the next room, shoulder to shoulder we stood there like cattle waiting to be fed."], "output": "[['place', 'negative'], ['staff', 'neutral'], ['miscellaneous', 'neutral'], ['food', 'neutral'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Tried again for Brunch and really bad server with HUGE attitude."], "output": "[['food', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Went for lunch but wanted to order a la carte, which was so highly discouraged by the waiter (pushing the 10."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food The pan-Italian menu forgoes the appetizer-entree format in favor of fairly priced small plates, which quickly add up."], "output": "[['food', 'neutral'], ['menu', 'neutral'], ['price', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter made no effort to remember who had orderd what (just threw it on the table and bailed), or even who ordered (I had to flag him so my wife could order her main dish 15 min after he had taken orders from others)."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["went there for dinner over the weekend and was treated rudely right away by what I think was a manager who was doing anything but managing."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I was interrupted by the waiter to say that when we are done with dinner he'd bring one."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food makes up for it, though the quality has fallen victim to it's success."], "output": "[['food', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Get a bottle of wine, and eat what your heart has been desiring because all the things you would love to be on one menu--are!"], "output": "[['food', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food was barely decent and our server was nowhere to be found."], "output": "[['food', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I always trek to Bar 89 and get one of their huge sandwiches that comes with fries."], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food The seafood-dominant fusion menu features standout starters, like super-fresh raw bar oysters, crispy citrus-pepperoncini calamari and flaky lobster-mushroom tart with fiery chorizo and caramelized onions."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food and decor is above average, but it is clear the restaurant has bad management and service."], "output": "[['food', 'positive'], ['ambience', 'positive'], ['staff', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The first time around, we had the $80 tasting menu, which included some sushi items, which I found to be pretty average, especially for the price."], "output": "[['menu', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Japanese folk music blaring on the quaint speakers are a trip and they have some interesting things on the menu like bull pen|s and turkey testicles."], "output": "[['ambience', 'neutral'], ['miscellaneous', 'positive'], ['menu', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The wait for a table is interminable."], "output": "[['service', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["but we waiting two hours to get it (we had reservations but it was late so we wanted to try to come in earlier)."], "output": "[['service', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the waitress was probably new, because she had no idea what wine they had, or if they had a certain type by the glass or bottle, and kept going back to the bar to find out."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When you go, you should ask for help from the wait staff in deciding what to order since the menu can be daunting."], "output": "[['staff', 'neutral'], ['menu', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Olives served at the bar are wonderful."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The only con is the price ($110 for two people for a full meal)."], "output": "[['price', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When we went, the wait staff did not talk to us about any of the specials/the menu etc and handed us our bill while we were still eating."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["food was just ok,, to many high end places in such a cool lower east side neighborhood,like prune and apizz, prices to high in these places for this hood."], "output": "[['food', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitress recommended four courses, not three, given their tiny size."], "output": "[['staff', 'neutral'], ['food', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I was a bit taken aback by the paper napkins and the flyer like menu, but was excited nevertheless to taste the food praised by at least 6 people on this site."], "output": "[['miscellaneous', 'neutral'], ['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The place was empty except for one table, but they were just having drinks (red flag #1)."], "output": "[['place', 'negative'], ['miscellaneous', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Food was much better than the average Indian place in the area, and more interesting."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["In addition to Italian staples like pasta, chicken and veal parmigiana, house specials like chicken Giovanni (chicken breast with sausage, sauteed in white wine) and linguini Giovanni (shrimp and clams in red sauce) keep the menu interesting."], "output": "[['food', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Just be sensible, if the wait is 45 minutes or longer--just have sushi there some other time, and eat something else that night."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["So, get drinks elsewhere, have a nice dinner here, and stop by the package store on the way home where you can get a bottle of Bombay Sapphire for the cost of 2 drinks here."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["One person's dinner was cold, another was charged for a larger portion than ordered, and my shrimp pasta was inedible."], "output": "[['food', 'negative'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Babbo and Lupa are significantly better, and this place should redo the menu, or empty seats could become the norm."], "output": "[['menu', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Subtle decor, above average wine list and a menu with a difference."], "output": "[['ambience', 'positive'], ['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After dinner our waiter takes the bill and the manager tells him to clear our table so that we could leave."], "output": "[['food', 'neutral'], ['staff', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food was awesome if you can deal with wait staff who you can hardly ever find."], "output": "[['food', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Two complaints- their appetizer selection stinks, it would be nice to get some mozzarella sticks on the menu."], "output": "[['food', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We waited FOREVER on Valentine's Day for our table because their hostess had lost our reservation BUT the food was worthy of the long wait anyway."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative'], ['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter brought the wrong food and charged us for food and drinks we didn't order."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["our waiter from last year, a young man named Chris, actually remembered us (we did speak at length that evening about everything from food and wine to how to create good marrige)."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I went back to telly's because i heard that they changed the Chef and the food was again, after a very very small break, was excellent again."], "output": "[['staff', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Expect to be cramped and you may have to wait a little for your food, but the service is really friendly and helpful."], "output": "[['food', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Art and miscellany adorn the black-painted walls; strings of colored lights, disco balls and TVs are hung here and there; and on weekends a DJ fills the dining room with loud dance beats."], "output": "[['food', 'negative'], ['staff', 'neutral'], ['ambience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Pad thai and a variety of noodle soups, such as pho bac and Bangkok Curry, round out the menu and arrive in heaping portions."], "output": "[['menu', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The portions are not huge, but they do include an alcoholic beverage or fresh juice, so that made up for it."], "output": "[['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Although the food was good, it wasn't quite worth the price tag."], "output": "[['food', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["During my meal the waiter and waitress gathered with other friends that had arrived and they spent the whole time talking and ignoring the clientele."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Finally, one of the waitstaff noticed and brought out a dirty bus pan which he put on the table next to me and started bussing the entire dining room."], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Even though it wasn't totally full, the waitress had to RUN around the restaurant, and the drinks and the food took a LONG time to arrive."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After ordering a couple beers from the pleasant bartender, my date and I took a seat at one of MANY vacant tables next to the bar (The bar stools were full)."], "output": "[['staff', 'positive'], ['miscellaneous', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Had a few appetizers; smoked duck was served cold but good flavor, tofu was good/fresh too, nothing to rave about though."], "output": "[['food', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The price wouldnt be so bad if it wasnt for the poor service, average food, and uninspired menu selections (choice of tiramisu and strawberries with whipped cream for dessert?!"], "output": "[['price', 'negative'], ['service', 'negative'], ['menu', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["NEED Reservations in order to get past the host by the secret door and the maitre d host downstairs but No trace of snooby attitude here."], "output": "[['miscellaneous', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Then the manager said, hey we'll give you shrimp instead, which would have taken another hour."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I always find myself asking the waiter to make something bland and different than what is on the menu."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["In Short The vegi burgers (and the full bar) are the main draws: ranging from the Super Veg-Burger with lettuce, tomato and Abijah's secret sauce to the McKate (two un-beef patties, special sauce, lettuce, dairy or nondairy cheese, etc."], "output": "[['place', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food was a meal I could find anywhere else in the city for a better price."], "output": "[['food', 'neutral'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["and if that wasn't enough the owner threw in a free beer each for me and my friend."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Informal servers sashay past plastic chairs and patterned booths, ducking enormous lampshades with cheerful insouciance."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When we showed up, the guy at the door said it would be 15 minutes and that we could wait by the bar."], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["our waitress (who was ok) disappeared in the middle of our dinner, leaving us to an obnoxious amateur (must answer the phones or something) who could not answer our questions and treated us extremely rudely."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Wait staff started swarming around us as if we just ordered cokes throughout lunch."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Smallish menu, but more than adequate, and not that heavy on sauces which is so typical of italian restaurants."], "output": "[['menu', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Besides ordering single dishes you can also order family style."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the staff there was really freindly the owner even sat down at one point to chat with us, it was hard to chose from the menu it all sounded good, so my wife and i shared plates to try a little of each dish , we ordered."], "output": "[['staff', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Even at lunch, when lawyers and publishers flock in to wheel and deal over the justly-popular lunch buffet, the atmosphere remains serene."], "output": "[['food', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I highly recommend the chicken hearts, but remember: ask the waiters, since they're not usually available and will be cooked upon request (and will go fast)."], "output": "[['food', 'positive'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Had a late-night dinner there on Friday, and while the decor is fabulous, we waited a long time for our check."], "output": "[['food', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the decor isn't quite like Shun Lee but the service will definitely make up for any shortcoming."], "output": "[['ambience', 'negative'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["In the middle of dessert, the waitress silently passes by and drops the check."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter's recommendation for the entree (seabass in a lime and mango chutney) exceeded our expectations and we ate the chutney to the last drop."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["For the cost of the lunch I expected much better service."], "output": "[['price', 'neutral'], ['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Even though it's a trek for me to get there and the place is a little of a Hole in the wall, I've gone many times for the food alone."], "output": "[['place', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["In the main dining room, finding your waiter is Hell and aside from when they take your order and bring the bill, you'll rarely see them."], "output": "[['place', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We sat there with the check and ordered dessert and more drinks."], "output": "[['price', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["As a former waitress, I get this conceptually, and I am even understanding of the fact that I had to wait 30minutes to get my first drink because the bar was backed up."], "output": "[['staff', 'positive'], ['food', 'neutral'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["But my lunch was very light with a wrap, not tortilla, but something thinner, a rice paper sort of crepe, that had lettuce and spicy cabbage and thin sliced beef."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I have been a waiter for many years and I can tell you that if bad service is given you at least apologize to the costumer."], "output": "[['staff', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Those less interested in people-watching dine inside the whimsical, wood-trimmed room under a canopy of Italian inscriptions, or at the long, art-lined bar, which hosts a hopping after-work crowd."], "output": "[['place', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["And I'm saying that dinner has actually taken about an hour more than it should, just because of the slow service."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We sat near the sluggish, hot and very loud kitchen and the service area was not wiped down once during the entire time."], "output": "[['place', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Manager couldn't be bothered to come over and acknowledge the mistake."], "output": "[['staff', 'negative'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Soy abounds, in all forms: as firm patties, pure squares of glistening tofu, and something called a hijiki patty--mixed tastily with shreds of seaweed, then fried."], "output": "[['food', 'negative'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Evening service--featuring waiters all in black--is a little slow; plan on a leisurely dinner unless you're headed for the theater."], "output": "[['service', 'neutral'], ['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Try the stir fried cube steak, shabu sahbu, or the Oden, or anything else you want to try on the menu."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I sat at the bar to receive faster service, and boy was i wrong!"], "output": "[['place', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Within 3 minutes after we sat the waiter was hovering over us to get our food order."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My mouth almost dropped, and for good reason, when the server brought my sandwhich and side of macaroni."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If you think the prices are outrageous, just take the family, enjoy the ride and go in and order a few appetizers as prelude to a real dinner."], "output": "[['price', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["(Note: Price variations were listed nowhere--and I had asked for a to-go drink, deciding--after paying--to sit at a no-service counter until my drink cooled off."], "output": "[['price', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["This restaurant was a great value, even though I know nothing about the prix fixe menu."], "output": "[['miscellaneous', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["To enhance the dining experience, there is a live jazz band, which further isolates you from the world outside the gates."], "output": "[['food', 'positive'], ['ambience', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Surf-and-turf encompasses the menu's star entrees: deliciously charred sesame-crusted tuna with ginger ponzu gently juxtaposes espresso-rubbed filet mignon."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu is quite substantial, with a number of chicken, beef, and seafood specialties not found at your typical chinese restaurant."], "output": "[['menu', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Other than the too fruity drinks at the bar which wasn't my cup of tea, everything else was excellent."], "output": "[['place', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The porterhouse is as good a steak you are going to find in NYC or the surrounding area."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After a short wait at the bar (which was very crowded), we were seated upstairs at a private table."], "output": "[['service', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My only two complaints are that (1) our server was a real space cadet and kinda inattentive and (2) the sodas were really small; overall, though, I had a great time and really enjoyed my dinner!"], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After paying for our meal, we left some feedback with the manager (a chap named J."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Down right comfortable, pleasant, enormous portions, have lunch and bring home a doggie bag wth your dinner."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The host actually came over to my table and told me and my date we had to leave because we already paid our bill."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Their Korean menu was also equally impressive, A must try is the Kimchee cabbage pancakes as an appetiser ( the portions were as big as an entree!)"], "output": "[['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Waterview is one of the best diners I've evr been to interms of the quality and taste of the food."], "output": "[['price', 'positive'], ['miscellaneous', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["40 minutes later, the waitress finally looked at our table and we asked about our dishes."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The staff were all partying with each other at the bar, so even though we were the only ones there for food, it took 15 minutes to get menus."], "output": "[['staff', 'negative'], ['place', 'neutral'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["we told the waitress and she told us that we ordered the dead fish as opposed to the swimming fish."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter was confused and forgot an additional soda when we asked for it."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene Neither trendy and slick nor haute and haughty, it this cozy wine bar adds a bit of Mediterranean sun to the chilly east 70s."], "output": "[['place', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["This is one of two Ping's in Queens, the other one on Queens Blvd in Elmhurst serves great seafood dishes fished straight off clean tanks."], "output": "[['miscellaneous', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The place was beautiful, I sat at the bar for two hours and eat oysters and had way too many martinis."], "output": "[['place', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Unfortunately it gets very crowded on the weekends, so if you don't mind dining at the bar you can skip the wait for a table."], "output": "[['food', 'negative'], ['service', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If you are under 24 this might seem to be a great place in the big city but for the rest of us it's just a liitle too chheesy and the food is under par for the price."], "output": "[['food', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They spoon the FAT GREASE over your steak when they bring it to the table."], "output": "[['food', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["In Short This old-fashioned luncheonette, festooned with artificial flowers and signs touting the cherry lime rickeys, egg creams and banana-walnut pancakes, is favorite pitstop for folks visiting the Brooklyn Museum and Botanical Gardens."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I'm a chef (30 years), and I can honestly say that I've finally found Italian food worth eating at a reasonable price."], "output": "[['staff', 'neutral'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["unbeknownst to the three of us, the hostess made note of the fact that i was celebrating my b-day after a member of my dinner party made a very brief reference to it as we were seated."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Although we were seated quickly, ambiance was cozy, service was decent the overall menu selection and overall food taste and presentation was less to be desired!"], "output": "[['ambience', 'positive'], ['service', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Count on fresh, fairly priced cuts of fish that represent a good value, even if portions are a bit on the small side."], "output": "[['food', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Food is pretty good but the service is horrific."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Warming clam miso soup and expertly rolled Mexican maki (made with yellowtail, scallions, avocado, and jalapeno mayonnaise) pair well with a stiff glass of shochu, Japanese liquor with a bite as strong as tequila."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food Mafrici's approach to modern Italian fare may seem gimmicky: The menu lists eight seasonal ingredients, each prepared as an appetizer, pasta and entree."], "output": "[['menu', 'neutral'], ['ambience', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food was cold and did not match the description on the menu, the waiter could not be bothered with me (and I am nice to deal with since I work in the industry), and it was way over priced."], "output": "[['miscellaneous', 'negative'], ['menu', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The tables are close so you can hear every conversation going on around you, but if you're here with someone who enthralls you, you will notice no one else but your dinner date."], "output": "[['place', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["00 bottle of wine, we had to endure the waiter's attitude, like he was doing us a solid, if you're into huge Euro crowds and don't care about what you eat and how it is served to you, Baraonda is your kind of place."], "output": "[['service', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After waiting almost an hour for a table (with resies) our waiter told us that they don't have a sommelier because no steakhouse has a sommelier (patently false), and finished with the notion that he had absolutely no idea about any of the wines on the list."], "output": "[['service', 'neutral'], ['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We had to wait by the door, and the host failed to acknowledge our existence for a whole 15 minutes!"], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["A friend and I went for dinner, the host was rude to us as we walked in, we stayed because the decor is charming and we wanted french food."], "output": "[['food', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Not the best ambiance, but meat that'll make you drool."], "output": "[['ambience', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food is good and cheap BUT the attitudes of the bartender and wait staff are almost unbearable."], "output": "[['food', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When we got there, the wait was just as everyone here has described, Domenico's process was just as described, but the pizza?"], "output": "[['service', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I don't think the menu is particularly creative, but I've gotten solidly tasty sushi here and it's always enormous."], "output": "[['menu', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiters are very kind and helpful, and I regularly get something on the house - coffee, dessert or a drink."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It takes forever for them to serve you just drinks, and some of the waiters seem to not comprehend what you order."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The servers were extremely professional, especially considering the entire room needed to be served at the same time."], "output": "[['staff', 'positive'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitresses are so nice and will even help you pick a meal if you are new to spanish food."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Sit at the bar (no reservations necessary), eat, talk to the bartender, and enjoy, b/c come dinnertime you will pay quadruple the price (but it's still worth it)."], "output": "[['miscellaneous', 'neutral'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Once at the table our waitress managed on two occasions to take 15 minutes bringing drinks to our table, our plates sat uncleared on the table for just as long."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We had reserved space one one side of the bar, but when the staff tried to force the Pre-Fixe on all 15 members of the party to stay there, we moved to the other side (the difference in decor was minimal)."], "output": "[['place', 'neutral'], ['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Also lovely was the atmosphere; the high ceilings and spacious room make it a nice contrast from the other brunch mills on the upper west side."], "output": "[['ambience', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["never had a bad pizza, the staff has always been friendly, if not overly solicitous, and the only downside is the occasional wait on line outside."], "output": "[['food', 'positive'], ['staff', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We had a horrible night here stemming from intolerable service, no appologies after our food never came out after waiting longer than an hour and a half, and a plate of crusty bread thrown at us when we asked for their signature corn bread."], "output": "[['service', 'negative'], ['food', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Clams, shrimp, mussels, scungilli, and calamari served together in a spicy red sauce atop linguine are full of flavor; steak pizzaiola, a heroic portion of tender beef in a pool of garlicky marinara, comes with a side of spaghetti."], "output": "[['food', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene Vintage suitcases and black-and-white photos of old ocean liners evoke the Golden Age of travel in the front bar, where a worldly clientele sips cocktails around a flickering faux fireplace."], "output": "[['miscellaneous', 'neutral'], ['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We had reservations and when we showed up the manager told us the wait was over 45 mins."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Diners choose between deep banquettes or seats at the bar, which offer a front-row view of the small preparation area and a chance to watch the two chefs as they whip together the elegantly constructed desserts."], "output": "[['price', 'positive'], ['miscellaneous', 'neutral'], ['place', 'neutral'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We had to ask for the bill twice, and our water was refilled only when we asked for it."], "output": "[['price', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter had a slight attitude and brought our wine aprroximately 10 minutes into our appetizer."], "output": "[['staff', 'negative'], ['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We did enjoy the recommended, yet simple $40 sangiovese, atmosphere and loosey-goosey service, but we were disappointed overall."], "output": "[['ambience', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter poured our wine into my water glass, rolled his eyes when I asked for a new water, and definitely didn't offer to comp the wasted glass of wine."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I am a martini guy - vodka, not gin - and their classic martini with blue cheese olives is pretty damn near definitive."], "output": "[['staff', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["With the exception of one late day when I came in for caffe and the waitress nearly rushed us out since dinner was coming around."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I can't imagine waiting for 20 minutes to have my plates removed, given that usually the waitstaff hover around like birds of prey waiting for a fork to drop etc."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Oh, but on a brighter note, when the waiter poured water into my vodka glass by mistake, we got a free drink out of it."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My girlfriend asked the bartender what kind of wine they had and since she couldn't hear she leaned on the bar to get closer to him and he made a face and told her not to get near him."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["sashimi was meh, salmon was good but the tuna was a little white and seemed like the day before as the flavor had faded."], "output": "[['food', 'positive'], ['ambience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They do make great burgers for the money and give big portions of fries with it."], "output": "[['food', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Went to dinner with some girlfriends on Wednesday at Calico Jacks and had a fun time."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Philippe should re-train their wait staff to communicate with one another and better orchestrate the timing of food service."], "output": "[['staff', 'negative'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter never came back to check on us or refill coffee, he got one of the orders wrong, and we both left wondering what we were going to eat when we got home."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["You'd expect one to have more dessert options, other than rice pudding."], "output": "[['miscellaneous', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food is definitely the attraction, but the service has been consistently bad on every visit."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["really bad service took half an hour just to get a drink."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["But the waiter was very accomodating; he brought extra garlic bread at no charge, was attentive, and apologized profusely for not allowing us to order from the 12-and-under kids' menu."], "output": "[['staff', 'positive'], ['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The night I was there, besides extraordinary food and service, the owners; Carmelo Leotta and Pietro Cinquemani were belting out Mario Lanzi tunes on the Steinway piano."], "output": "[['food', 'positive'], ['service', 'positive'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter's knowledge of the menu and ability to make recommendations were ridiculously bad, requests weren't observed effectively, and our water and wine glasses were not kept full."], "output": "[['staff', 'negative'], ['menu', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Food is served simply but quickly with a smile."], "output": "[['food', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["First, the hostess gave us a nasty look when asked if we could eat at the bar, and then just swished her hand to indicate we could seat ourselves."], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I use to always get the turkey club, until recently where I have gotten more bread than turkey."], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Despite the fact that I had called earlier in the day and was told that the place didn't take reservations and there were several empty tables for two on both floors, we were told that there would be a 30 minute wait."], "output": "[['miscellaneous', 'neutral'], ['place', 'negative'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I must start by stating plainly that I love Jeollado, but it is loud, the service is bad, but the rolls are great and it is the best deal (CHEAP) in town."], "output": "[['service', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["we ordered filets, and ny steaks eventhough our waiter kept pushing up to get the porterhouse."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["What the sparse space lacks in decor it makes up for in atmosphere."], "output": "[['place', 'negative'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food is ok at best, but the service and the uncomfortable accomidations have such a negetive effect, that one can only wonder why they waited so long for so little."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["There are a few things I can forgive at any popular place: somewhat long waits even with reservations, service staff that mistakenly believes they're there to act haughty rather than serve, and a way over-the-top interior."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Inside as we waited momentarily for our table, the bartender made light conversation as he made our drinks."], "output": "[['miscellaneous', 'neutral'], ['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Tuesdays are Wine Lovers nights, where everything on their wine list is half off - it's a great deal."], "output": "[['miscellaneous', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["This Prospect Heights institution, with its old-fashioned soda-fountain type counter, complete with cakes of the day on pedastals w glass covers, attracts a diverse and loyal crowd."], "output": "[['food', 'negative'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service was a bit inadequate-and be warned they bring your food as it is ready- so be sure to order apps then after being served order entrees."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter messed up my order and we had to hunt down the wait staff to get a second drink."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were not offered bread and the host did not apologize until we asked for another update 45 minutes later."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["A friend asked for cheese on her pasta and the waitstaff, including the manager, REFUSED to give it to her."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We had at least 10 of the appetizers on the menu, which all were delicious."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We asked the waitress very nicely to please change the playlist to something more appropriate for dinner, she chuckled to herself and said sure but never changed it."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The host was playing god with his headset and reservation list, the bar was packed with horney drunken investment bankers, reservations are a joke and after haplessly sliding the plates at us when serving the food, they couldn't wait to collect the plates until we were done."], "output": "[['place', 'neutral'], ['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Because our daughters weren't sure what to order, and were a little intimidated at the surroundings (notwithstanding the beautiful simplicity of the decor), they ordered only appetizers while their fathers ordered dinner."], "output": "[['ambience', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We get our beers and then are told from a confuzed waitress that she realized that she can't give us the happy hour drink prices if we are not sitting at the bar."], "output": "[['food', 'neutral'], ['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["There is no menu and the waiter never told us how much lunch was, I thought it couldn't be more than $35."], "output": "[['menu', 'neutral'], ['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Every course was delicious, including the multiple chef samples, brought to you from the chef throughout your entire meal."], "output": "[['food', 'positive'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["this has become one of my favorite spots to hang out at the bar and drink martinis, not only because the atmosphere is energetic and lively, but also becasue the staff are so friendly."], "output": "[['place', 'neutral'], ['food', 'neutral'], ['ambience', 'positive'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["What we were treated to, instead, was snooty attitude by the waiter and the maitre d' and a dinner I couldn't eat."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We had to ask for water multiple times, there were no paper towels in the bathroom and even after informing a staff person they still were none an hour later."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food is worth it, but I suggest you order delivery, so that you don't have to read old issues of Robb Report while you wait forever in a small and hot room."], "output": "[['food', 'positive'], ['service', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["A blink-and-you-missed, tiny bar lines the lefthand side wall as you enter, which is packed with neighborhood hipsters, but it sadly interferes with the tables filled with dining patrons that are forking out mega bucks for mediocre fare."], "output": "[['place', 'negative'], ['miscellaneous', 'neutral'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Another quick tell-tale sign is the furniture at the bar and the seating tables."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Take out and delivery is next door and usually will be better if you are looking to get your food faster."], "output": "[['service', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Ignoring the plain decor, Jo-An is one of the best options for cheap japanese food on the Upper West Side."], "output": "[['ambience', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When my brother and I we had too much pizza in New York, we would like to order something else from the menu."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We ate at the bar to avoid waiting for a table."], "output": "[['service', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It was absolutely delicious to the point where i went back and asked for a variety plate They were so nice to accomodate me and gave me almost everything on the menu to taste from."], "output": "[['miscellaneous', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After waiting over a month for weekend reservations, I would of rather gone to IL Baggato."], "output": "[['service', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If you're looking for nonstop attention, a 20 page wine list and a waiter who puts your napkin on your lap, this is not the place to go."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We hunted the waitress to at least pay for the drinks."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Food : A++ Service : A++ Value : A++ No other steakhouse in Manhattan can beat Ruth's Chris."], "output": "[['food', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene There are exactly three small tables at this tiny hole in the wall, but for food lovers on a budget, it's heaven."], "output": "[['miscellaneous', 'neutral'], ['place', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter (a real cutie) had to ask us twice for our entree selections, the coffee orders were wrong and after saying, no, thanks, the pepper man poised his mill above my friend's calamari dish and ground away."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["A dish of chewy smoked seitan evokes Peking duck, while an entree of wide green-tea noodles is served in a tasty faux Bolognese sauce."], "output": "[['food', 'positive'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I had six different items on the menu (yes, I am a trencherman) and three were simply OUTSTANDING: the steak, the sweetbreads (best I've ever had), and the monkfish liver (also the best I've ever had)."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Chef Richard is always eager to please, and will be happy make something special 'off the menu' if you ask."], "output": "[['staff', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We did not have reservations so we sat at the small bar with the friendly bartender for 10 minutes."], "output": "[['miscellaneous', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After we waited nearly 25 minutes for our food (the place wasnt crowded), our waiter forgot some of our order and brought out a salad when we asked for everything to come out all at once."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We often come with a baby and the staff is so sweet and kind to her, it is a joy to be there."], "output": "[['miscellaneous', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I don't know why the place was almost empty until 8PM, but the food and service were perfect for the price."], "output": "[['place', 'negative'], ['food', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["First, the seating people gave me huge attitude and claimed I had not reserved a table at the grotto - and I quote my reservation You are all set for the grotta this saturday."], "output": "[['service', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the sushi was good and the service was not as bad as some would have you think but the crowd was more business than hip, more wall st."], "output": "[['food', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["On the other hand, I never felt rushed to vacate the place at the end of my meal."], "output": "[['place', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["There were 6 servers standing around watching me eat but they never asked if I needed anything or even offered me water."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["But once we spoke up (and they figured out what happened with the menus) they re-did the dish in a butter sage sauce, which was awesome."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I didn't take a look at the rest menu, but the oysters were fantastic."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Took my girlfriend here for dinner on a friday night, we were seated promptly and the service continued to be good for the remainder of the evening."], "output": "[['food', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The salad looked as though they have a premixed trash bag full of it, and they just dump a heap of it on a plate."], "output": "[['food', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food quality is good, but the prices are not worth it!"], "output": "[['food', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitress didn't seem to know anything about the menu, she forgot our drinks, took away our wine list after I asked to keep it, and then said, I'm sorry, I only slept 3 hours last night."], "output": "[['staff', 'negative'], ['menu', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter actually said he would check with the chef, like they might force us to share our food."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Ok, so the service can be a little spotty, but despite this Cafe Con Leche has good food, and decent prices."], "output": "[['service', 'negative'], ['food', 'positive'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They've got some of the best french toast you'll ever eat for Sunday brunch, and while their dinner menu hasn't changed much in the past few years, their food is reliable and they I always find something new in their chicken or fish specials, which are usually prepared with a red or white wine-based sauce."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service is pleasent, but they did forget to bring my mother in law's appetizer."], "output": "[['service', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Good brunch menu - it was hard to make a decision between the breakfast tacos, huevos rancheros, and salads on the menu although our waiter was happy to rank menu items upon our request."], "output": "[['menu', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter was able to answer any questions I had about the wine or food."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The crowd is not young, but hey, go somewhere else to get a drink afterward."], "output": "[['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Trendy decor doesn't make up for the avg food, adequate service and relatively high prices."], "output": "[['food', 'negative'], ['service', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I arrived with one other person at ~8:30 on a Wed night -- the hostess was very kind and showed me the reservation computer which showed that they were completely booked."], "output": "[['staff', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the bread they served as we sat down had a pastry-like crunch on the outside and still warm."], "output": "[['food', 'positive'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Same quality for 1/3 the price and a realistic atmosphere."], "output": "[['price', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Well, literally 7 minutes later we were being served dinner, with no apologies from the server who was too scared to come to our table."], "output": "[['food', 'neutral'], ['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The lunch specials are reasonably priced, but I avoid this place when I can only order off the regular menu."], "output": "[['food', 'neutral'], ['price', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The staff is nice, but they have the awful job of having to sell bland food as amazing treats."], "output": "[['staff', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I ended up wasting $24 on the most expensive dish on the menu."], "output": "[['food', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We had a late 9:30 pm reservation; when we arrived and went to be seated, there was some type of discrepancy since the hostess was missing in action."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The wait staff was all hanging at the bar, lounging around."], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu was still small, but the quality of food that came out of the kitchen was superb, and the service was not bad at all."], "output": "[['food', 'positive'], ['place', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Appetizers took their sweet time in coming, and literally about an hour later we had our main dishes which were very small considering the price."], "output": "[['food', 'negative'], ['miscellaneous', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["While dining on a delicate lamb carpaccio, and grilled skate wing, the owner explained that due to low lunch-time patronage, they may be discontinuing lunch altogether."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The decor was pleasant, but the tables were way too much crowded for a restaurant of this presumptive caliber."], "output": "[['ambience', 'positive'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The only downfall was that our appetizer never showed up, we were apologized to, and it wasn't on our bill, but we also didn't get the jumbo shrimp we were all craving."], "output": "[['food', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["From the enormous menu, we opted for the 3-course dinner specials - chicken soup or clam chowder, although small portions, came with loads of rolls, crackers etc."], "output": "[['menu', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Drinks were well priced and the buyback rate was fantastic."], "output": "[['food', 'neutral'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Despite him not being my designated server, he basically took over for our inexperienced waiter the rest of the dinner."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service was great, the chef even gave me a complimentary dish."], "output": "[['service', 'positive'], ['staff', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Tension filled the air as the chief yelled at a waiter in the middle of the bar while in uniform and drinking."], "output": "[['miscellaneous', 'negative'], ['ambience', 'neutral'], ['staff', 'neutral'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["then the manager gave us lemon juice instead of ceasar dressing for a ceasar salad which ruined the salad."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['ambience', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Midway through the meal the waiter came over and said we were being charged $40 a head since there were 7 of us, and they never said that when i made the reservation."], "output": "[['food', 'neutral'], ['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I excused myself from my table went downstairs to inform the hostess that I would like to suprise my dinner guest by recognizing his birthday in a very understated way."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I organized a dinner for 20 and was extremely satisfied with the results."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The only cuisines that will provide comparable quality in the vicinity are Greek (if you know where to look) and Pizza."], "output": "[['miscellaneous', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The other two entrees that were ordered were very large portions."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["nice place, good service but the price is a little bit more expensive when compare with the area, location and small dishes."], "output": "[['service', 'positive'], ['place', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were served by two very rude waitresses who slammed every glass and dish they brought onto the table, and then got so caught up by hanging out at the bar that I eventually had to hunt them down to pay my bill."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['miscellaneous', 'neutral'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The hostess kept me waiting 10 minutes (attempting to read seating chart which I assume was in cyrillic) before determining whether she could seat us."], "output": "[['staff', 'negative'], ['service', 'neutral'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["A server came shortly after that with a cheeseburger, which is not what i ordered."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Went to dinner on a Friday night and the place was packed and hot."], "output": "[['food', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We didn't order-the waiter just kept piling the food in front of us."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Upon arrival I attempted to give a waiter my name (there doesn't seem to be a hostess) and tell him I had a 9pm reservation, but was told to just go get in line and wait for a table."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Food is fine but unremarkable, atmosphere is very noisy, especially for a date, and our waiter looked like he had never seen us before when we reminded him that we had ordered a second round of drinks 20 minutes earlier."], "output": "[['ambience', 'negative'], ['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The cool thing about the 3 course price fix is that there is no special or limited menu, you can order ANY app, ANY entree and ANY Dessert."], "output": "[['price', 'neutral'], ['menu', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The space is small and reservations are definitly needed."], "output": "[['place', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Servers struggle to explain the menu to those who can't tell an idli from a chapathi, but the mostly Indian clientele is completely at home with the vegetarian South Indian fare."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Had to constantly ask the waiter to top up water glasses, but generally service was ok."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["As we sat waiting for our menus, we started noticing the frowns on the faces of the people around us, watching as patrons tried to flag down waiters without luck, asking for things like water."], "output": "[['service', 'neutral'], ['menu', 'neutral'], ['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Ones experience is truly dampened by having to trundle up lifts and escalators, further on arrival at the restaurant we found the actual dining room to be slightly sterile and lacking in atmosphere."], "output": "[['place', 'negative'], ['ambience', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["service was reasonably quick via delivery, but the hunan beef had no spice whatsoever and the chicken chow mein really looked inedible."], "output": "[['service', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The bar is available while you waiting for the table, the DJ is nice."], "output": "[['place', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The seating for dinner is uncomfortable, too close to the bar which gets really crowded since it is so small."], "output": "[['food', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["In Short Custard Beach is located in the lower-level dining concourse of Grand Central Terminal, which features seating, many dining choices and a crowd of tourists and commuters."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I am not one to waste dessert but we threw away the box after taking a few bites of it."], "output": "[['food', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food wasn't impressive either- I was expecting huge portions, but my lobster ravioli was only 4 medium sized pieces, and I've tasted better at other restaurants."], "output": "[['food', 'negative'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["As the afternoon progresses, you'll see as many waitstaff as customers scurrying after food carts with bill cards in hand, clutching stacks of steamers back to their tables."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Food was much better then I had remembered (smaller menu) Great place for lunch."], "output": "[['food', 'positive'], ['menu', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Even if their service was not top notch at all times, at least the wait staff was very accommodating and respectful."], "output": "[['service', 'negative'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waitress bought us a round of after drinks too."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["This is the perfect place to come with a group from work, people from out of town, or just to have a drink at the bar and enjoy the atmosphere."], "output": "[['food', 'neutral'], ['place', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["While you're standing around for a good half hour waiting for two plain burgers, you're being bumped into by people waiting to be seated because of the narrow passageway leading to the dining area."], "output": "[['service', 'negative'], ['food', 'neutral'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["after the main course the waitress brought desert menus and never came back."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When the other half of my party arrived, the waited helped us with the menu, and i was happy to know you can mix and match items in their lunch box I got the mekong box and i could not believe how great the pork sandwich was, I also enjoyed the asian salad and brownie tremendously."], "output": "[['menu', 'neutral'], ['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene Upstairs in a narrow, handsome but oddly shaped space, this serene, refined restaurant caters to a mostly business-oriented crowd that, auspiciously one presumes, is predominantly Japanese."], "output": "[['miscellaneous', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The bread was served, one razor thin slice on our bread plate, by the waiter."], "output": "[['service', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Good value for breakfast."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Went here with my husband on a Saturday night for dinner since the place looked like it had great atmosphere."], "output": "[['food', 'neutral'], ['place', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["However, unlike a lot of places the service was great: we walked in after not being able to get a reservation and were seated within 10 mins."], "output": "[['service', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I haven't tried a lot of their menu however their appitizers are tasty and fairly priced."], "output": "[['menu', 'neutral'], ['food', 'positive'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Highly suggest you sit at the bar for added atmosphere and generally friendly people."], "output": "[['place', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waitress was a bit cold but she was still attentive and food came quickly."], "output": "[['staff', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["From the bottomless cup of coffee to the basket o' scones mini-muffins to the delicious entrees, Dizzy's is the place to be."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We ended up hanging out for a few hours at their bar with a staff that we felt like we've known for years."], "output": "[['place', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["To SM's credit, our waiter was eventually replaced and the matre d' offered us free dessert, but we're not going back there ever again."], "output": "[['staff', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Be prepared to make friends with the people sitting next to you, tight seating."], "output": "[['miscellaneous', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our server was a delight, she helped guide us through the menu with honest insight."], "output": "[['staff', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When I read some of the reviews in this section, I am not sure if they had diner in the same restaurant and also I would not be suprise if they decided to have their Branzino well done with butter on the side."], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["There's no bar, only beer and wine, and you're likely to be annoyed by unruly Park Slope offsprings, so come late and enjoy the smart wine list."], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Not only is there very little on the menu besides steak, but you really have no choice of what cut of meat to get."], "output": "[['menu', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["On top of it all, I was with family from out of town and the only reason I took them there was because a friend had mentioned the place and Coffee Shop had a little wait."], "output": "[['place', 'neutral'], ['food', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["What I thought was a rip off was, when we were ordering, the waiter told us there was a minimum of food we can purchase."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food *was* pretty good, though, (though certainly not worth the prices) so it's worth checking out if you have an expense account to work with."], "output": "[['food', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["- , the desserts are sinful, the moroccan hospitality evident in the wait staff's friendliness and there is an overall ambience that makes you want to stay all night!"], "output": "[['food', 'positive'], ['staff', 'positive'], ['ambience', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Service was good, the waiter was a little flip, but we can deal with that."], "output": "[['service', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service and atmosphere may not set your mood but when you're done you will realize that it's only the food that counts!"], "output": "[['ambience', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We ordered one of the specials our decent waiter mentioned, and one of the chicken dishes off the menu."], "output": "[['food', 'neutral'], ['staff', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I got fed up waiting that I went to get the check and paid for it at the counter where my waitor was busy flirting with the cashier."], "output": "[['service', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Although the food was in small portions, it was good."], "output": "[['food', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Service was at best distracted, at worst disdainful, even though we came early with a reservation and are not food novices."], "output": "[['service', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["One example: They literally took bread from my baby, after we ordered a brick oven pizza, not food (the waiter's words)."], "output": "[['food', 'negative'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The drinks are cute as is concept--unfortunately, the service is not and neither is the wait."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The garden is beautiful and romantic place to share dinner with that special someone or just with friends."], "output": "[['place', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Seating is usually very prompt but expect a wait at peak times such as Sunday Brunch."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We ate here once and the waiter was very aggressive about pushing the specials instead of what was on the menu."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Though the celery root soup was super yummy - everything else was an overpriced letdown- the plates come out looking like it's the depression era."], "output": "[['food', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I ordered the plane no fuss SALMON and it was honestly the best salmon EVER."], "output": "[['miscellaneous', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My boyfriend and I loved Imagine Bar and Grill."], "output": "[['place', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We recently visited Madiba for lunch, and our waitress was sweet but ineffective."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I politely asked the waitress to explain these charges noting that the menu was misleading and she got frustrated mad and then told her manager."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The wait staff are friendly, but they disappear after they take initial drink and food order."], "output": "[['staff', 'positive'], ['food', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["had the $80 chefs tasting menu - was excellent -and we were stuffed - basically is a bit of all of their special dishes - one at a time - with sushi soup coming last."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I ordered a dirty martini that was not dirty at all-and when I asked the waitress to make it dirtier, instead of reshaking/making it at the bar, she broght me over some olive juice in a cup!?"], "output": "[['food', 'negative'], ['staff', 'neutral'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["last time, the waiter told my roommate he'd have to charge her $5 for mushrooms as one of her omelette choices (never heard that at my other favorite brunch places."], "output": "[['staff', 'negative'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My date and I were both taken back by the lack of the friendly attitude from the owner of the restaurant."], "output": "[['service', 'positive'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["atmosphere is not that relaxing, if you go - you MUST bring a cell phone and go down the street for a drink."], "output": "[['ambience', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Everyone says that their round slice is no good, but the Sicilian is so good that I have never tried the round."], "output": "[['miscellaneous', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My party felt like we got put in a dining room for tourist, which must have been the penalty box area for the disgruntled wait staff on duty."], "output": "[['place', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The place is small and intimate and you may feel a little crowded, but the service is excellent and it's great for friends out, a romantic date, or a special occassion."], "output": "[['place', 'negative'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I recently went to this restaurant with some co-workers for lunch and had an amazing time."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I felt that the meat had little flavor(ribs and chicken) and as result I had to use A ALOT of their bbq sauce (which is good) and the ribs were not falling of the bone."], "output": "[['food', 'positive'], ['ambience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The server (Jasmine) checked up on us periodically and was patient as she explained certain menu items."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The decor in the dinin room is a bit bland, but the service is always friendly."], "output": "[['ambience', 'negative'], ['place', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I'd say the menu is generally below-average for the neighborhood, but if you want a burger, this is the place to go."], "output": "[['menu', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The wait here is long for dim sum, but if you don't like sharing tables or if the typical raucous dim sum atmosphere is not your gig, this is a sleek (for Chinatown) alternative."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Once seated we were greeted by a very rude waiter who threw menus at us and then snatched them away as we were ordering."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The wine list is short and the wine glasses suck (not spigleau or riedel, in addition they are small for the big italian wines on the menu)."], "output": "[['food', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It's a shame you can't even sample the food or sit in what is a very nice space."], "output": "[['food', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If you don't care about the wait staff as long as they bring you your drinks and dinner, then go to Opa."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Even though the place was more than half empty he refused to do so because we had already given our order to the waiter and a change of tables would cause too much confusion."], "output": "[['place', 'negative'], ['staff', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food wasn't overwhelming, but was very tasty, and the space wasn't overcrowded or obnoxious - the waiters and waitresses were attentive and helpful, but not obtrusive."], "output": "[['food', 'negative'], ['place', 'positive'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Seemed like they got something wrong with every drink order Bartenders were def."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["A few times at the bar I felt as though the Sushi chef an older gentleman was laughing at me and my girlfriend."], "output": "[['place', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Also, they upped their prices, so I have their old menu, and was surprised when my bill came to over $5 more than it used to (I know, not a huge deal)."], "output": "[['price', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They kept us waiting for more than an hour WITH a reservation and WITHOUT an apology."], "output": "[['service', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Though the wait staff was attentive, when the raw (really, not al dente) potatoes were brought to our server's attention, she listened but didn't respond."], "output": "[['staff', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["An Egg like custard appetizer, a platter of different kinds of rolls made from: Lobster, Eel, Sword Fish, Trout, Blue Fin Tuna, Horse Mackerel, and Salmon Roe."], "output": "[['miscellaneous', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter fast to get our drinks, aptz, and orders."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Their service needs some work, but it is safe to say that you will enjoy the food."], "output": "[['service', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Don't let the decor fool you because you will miss out in some of the best food you ever eaten."], "output": "[['ambience', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["worth every penny, and with the deals on the bar , you could drink and sing to CURRYoke all night,,,,"], "output": "[['price', 'positive'], ['place', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I naively thought dinner was served during the show, but the waiters don't come by once the shows start, so order your wine 30 mins before the show start time."], "output": "[['food', 'neutral'], ['service', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene With three outposts around town, Sarabeth's Kitchen has become a well-known and reliable spot for casual dining at breakfast, lunch or dinner."], "output": "[['miscellaneous', 'positive'], ['place', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We actually enjoy eating there earlier for lunch definatly a more relaxed atmosphere."], "output": "[['food', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["In addition to the two rounds of drinks, the bartender and owner were a hoot."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When I got home, there was a message on the machine because the owner realized that our waitress forgot to charge us for our wine."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were seated promptly there were a few people waiting in the bar, but had ordered quickly been at the table less than 45 mins."], "output": "[['service', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitress could have been more specific when I asked for a wine suggestion."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The uptight female manager came up to our table and rudely asked us to get up because they had a party waiting to eat."], "output": "[['staff', 'negative'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["However, didnt take too long to get drinks and the hostess seated us promptly."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The prices are decent for this type of food and dining experience."], "output": "[['price', 'positive'], ['food', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Interesting crowd for people watching - old school Italian music cranking - friendly Italian waitress brought us our wine garlic bread in no time."], "output": "[['ambience', 'positive'], ['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Their relatively recent introduction of a version of the Sicilian pie is called the Grandma pie featuring a thin crust, much sauce, with less cheese, and chopped Basil."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Went on a Saturday with out of town tickets and the food was great but the service was awful, even surely."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Whatever happen to FAMILY STYLE Thai cooking, the portion are too small and tradtional thai cooking uses MSG which I prefer not to have in my body."], "output": "[['food', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They have possibly the worst service in New York I have waited until the waiter has finished his paper, begged for water and waited over an hour for my meal."], "output": "[['service', 'negative'], ['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["By the end of the meal, we were shaking hands with/hugging our waiter as we stumbled/rolled out the door."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitress at the bar was very nasty to me because she mistakenly took an order for thai ice tea from me when I asked for thai lemonade in a to-go cup."], "output": "[['staff', 'negative'], ['place', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If you don't want to wait 45 minutes for a table or a long time for service then don't go @ 9pm on a Friday or Saturday night."], "output": "[['miscellaneous', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The manager also refused to remove the drink from the check, suggesting that if we didnt like it, we could simply remove the corn ourselves."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The space is cool, but the food and service were awful."], "output": "[['place', 'positive'], ['food', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The place is full of flavor and color and the music just puts you in the mood for food and drinks."], "output": "[['place', 'neutral'], ['ambience', 'positive'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I loved the food and service here, the only downside was the decor was dissappointing and the prices are a bit high (about $30 for an entree."], "output": "[['food', 'positive'], ['service', 'positive'], ['ambience', 'negative'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Plus, everything comes in small to average portions, so the next time you get a sushi craving, I don't recommend that you go here."], "output": "[['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["we had dinner at becco on a friday night, and were seated in the left bar area, which while pretty crowded, had a manageable noise level."], "output": "[['food', 'neutral'], ['ambience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We had a 9:30pm reservation for two which stretched out to an hour wait."], "output": "[['miscellaneous', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If only they'd get a better wine list - the reds are all so mediocre - this would be the perfect meal."], "output": "[['miscellaneous', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Special touch -- my dessert plate had Happy Birthday drizzled in chocolate."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service isn't fantastic and the seating is a bit tight but if you aren't looking Four Seasons type quality, then this is the perfect spot to meet some friends for dinner or lunch."], "output": "[['service', 'negative'], ['place', 'negative'], ['miscellaneous', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["This is the perfect spot to meet up with friends and have a drink at the bar or stay a while and enjoy the scene and savor the food."], "output": "[['miscellaneous', 'positive'], ['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We got the tasting menu($100 for two), which was a selection of the signature dishes."], "output": "[['menu', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The arrogant maitre'd was annoyed when i asked about sitting down those tables are for other reservations low and behold those tables were still open as my wife and I finished dinner."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Don't go if you want a serene environment to go with your sushi."], "output": "[['ambience', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the food is still awesome - the twist on mexican is perfect - but the service is terrible - from the apathetic hosts to the unbelievably slow servers."], "output": "[['food', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were here for lunch and were seated promptly in the bright, comfortable dining room."], "output": "[['food', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Caravan can be a little slow sometimes, but more than makes up for it in the quality of the food and the care of wait staff."], "output": "[['food', 'positive'], ['service', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Bland food, arroganrt waiters."], "output": "[['food', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service is a bit slow, but harkens back to my years growing up in Napoli, Italy where things are not rushed and when you sit down for dinner the table is yours all night."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I will definitely try dinner, but they do need to fix the kitchen shifts so that people get served in a reasonable time."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I went to Ciao on a Saturday evening and the food was not up to the price asked for."], "output": "[['food', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My group and I cancelled whatever drinks we ordered (no food order since there was NO wait staff) and left."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiters do not tell you that and our large party wound up with over $100 extra food because all members thought dessert, coffee/tea were included - which they lead you to believe - and they weren't."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["On the menu, unusual offerings like mango salad, Kashmiri chicken and whole fish cooked in mustard sauce refute the strip's infamous reputation for one-sauce-fits-all cooking."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Knock off 15-20% of the prices and you have a decent night out."], "output": "[['price', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["had to ask the host for the check because the waitress was sitting at another table taking their order."], "output": "[['staff', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["However for one appetizer, three entree's, one shared dessert, and two bottles of white, the bill was a cool $100!"], "output": "[['food', 'neutral'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We sat at the bar so the service wasn't too bad."], "output": "[['place', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I liked the hummos platter, the brie sandwich, and about 20 other things on the menu (if they still have the chocolate cake you need to get it)."], "output": "[['miscellaneous', 'positive'], ['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["But in my opinion, a great experience doesn't just pertain to food, and an evening of dining is certainly given a bad taste when the service is not up to par."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["A regular Japanese menu is available for those who would like to experience traditional Japanese cuisine."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It's in a less travelled spot on 3rd, but the intimate setting is great and romantic."], "output": "[['miscellaneous', 'negative'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The kitchen staff either cannot or will not accomodate special diets which is surprising given that there are so many fine dining establishments that do have special menus to cater to vegetarians."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It's a good place to meet up with a friend while shopping, grab lunch (although the lines do get long), dining solo, or to take home after work."], "output": "[['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The server also forgot about our dessert."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The only thing that I was unhappy about was that one time, the restaurant received a delivery of supplies and the rolled it in through the dining area into the back kitchen, with the deliverymen shouting loud things to each other in chinese."], "output": "[['place', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It came with a (small) salad, large bowl of udon, and 6 pieces of sushi plus wrapped rice (not sure what that was called."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We sat at the bar and were constantly bumped by the waitress flying past; had fabulously fresh raw oysters with pieces of shell in every bite; lobsters rolls were tasty but the large pieces of meat were tough; the apple crumble was excellent but the ice cream was over-frozen and the stench of frying oil was nearly unbearable."], "output": "[['place', 'neutral'], ['staff', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["best chicken in queens."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Reservations for parties under 5 people isn't allowed but their yummy cocktails and handsome waiters help soothe the pain."], "output": "[['miscellaneous', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Interior is limited, but there is a second floor for dining to avoid some of the main floor chatter."], "output": "[['place', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Handsome baritone Nordic waiters patrol the room, proffering fresh-squeezed juices and $4-a-person pots of French press coffee."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The bartender said that they didn't have one, but did say, We have mixed drinks."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It seemed to take the new staff forever to figure out what they were doing; I had one nightmare of a brunch where the registers didn't seem to work and it literally took over an hour to get our check."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitress was slow and forgot drinks and food we ordered."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter was not attentive he gave me the wrong drink twice and the bill for three people who had appertizers, a drink and an entree was $200."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["A bustling crew of sage green-shirted servers whisk plates of luncheon and light dinner favorites to power lunchers, tourists, and ladies who lunch."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the place has an awesome decore, with fish swiming below certain tables."], "output": "[['ambience', 'positive'], ['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When one purchases a bottle of wine, it's fairly common practice for a server to come by and refill your glass, but not the case here; 2."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Service: Below Average, the staff joked stood around in the dinning room joking around with each other."], "output": "[['service', 'negative'], ['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Although the dining area is a bit small you'll feel at home as the owner is very friendly and talkative."], "output": "[['place', 'negative'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["In April, the service was fair but again, the food was at best only warm."], "output": "[['service', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Increedible value, 3 courses $20 price fixe(menu changes everyday), organic seldom seen wines all around $20."], "output": "[['miscellaneous', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Perhaps it was because the 20% tip was already added to the bill, but the waiter brought us plain gazpacho without any of the other ingredients described on the menu; later, when we complained, he brought us saucers of garnish instead of new bowls of the soup properly prepared."], "output": "[['price', 'neutral'], ['staff', 'negative'], ['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Yes the wait is dreafully long, the place feels a bit uncomfortable to talk in with your dining partner, but the food is excellent none the less."], "output": "[['service', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The host came by and told us that they made a mistake and would have to seat us at a two-person table."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere couldn't be better, and the service was outstanding -- at the time there were only two people working the entire bar, and we still got taken care of like it was a five star restaurant."], "output": "[['ambience', 'positive'], ['service', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food was great so that made up for the lack of service from the waitress."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitress apologized for the long wait and said they would give us some free drinks or desert since they forgot about our orders but we never received anything and by the time we got the bill we just wanted to pay and leave."], "output": "[['staff', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When my family and I visited, we were hearded in and out of the restaurant like cattle; not once did our waiter ask how are meal was, and the waitress mixed up our steaks."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Music is a nice mix of everything from Aerosmith to James Brown to Metallica to disco to whatever else there is."], "output": "[['ambience', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food The menu is a paper buffet--pick your cut of meat, dress it in either a sauce or a baked-on chapeau and then pick accessories, such as Yukon gold mashed potatoes, bitter greens or wilted tomatoes with blue cheese."], "output": "[['menu', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter (the one with the Spanish accent) was a bit pre-occupied with other things- hardly coming around to the table and nowhere to be seen most of the time."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If you want peace quiet, ambience and patient service, go elsewhere."], "output": "[['ambience', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The only time the waitress paid any attention to us was when she took our order and at the end of our meal to ask if we wanted dessert (by then we had already packed up our leftovers and were waiting for change from our bill)."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Great food -- but some of the worst service in the neighborhood."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Worth the trip over the bridge, worth the search for parking, worth the wait for a table at dinner time and worthy of a ten rating."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere is perfect, whether sitting down for dinner or just having a drink at the bar and engaging the friendly bartenders in converasation."], "output": "[['ambience', 'positive'], ['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The server came to us and was sooo hot, he went over the menu and specials with us."], "output": "[['staff', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Service was en pointe and I felt like the servers were always aware of our wants, whether it was punctual refill of water, new napkins, etc."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Reasonable prices for Cuban food in the city."], "output": "[['price', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["This is the kind of place that is suppose to have pushy waiters and a loud atmosphere."], "output": "[['place', 'neutral'], ['staff', 'negative'], ['ambience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Although the food was good, the way our waiter treated us was so rude and bad-mannered that it almost ruined our night and he even asked us to give him a better tip!!!"], "output": "[['food', 'positive'], ['staff', 'negative'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the pre dinner drink at the bar was very pleasant, good start, although we waited up to about an hour before our table was ready."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["A simple dish like Fattouch or Tabbouleh are turned into the most delicious salad youll ever have."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I thought the service was a little slow and not attentive enough for the price but other than that I'll be back when I can afford to spend $60 on dinner!"], "output": "[['price', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Since I listened closely, I know they were a party of 2 without any reservation The manager then offered to seat us but we left."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The feeling of unwelcomeness was especially prevalent due to the fact that our waiter hovered over our table and immediately cleared the table of dishes and glasses, some of which were still full in order to get us out the door ASAP."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu features American bistro dishes like crab cakes, chicken under a brick, fresh oysters and various seafood dishes."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Another hour waiting for our food, we spoke to the manager, he told us he would give us a discount off our bill."], "output": "[['service', 'neutral'], ['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Went to Butter on Monday night for a friend's birthday dinner at like 11:00pm, the kitchen was supposedly closed, but we spoke to the manager and we were seated promptly."], "output": "[['food', 'neutral'], ['place', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["yes this place has good pizza but HORRIFIC HORRIFIC delivery service."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["A simple shrimp seviche with fresh cocktail sauce shines on the lunch menu, while dinner items tend to be more sophisticated, such as turkey filet mignon with bacon and a bold mole negro."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Unless you like getting bumped by waiters and people walking by, do not sit at a middle table."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Nice decor poor food poor service."], "output": "[['ambience', 'positive'], ['food', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I expected high prices at Nello, but as I looked at the menu my eyes became as large as the Birkin Mary-Kate has been seen toting around these days--$18 for soup, $22 for a plate of mixed greens, $40 for pasta."], "output": "[['price', 'negative'], ['menu', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["While the food was good and reasonably priced, the service was horrible."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Atmosphere, I'd give to Rosa or Maya, but Mexican fare at Zarela is tops."], "output": "[['ambience', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["not to mention that the waiter offered putting a scoop of ice cream on my dessert."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The kitchen is fast, but you sometime may have trouble getting a seat, since this place is very small."], "output": "[['place', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere's a bit grungy, yes, but the music and the coffee are good."], "output": "[['ambience', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If you want a quiet dinner don't show up late, cuz the atmosphere gets louder and more loungy as the nite goes on."], "output": "[['food', 'positive'], ['ambience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After a few minutes, seeing we were without menus, a slightly more pleasant waitress approached us and explained that the manageress had asthma and wasn't in a good mood."], "output": "[['menu', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The servers didn't know what tables the meals were going to, it was a complete comedy show."], "output": "[['staff', 'negative'], ['place', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The only other negative, we found the waiter to be slightly pompous, and when I asked him some very basic wine questions, he was lost."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter was courteous and knew the menu well, though he was a little pushy with the bottles of wine."], "output": "[['staff', 'positive'], ['menu', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My two best friends took me to Cafe Gray for my birthday and by the end of the dinner, they were apologizing for the poor service and so-so food."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The outdoor tables overlooking bucolic Irving Place, or the wooden ones inside, are prime spots for brunch featuring all the usual suspects--omelets, pancakes, French toast--served on cast iron skillets and griddles."], "output": "[['place', 'neutral'], ['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["With the large crowds here and the larger menu, be prepared to wait for your dinner to arrive at your table."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Well I can't tell you how the food was because the moment we walked in, the single waiter was extremely rude and told us to wait outside while he cleared a table (in the middle of winter) because he was busy."], "output": "[['food', 'neutral'], ['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["junk food place that could do well with a good cleaning."], "output": "[['place', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["And while a narrow wood counter and three stools provide desperation seating, most folks choose to take lunch and dinner to go."], "output": "[['miscellaneous', 'negative'], ['place', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["All-night restaurant with excellent burgers and stella on tap."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The manager came personally to apologize and to my surprise, he brought me the drink, a big chocolate chip cookie, and a bag of chips!!!"], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I went anyway and was greeted by the rude owner who practicly ripped our outside drink from our hands (although we were trying to throw it out anyway."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["it's a very chill spot to hang with a group, I went there with a bunch of my friends to have drinks for my birthday and we all had a great time."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The upside of the smallish portions is that a good sake can do a better job working over one's date, and you don't leave the table w/ a food coma."], "output": "[['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I don't claim that the place as the most authentic, but when you're talking about Southeast Asian street food, which really represents a melting pot of cultures and have slight variation in style for many similarly-named dishes depending where yuo're specifically from, who's to claim what's authentic?"], "output": "[['place', 'positive'], ['food', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I have never been to an establishment that boasts traditional French service that basically throws food at you; waiters not only reach across the table but drip wine and water all over their diners."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Amarin's food is always fresh, although the quality does vary--avoid ordering on Friday Saturday nights, prime dining hours, when they seem to throw things togehter a little too haphazardly."], "output": "[['food', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["i just wish they wld drop some staff though, sometimes you feel like your being stalked by waiters, waiters helper, waterperson, busperson, food runner, supervisors, managers."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["not fancy I think they keep their christmas decorations up all year long, but good mexican food!!"], "output": "[['miscellaneous', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["She's watching your table, helping the staff candy to your eyes."], "output": "[['miscellaneous', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I would definitely recommend getting reservations as the wait can be very long."], "output": "[['miscellaneous', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Once seated the waiter took our drink orders only to return 10 minutes later with the wrong drinks."], "output": "[['staff', 'negative'], ['food', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Someone should tell these people that high prices on the menu does not make your restaurant better."], "output": "[['price', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Lastly, after spending a little over an hour and most of that time waiting for our food to arrive the manager barked at us to leave to make room for another party that had been waiting for 25 minutes!"], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["This Restaurant was very Ask to the waiter or waitress to give you a table in the back room where all the romance of the place is situated with a so-called chimney!!"], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["This past Memorial day weekend was hot and I asked the waiter why was the air condition not working and he responded doens't know why."], "output": "[['staff', 'negative'], ['ambience', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["There is nothing else on the menu except for exotic teas and cold beverages, but with a meal this cheap and delightful, who would care?"], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Food was good although menu was a little limited(still plenty to chose from)."], "output": "[['food', 'positive'], ['menu', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["On each of my several visits, the crowd is local, professional, family and those who are not familiar with the cuisines of India are deftly walked through the menu by management."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral'], ['menu', 'neutral'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Delicious appetizers and entrees, our server recommended a wonderful bottle of wine, and we couldn't resist dessert."], "output": "[['food', 'positive'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After I have my dinner I try to talk to the manager and let him know that he had very good workers and that he should be more considerate with them and the answer that I got from him was (THey can leave I don't care)."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Its great for people who want to try Korean food, but can't understand the servers or the menu on 32nd St."], "output": "[['food', 'positive'], ['staff', 'neutral'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The huge terrace is just so beautiful--and rumor has it they'll be tenting the space this fall, so we midtowners can continue to dine outside through the end of the year."], "output": "[['miscellaneous', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["This much heralded restaurant brought my wife and I some excitement as we walked in the door, but we were met with an awkward maitre'd who barely spoke to us at all and just seemed standoff-ish."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I had the salmon dish and while it was fine, for the price paid, I expected it to have some type of flavor."], "output": "[['price', 'neutral'], ['ambience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When I saw it on the menu I didn't beleive it and was not expecting the real thing."], "output": "[['menu', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It took the waiter over a 1/2 hour to come over to tell us the specials."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["even when they informed us they were out of the port we chose to accompany our dessert, the manager made sure that we were offered an even better bottle that wasn't even featured on the menu."], "output": "[['food', 'neutral'], ['staff', 'neutral'], ['miscellaneous', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Many meals were delivered by two servers, besides having a waiter to oversea the process."], "output": "[['food', 'positive'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Obviously bz place, greeting was less than welcoming, service was adequate from less than friendly waiters, steak for 2 was anything but spectacular served with sauce that's better suited for seafood than meat."], "output": "[['service', 'positive'], ['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I have been to Blue Ribbon Sushi at least 75 times and have never ordered the same dish twice, that's how awesome the menu is."], "output": "[['food', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Anyway we get a table and order some appetizers from one of the waitresses who was pleasently nice."], "output": "[['miscellaneous', 'neutral'], ['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If it was outstanding I could see it as a nice change for lunch, but the peanut butter wasn't any better than one you could buy at any grocery store and the chocolate peanut butter brownie was horrible."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It's served cold with carmelized onions atop, with mashed potatoes on the side and it's the best darn thing this side of the Hudson."], "output": "[['service', 'positive'], ['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Every item on the menu tasted like it had been lovingly perfected- from the pulled pork sandwich on white roll to the smokey baked beans, buttery mac-n-cheese, and slightly spicey coleslaw."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When we proceeded to order our food, the waitress interrupted and told us that maybe we had ordered enough for now."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I have been coming here for several years and know that the staff and bartender would be there with my favorite drinks and dishes I like to eat and drink on any given night."], "output": "[['staff', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were a bit chatty so it took us a while to decide what to order, but when we made it abundantly clear we were ready (closed the menu, looked around for our waiter) he was slammed from the recent filling of the space."], "output": "[['menu', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Thankfully, a succinct menu leaves little to ponder--and, despite the high churn, burgers always arrive as specified."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["as of late though(maybe change of ownership)the food quality dropped with the menu change and the service got worse."], "output": "[['food', 'negative'], ['menu', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Be prepared to wait for a table - go to the upstairs bar and crack open a bottle of wine, or a nice bottle of Italian beer, and get to know everyone else waiting - who knows, you could be sitting with them for dinner!"], "output": "[['miscellaneous', 'neutral'], ['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Orange Valve is probably the best bar that I've been to in a while."], "output": "[['food', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When asked what the waitress recommended she just named a few things off the menu without saying why."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["You may as well just extend the bar into the restaurant since it has already penetrated it with loud music, loud voices, and a remarkable amount of cigarette smoke."], "output": "[['place', 'neutral'], ['ambience', 'negative'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere is nice, food is really worth it, especially for such prices, but service sucks: I first ordered 2 different martinis and never got the one I asked for; they brought the wrong dishes -although it was quick!- and then we had to ask for chopsticks to be able to eat our dishes."], "output": "[['ambience', 'positive'], ['food', 'positive'], ['price', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter, who was missing when we wanted to place our order, hovered over us throughout the meal, as if in a hurry to get us out of there."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When we finally got to order, we were told the bartender wasn't there, so we couldn't order any drinks."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I asked the captain to bring the food in separate bags and he loudly said, Oh, I guess you are not getting lucky tonight."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waitress was rather un-friendly, seemed annoyed that we didn't want appetizers and we waited 15 minutes before our wine arrived."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It says it on the menu and the servers explain it to you as soon as you sit down so I'm surprised by how many people on this site complain about the portion sizes."], "output": "[['menu', 'neutral'], ['staff', 'negative'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Faux Models/Waiters hustle around the tight spaced restaurant, while the bar is crowded with waiting patrons and dates enjoying a drink."], "output": "[['place', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I had to stare out waitress down to get our check and also we were charge."], "output": "[['staff', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Anyhow, there were a lot of Japanese people seated at the bar, eating chatting up the chefs, surely that's a good sign of authentic sushi."], "output": "[['service', 'neutral'], ['place', 'neutral'], ['staff', 'positive'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The servers are constantly in your face asking if you want another drink (mine was half full)."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Sam and the staff at Rialto were so accomodating and gave us a dinner event we will always remember."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I tried several dishes, while at dinner with friends, and was amazed to discover that even their Caesar Salad was completely lacking in flavor."], "output": "[['food', 'neutral'], ['ambience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Just finished a tasty jerked chicken dinner that was too pricey for the subpar service and good, but not great food."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter brought out three main courses, but the fourth wasn't ready so we had to wait for 10 minutes for the last dish to arrive, but they were very nice and gave us free red pepper hummus while we waited."], "output": "[['staff', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Outside the realm of steak, things aren't so certain: The pork chops can be a bit tough, lobster tails aren't the greatest and the special salad isn't."], "output": "[['miscellaneous', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["So we left, the menu looked decent but you have to go when you can get one of the 2 or 3 tables."], "output": "[['menu', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": [") While the location and ambiance sure are nice, I found the price a bit expensive considering the quality of the food was nothing spectacular."], "output": "[['place', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After dinner we ordered a hookah and after 20 minutes waitress comes by and tried to take it away because she claims our table is reserve for another group in 10 minute."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["of course i haven't mentioned the fact that we walked in on time for our reservation only to wait in the empty bar for over half an hour, being seated when we reminded the hostess that we were still waiting."], "output": "[['miscellaneous', 'neutral'], ['place', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We started ordering wine and, since we don't know much about it, we decided to let the waiter choose for us; we were pleased with his recommendation."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Don't ever bother - the drinks were awful, but it was the people who work there that really made this the worst experience at dining."], "output": "[['food', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Dominic will give you the ambience of the old times when they were all immigrants and good food was equivalent of good friends and unforgettable times."], "output": "[['ambience', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I dined there on a Wednesday night, the restaurant was practically empty, and we had to ask our waiter for everything, the menu, more water, the check, etc."], "output": "[['staff', 'negative'], ['menu', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food The key element to a proper British chip is fat, and the flabby, pale yellow specimens here come close to the ideal."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["i always get the apple pie, but the past two times i visited, the waiter burnt the pie while he was supposed to warm it up."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food ranges from okay to delicious and the service varies from great to poor."], "output": "[['food', 'positive'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu has been changed to a mostly unhealthy one, adding bacon even to the fish dishes (sometimes with no notice), so if youre looking for vegetarian or even just healthy seafood dishes, you wont find much."], "output": "[['menu', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When we mentioned that we had theatre tickets, the waiter made certain that our dishes were served promptly and courteously."], "output": "[['staff', 'positive'], ['food', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I have tolerated the fact that the place is packed on weekends, pricey and not that great drinks, often poor music on Saturdays, and bottle service that is slowly turning into a must."], "output": "[['place', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Server Sean Toussaint suggested specials and specialties worth the $$$ price."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The highlight of the night was the mayonaisse for my side of fries I received from one of the food runners, which is not good considering the bill was nearly $100."], "output": "[['food', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu is a bit different and all of the selections are pretty tasty."], "output": "[['menu', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["BTW, the prices are very affordable, which make the mediocer service tolerable."], "output": "[['price', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The basil pepper mojito was a little daunting in concept, but I was refreshed at the flavor."], "output": "[['food', 'negative'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Don't ask for a menu- take the trip with your waiter who eloquently (and vividly) describes dishes until he sees your eyes light up."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Basically traditional menu could have been boring and old-fashioned, but is instead updated enough to please modern palate: steaks, seafood, fish, poultry - ample portions (we took half home), seasoned with care and imagination."], "output": "[['menu', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My boyfriend took me to dinner for an early Valentine's Day, we showed up early for our reservation to meet an incredibly rude host who told us the bar was full, to just wait behind a rope."], "output": "[['miscellaneous', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere of the place is nice as well as the location, but I found food mediocre and too expensive for the quality offered."], "output": "[['ambience', 'positive'], ['place', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We decided to ask for our check for the wine we had and the waiter became completely annoyed at us!"], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Once just for late night drinks (they have a great drink menu) and then again for dinner."], "output": "[['menu', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The not-so-friendly-cigarette-reeking waiter asked if we had any questions then when we did ask, he rolled his eyes and covered his face with the menu to say something to a passing coworker."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["With dessert, the pre-theater is a great deal/meal."], "output": "[['food', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["it is a small take-out style restuarant but they have a few tables."], "output": "[['food', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After dining there twice, all the waiters will remember you and what you ordered the last time you were there!"], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Really great thin crust pizza - hot and fresh and fast, though you'll probably have to wait for a table."], "output": "[['food', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They served the salad and the main course together and didn't even bring the dessert menu."], "output": "[['food', 'neutral'], ['menu', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Granted, it's loud and sometimes obnoxious and it's such a pain to get seats for, but the the food is great."], "output": "[['miscellaneous', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Love the pizza here (although the slices aren't as fresh at 3am, but who's that picky when you're drunk), and there's plenty of other good stuff."], "output": "[['miscellaneous', 'negative'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We went ot Al di La a bit earlier than we usually go to dinner, mainly due to the fact that reservations are not accepted."], "output": "[['food', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Though the service is speedy be prepared to wait at least 20 minutes for the soup dumplings."], "output": "[['service', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the waitress was surly -- refused to bring sweetner for my tea!!"], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["With a chef from Liguria, Italy, authentic Neapolitan brick oven pizza and one of the most impressive Italian wine lists I've ever seen, this was the real deal!"], "output": "[['staff', 'neutral'], ['miscellaneous', 'positive'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The bartender informed me the place was full, and the wait was 30 minutes."], "output": "[['place', 'negative'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When we got there (6 women), we were not even allowed in when a staff member with a bad attitude wearing a suit told us that we absolutely needed a reservation (yes, we've gone from an artsy community to this)!"], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The wait staff didn't bother to refill my water until I had finish mine and was almost done with my husband's glass too."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["ran ~$30 ($12 for the taco, 8 for the rb, 10 fir the drink) plus tax and a very deserved tip."], "output": "[['food', 'neutral'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Great pizza and heros, without the variety and selection of that star wars-style canteena hipster crowd pizzeria on Bedford (Anna Maria's) but with 5X the flavor."], "output": "[['food', 'positive'], ['ambience', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were not rushed at all, and the manager comped drinks at the bar so that we would vacate our table for a birthday girl who had to wait."], "output": "[['staff', 'positive'], ['food', 'neutral'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["if you don't mind slow service and limited selections on the menu occasionally, then you might consider dining there."], "output": "[['service', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If you hate waiting for a table, then get take-out just around the corner next door."], "output": "[['service', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["my sister asked for iced tea twice and the waitress said they didn't have."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Bouley has done an excellent job creating this dining establishment with almost a museum sense, the artworks on the wall have a very Klimty feeling and the gold ceiling completes the rest of the experience."], "output": "[['ambience', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["First, we waited 40 minutes for our food, but after a thrity minute wait, the waitress asked me to clarify what I had ordered (I ordered off their menu, with no changes)."], "output": "[['food', 'neutral'], ['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Very pleasant atmosphere, not a quiet romantic dinner."], "output": "[['ambience', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter was nice once he got to us, it took about 5 minutes to get a glass of water and someone to get us started even though it was very slow."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When I requested a change to the non-smoking section, the waiter replied that there were no open tables."], "output": "[['staff', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Somewhat agree with the previous reviews about service and the long wait but once seated, the food is well worth it."], "output": "[['service', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The veal was nice and tender, but the flavors weren't exciting."], "output": "[['food', 'positive'], ['ambience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It is a nice room with a cool bar and you should stop in for a drink and Tapas but dinner was very weak!!!!"], "output": "[['place', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I would love the owner to consider hosting a 'tango bar' once - twice a week."], "output": "[['staff', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Just sit at the bar and sip some amazing Italian wines."], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The prices have gone up and some of good old standby entrees have disappeared from the menu."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["On the menu board posted outside - they got Passion Fruit Creme Brule."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Ask for a table closer to the bar than in back of the dining area; the drop ceiling the back compromises enjoying the soaring space of Guastavino's."], "output": "[['place', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When we got our bill the drinks were full priced and when we asked, our waitress said that there is no happy hour on the roof."], "output": "[['price', 'neutral'], ['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My only suggestion would be to avoid long waits for food by adding extra servers when there are large groups."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Coffee, treats, and the best of eerything."], "output": "[['food', 'neutral'], ['service', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["a drink or two went by, but as we slowly realized our wait had become an hour from the promised 20 min, the server noted upon our inquiry that they recognized and remembered us and would seat us soon- rolling eye look- matched by a tone protesting the uncouth annoyance."], "output": "[['food', 'neutral'], ['service', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The scene was sassy and cool, but i would never eat dinner here again."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The managers aren't snobby for wanting reservations -- it's a new restaurant and they're trying to manage the flow of diners."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food is decent, but for what the bill comes to, it's just not worth it."], "output": "[['food', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["However, it was a very long wait (over 45 min) and I confronted the hostess who stated that she could not find me at the bar and she had seated 6 other parties before me."], "output": "[['service', 'negative'], ['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They do have a large menu of things along the diner lines, and they go a little gourmet on the brunch omelette fixins/combos."], "output": "[['menu', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Despite reservations, we ended up waiting for 1hr+"], "output": "[['miscellaneous', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Charging full price for half pie toppings, and refusing delivery (1 block) for orders under $20."], "output": "[['price', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Noise level is high, and if you are a non smoker ask to be seated away from the bar."], "output": "[['ambience', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It was Au Bar meets 'Absolutely Fabulous' meets a Versace Outlet Sale."], "output": "[['place', 'neutral'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waitress recommended the coffee flan for dessert, and we didn't regret it."], "output": "[['staff', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The attention to detail whether it's decor or service or menu made us feel fortunate to be part of the Camino Sur dining experience."], "output": "[['ambience', 'positive'], ['service', 'positive'], ['menu', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter was apparently angry to have to be serving, because it took him 15 minutes to even bring water, let alone take a drink order (it was early on in the day and the restaurant was not even 50% full, so he was NOT busy)."], "output": "[['staff', 'negative'], ['service', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Overall, it is a nice place and if you don't mind possible attitude and the not-so-cheap prices, it is a great place to meet for coffee or drinks (they have a nice selection of that too!"], "output": "[['price', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We waited 15 minutes for a menu, another 20 for a tea, another 15 for an appetizer, then when the plates came out, the waitress had to ask me what I'd ordered."], "output": "[['menu', 'neutral'], ['food', 'neutral'], ['miscellaneous', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the dishes are a little too recherche and too trendy for their own good and there is not enough on the menu for vegetarians."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The pricing isn't quite clear and look out for that asterisk on the menu where they add on that extra 6-8 bucks."], "output": "[['price', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the menu looked great, but the food was the biggest disappointment i've had yet!"], "output": "[['menu', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My boyfriend and I went one Friday night to find that the place was empty except for one other table."], "output": "[['place', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Pink Pony's brunch is among the very best in the city!"], "output": "[['miscellaneous', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The environment is a touch loud (although the music's good), but the walls sport nifty vintage items, from license plates to pennants to movie posters."], "output": "[['ambience', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Only quibbles are so-so wine service, and while Prix-fixe is reasonable at $68, extra charges for additional dishes/tastings can be high."], "output": "[['service', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter was a real pro; knew a lot about ingredients and allowed us to take our time."], "output": "[['staff', 'positive'], ['ambience', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Fresh fish, tender milk fed veal and outrageous Veal Chops adorn their menu and special list."], "output": "[['food', 'positive'], ['menu', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Any sandwich or appetizer on the menu is delicious."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Expect to stand around for a while before one of the waiters desides that they can be bothered to actually get you to a seat."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Good value for money--especially the $7 lunch special for 2 courses."], "output": "[['price', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The staff were rude and rushed us through our meal, clearing plates and laying down dessert menus while others were still eating their main courses."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The place wasn't packed, but there was a bar scene and a few salsa dancers who strutted their stuff on the dancefloor."], "output": "[['place', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Suddenly the manager, came to our table yelling absolutely no way we can have a drink after dinner becuase he has tables waiting Just to be clear we spent over $70 and had 1 drink each, we used the table for about 1hour and 15 minutes."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Half way through the meal we did not have refills on our waters, even though our waiter passed the table many times and he never stopped to check on us or to ask if we were pleased with the entrees."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The two cons were the lack of information on the menus (they had just sushi roll names, with no description of their contents, printed in a bland format), and music selection, which didn't fit the ambiance."], "output": "[['menu', 'neutral'], ['ambience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My friend's entree wasn't presented as described in the menu, but we didn't want to add to the drama."], "output": "[['food', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["This is also when the waiter told us that half the menu was sold out."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["i thought the food was great but kind of expensive for that atmosphere, the tables were too close and it was too noisy."], "output": "[['food', 'positive'], ['ambience', 'positive'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I went here for a dinner with some relatives from out of town that I was eager to catch up with, but the noise level at this place made that really difficult!"], "output": "[['food', 'neutral'], ['ambience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The server was condescending and was unable to provide assistance with menu selections."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They later told us that our waiter had to fix the 'computer' - that was the reason he couldn't bring us our drinks."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Besides, they used to be much more accommodating when I used to request a jalebi paratha instad of a plain naan as part of the brunch price."], "output": "[['miscellaneous', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["A cold reception got even colder when we didn't have a reservation for a Tuesday night (the place was half empty)."], "output": "[['miscellaneous', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our server (after 4 reminders) finally got around to getting our cocktail orders during the meal (at a time when the establishment was not full)."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene Petite Abeille is ideal for a lazy lunch, a restorative brunch or light dinner."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After waiting an hour and a half, a delivery man - with heavily bleeding gums - told me not to worry, that my meal had been replaced with fresh food, and that my old order had been RE-SERVED to another customer."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene Quartino's airy dining room, wrapped in high windows, hinges around a trendy bar where regulars sip wine out of blunt tumblers while swapping stories--often in Italian."], "output": "[['miscellaneous', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were directed to a table by a member of staff, which we were then informed was reserved, and lost our seats at the bar, all this after spending upwards of $30 each on very expensive drinks over a two-hour period."], "output": "[['miscellaneous', 'negative'], ['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I never have to wait a long time to get my food, so it's a great place to go if you're really hungry and/or in a hurry."], "output": "[['service', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Good Italian spot, but should raise the bar on the food before some newcomers challenge its standings."], "output": "[['miscellaneous', 'positive'], ['place', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["went here late night after a a few drinks at my favorite watering spot and was amazed that a place which serves food till 4 can be so damned good."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Although when I went to eat dinner at Bombay Talkie on a crazy busy night, my waiter was extremely helpful through the menu, polite and polished."], "output": "[['food', 'neutral'], ['staff', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["What do you like more, completely addictive patties of greasy beef, or glasses of cheap refreshing beer to wash it down?"], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Yet, the place was emptyIts too bad because the food is authentic and price is very reasonable considering the location and the quality (eg."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the heroes are enough for lunch and dinner."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Then the waiter acted indignant when we called him out for bring us the wrong (later) vintage of wine we picked out."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Then, when we ordered from a regular menu, and told the waiter, that we are in a hurry to make the show, his response was So what do you want me to do ?"], "output": "[['menu', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food came out really quick and the service overall was not bad."], "output": "[['food', 'positive'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Every time I eat there I feel as if the chef and waitstaff have cooked, prepared and served a meal as if I am the only customer/guest."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After lunch, we sat at the bar and chatted with the bartender who was also very nice."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The place was nice and the bartenders were friendly, but the cocktail girl was rude, obnoxious, and over charging all of us."], "output": "[['place', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were seated promptly and brought rolls and water but then were made to wait much too long before our beverage order was taken and then much much too long before our waiter came back for a food order."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service was good and the price was decent but it wasn't enough to overcome the bland tasting food and the bland decor of the restaurant."], "output": "[['service', 'positive'], ['price', 'positive'], ['food', 'negative'], ['ambience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["But other comfort foods are also superb: Scallion pancakes are delectably crispy yet chewy, and chow fun with shredded pork and preserved cabbage (it's not on the menu) offers a tangy rice-noodles retake on the usual lo mein."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter was pleasant and I thought how bad could someone screw up basic Italian food?"], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["While the appetizers, entrees, and desserts arrived in a timely manner, our water glasses maintained consistently empty (at one point one of us had to ask for water twice!)"], "output": "[['food', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were first greeted by a very friendly hostess who asked if we had reservations - even though we didn't they were VERY accommodating - we sat at the bar and spoke to the VERY nice bartender who recommended a GREAT wine and gave us some brucetta to munch on while we waited."], "output": "[['miscellaneous', 'neutral'], ['staff', 'positive'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Wait staff is seemingly non-existant, and food servers are way too agressive - our food was thrown on the table, and even knocked a member of my party in the head with a plate with little acknowledgement."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I had reservations for 9:30pm and after waiting more that 50 mins and bunch of lies that you're next."], "output": "[['miscellaneous', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Arriba Arriba has much better food, margs, and atmosphere with slightly higher prices, but well worth it."], "output": "[['food', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Corner Bistro, despite the hoopla and critical praise, is nothing more than a burger joint with long lines."], "output": "[['food', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['food', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['service', 'negative'], ['place', 'negative'], ['miscellaneous', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Trish, our waitress was really great - the food was mediocre."], "output": "[['staff', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['menu', 'neutral'], ['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['place', 'positive'], ['ambience', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['service', 'negative'], ['ambience', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Although Sweet Melissa's food and pastries are very tasty, the unfriendly folks who work there sour the experience."], "output": "[['food', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["from drinks at the bar, to our perfect round table!"], "output": "[['place', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['food', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We sat in the garden out back, and the calm atmosphere with the waterfall rock wall on the side completed the setting."], "output": "[['place', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["To complain about waiting for a table, etc."], "output": "[['service', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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)."], "output": "[['miscellaneous', 'positive'], ['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Anyway the food was really good, the portions are not big however very filling and exceptionally good."], "output": "[['food', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['miscellaneous', 'neutral'], ['staff', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I found my dinner to be a bit on the heavy side and blamed the large portions."], "output": "[['food', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["While the environment is still fun and diverse, the food quality has been sliding lately."], "output": "[['ambience', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['service', 'negative'], ['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After all that, the waiter tried to backpedal saying its too hard to time the cooking of miso soup with the sushi bar offerings."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Good atmosphere, the service is so-so and there is a long wait if you don't have reservations."], "output": "[['ambience', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['food', 'positive'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We sat, missing a place setting for a while before the waitress came to ask if we wanted water and then ran away."], "output": "[['ambience', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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)."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['place', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Expect to get average food, a big bill and lots of attitude from the service."], "output": "[['food', 'neutral'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My roommate says she has had good food here at night, at the bar."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['miscellaneous', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['food', 'positive'], ['place', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Once in the oven (electric, mind you), he shifts pies every few seconds to attain nicely-charred, chewy crust perfection."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The restauarnt is Ok in terms of decor, but the food was really lacking - things were not cooked to order."], "output": "[['place', 'positive'], ['ambience', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food Surprisingly tasty Texas-style barbecue gives this place culinary flexibility beyond that of most wrap-and-burrito shacks."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["cause, I was bored by the club scene and too overdressed for the local bar."], "output": "[['miscellaneous', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['service', 'neutral'], ['miscellaneous', 'neutral'], ['food', 'negative'], ['menu', 'neutral'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Room is impressive, but service is slow and taste was almost like fast food."], "output": "[['place', 'positive'], ['service', 'negative'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We had to flag the waitress down to get a drink refill and waited an extrodinarily long time for our entrees."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Not the most beautiful environment, but the food is consistently delicious and the barbeque is fun and tasty."], "output": "[['ambience', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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 !"], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu ranged from standard (steak, duck and mussels-all fantastic) to curious (ostrich-awesome, and tartare-smoked not raw but still so good."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Hoegardden on tap is an added bonus if you're not drinking from the well versed wine menu."], "output": "[['miscellaneous', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Nothing beats being served platters of shrimp and wings and pitchers of beer, by the HOTTEST waitstaff in NY!!!!"], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Oh yeah, the food's just alright for the price."], "output": "[['food', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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!"], "output": "[['service', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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)."], "output": "[['staff', 'neutral'], ['miscellaneous', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Even with reservations, checking in, and a generally quiet night, the hostess forgot that we were there and gave our table to her friends."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Fresh, original, creative, absolutely delicious - Perhaps I would chose a table at this cozy Italian corner versus an NYC top 5?"], "output": "[['miscellaneous', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['place', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service was warm, but it took forever to get the check."], "output": "[['service', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['miscellaneous', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I had to ask the waiter a couple of times to clear our empty glasses."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I had the item that they forgot to put on the menu; some very tasty fish over jasmine rice with shrimp."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Waiter had to lean on my husband to give people next to us their food."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Go have a drink there the space is beautiful and buy an appetizer maybe, but pass on dinner, not well cooked and small portions."], "output": "[['place', 'positive'], ['food', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['ambience', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["This is authentic Japanese food - California roll is not on the menu."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Space aside, service is ok but the food is really well done."], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When you feel like eating again an hour later (portions are small) at least you won't feel as regretful about ordering take-out."], "output": "[['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["There was only one server on duty and we waited a while for menus."], "output": "[['staff', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['food', 'positive'], ['staff', 'negative'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The place is not fancy, but their food is wonderful."], "output": "[['place', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['miscellaneous', 'neutral'], ['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["' 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."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Had an OK dinner that was made better by the attention the owners pay to the patrons."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We had to wait 20 minutes before getting a beer, and we never got our burger order."], "output": "[['food', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": [") Service was good not great, waiters stood around,didn't ask how everything was."], "output": "[['service', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu had more selections, price points that fit all our budgets and a new Sushi menu that went over huge with the table."], "output": "[['menu', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['staff', 'positive'], ['food', 'neutral'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['staff', 'neutral'], ['place', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['food', 'positive'], ['menu', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["nice and cozy place but the soup was cold, the pizza was cold."], "output": "[['place', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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)."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Still, after all the fuss, the food makes you forget about the wait."], "output": "[['food', 'positive'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The wait staff was attentive without being overbearing, and our waiter gave thoughtful advice on dishes that would be suitable for the children."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Dim, candlelit dining room is accented by a funky star pointed bar and multi-colored ceiling lamps, with trendy upbeat music in the background."], "output": "[['place', 'neutral'], ['miscellaneous', 'positive'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The prices weren't bad though - dinner ended up at $80 with tip and we had a couple drinks as well."], "output": "[['price', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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!"], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["$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."], "output": "[['food', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our cocktails were ok but at ridiculous dance club prices."], "output": "[['food', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We (naturally) asked for a discount when the bill came, and our waitress disappeared for a moment and offered us."], "output": "[['price', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Luckily, I made reservations for our group or else it would have been a long wait."], "output": "[['miscellaneous', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The decor isn't the best and the place is very modest, but if you're around Ditmars Blvd."], "output": "[['ambience', 'negative'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food is great and I found it to be fresh and the prices are below to average compared to other Greek Restaurants."], "output": "[['food', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['place', 'neutral'], ['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['food', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['miscellaneous', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When we were finally seated about half an hour after my reservation, the waitress took her time taking our order."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['ambience', 'negative'], ['miscellaneous', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["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."], "output": "[['place', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The dessert was as good as the waiter said it would be."], "output": "[['food', 'positive'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food The menu is better suited to the snacking at the long bar than dining in the compact dining area."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After asking several different people find our waiter, he returned to say he couldn't find any wine and begged us to order sake instead."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When we asked if the waiter could put the lights back on, he said:we have this complaint every night but the owner thinks it's more 'Parisian'!"], "output": "[['staff', 'negative'], ['ambience', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["i have been waiting for 15 mn ( no food menu , no cocktail menu , no one even say hi to me )."], "output": "[['service', 'neutral'], ['menu', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Summary - good food which they rush you through and do everything to up your bill."], "output": "[['food', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The high light was the fondue, that we never got because again the server said the kitchen was too busy."], "output": "[['food', 'positive'], ['staff', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiters have been there for YEARS and they know their steak is amazing."], "output": "[['staff', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The deli-diner-soul-food menu, featuring everything from matzo balls to barbecued chicken and ribs to 10-ounce burgers, is available until late."], "output": "[['menu', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Very claustrophobic place so expect it to be really crowded during lunch."], "output": "[['place', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Not the best ambience and the service is sometimes just mediocre, but the quality of the food is incredible."], "output": "[['ambience', 'negative'], ['service', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I have to say that I've been there only during brunch time but the service even though slow, it was good."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service is friendly, if not the most prompt in the world, the food is great, and the prices, while not cheap, won't put your wallet out of commission."], "output": "[['service', 'positive'], ['food', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The portions are like a buffett for breakfast."], "output": "[['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Service is FAST so if you are dining, order entrees after receiving apps."], "output": "[['service', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Dinner is okay - not many vegetarian options, and the portions are small."], "output": "[['food', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When the manager was asked for things did imporve but 2 hours to get our meal."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Bread bar couldn't get anything right except water refills (good job to the water guy)."], "output": "[['place', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food Chef Tom Kearney (Blue Hill, Jean-Georges) presides over the contemporary, pared-down menu."], "output": "[['staff', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Service was slow and spotty; had to flag the waiter down many a time to get drink and food orders in."], "output": "[['service', 'negative'], ['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Although the place had an actual makeover not long ago, the food or chef needs to be changed."], "output": "[['place', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The place looks like the inside of a factory, with its steel drums, over-amped A/C and hard wooden benches, and the industrial decor seeps into overly streamlined menu and passionless food."], "output": "[['menu', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I had to try the sweet tea, which was served in a plastic cup at room temperture."], "output": "[['food', 'positive'], ['service', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I can only say that the soup dumplings are almost as good as Joe's Shanghai and some dishes I had (like Eight Spice appetizer) were tasty while others (Shanghai style Shumai) were less so."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were a large group and would highly recommend all the drinks and foodThe manager on duty was understanding that our friends were very late and held our reservation."], "output": "[['food', 'positive'], ['staff', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Start off with an expertly mixed cocktail or glass of wine at the beautiful bar."], "output": "[['food', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The wait staff is slow, full of attitude and forgettful--often taking 20 minutes to bring another round of food and drinks."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu contains both Japanese fusion and plain Italian dishes - everyone should be able to find something they like."], "output": "[['menu', 'neutral'], ['miscellaneous', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We waited half an hour just to get menus, and watched another table of 10 people leave because they had been ignored by the (single) waiter."], "output": "[['menu', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If you don't mind interacting with sour-puss employees, then by all means, enjoy the treats at Sweet Melissa."], "output": "[['staff', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene The consistent lines at this bustling Japanese tapas hot spot don't lie: Yokocho's fresh, reasonably priced comfort food and social atmosphere draw a youthful clientele of cultural natives and gaijin alike."], "output": "[['miscellaneous', 'neutral'], ['food', 'positive'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Upon reading the $44 prix fixe menu (a fair price for good food), we realized half of the Appetizers and Entrees required an additional supplement ranging from five dollars to $105!"], "output": "[['menu', 'neutral'], ['price', 'positive'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["There are times when there is a long wait at lunch so be safe and make a reservation."], "output": "[['service', 'negative'], ['food', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our meal was interrupted several times by the arguments between our waiter and the maitre 'd."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["for ANYONE to come and take our dessert order (we had previously seen our waitress going outside for a cigarette break and never coming back)."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["not only were we waiting for half an hour with reservations, once we got seated we waited another 15+ minutes for the waiter to come and take out drink menu."], "output": "[['service', 'neutral'], ['miscellaneous', 'neutral'], ['menu', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Evidently, our waiter went to the Mediterrean for our humus pita because it took about 25 minutes."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food There's no need to slump into a well-known comfort zone of teriyaki and udon."], "output": "[['ambience', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The outdoor patio is really nice in good weather, but what ambience the indoors possesses is negated by the noise and the crowds."], "output": "[['place', 'positive'], ['ambience', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I'm not going to trash the place simply because I had a bad experience there, but here's the facts: the food is very good, the portions are small-to-medium, and the prices are large."], "output": "[['place', 'negative'], ['food', 'positive'], ['miscellaneous', 'negative'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The bar was a disaster because there were no tables for anyone, and drinks took 20 minutes to receive."], "output": "[['place', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["For spending over $100 per person for dinner, i would think that the waiter would put my plate of food down for me instead of handing me my dish."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Called to make a reservation and b/c the man who answered was so nice decided to chance it."], "output": "[['miscellaneous', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I have told so many people to come here even my friend from Japan and we all love it, especially when we get the room for all of us to sit in our own little world eating tons of good sushi!"], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["it's one of the cheapest eats in the city and the food is not bad if you sit at the bar only - they have a decent chicken and/or beef tender tips but they cook with a lot of garlic so beware."], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Once we had our menus we were nearly assaulted by wait staff asking if we were ready to order."], "output": "[['menu', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The staff is constantly disappearing from the restaurant, making it impossible to get drink refills or to get the check."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They bought the same surly staff, it still took way too long for food, drink, ANY SERVICE and the food is still $ 12."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Overall, I would rather go to a chain coffee house up the street for the same priced coffee, but a much more relaxing atmosphere, and no one forgetting my order."], "output": "[['food', 'negative'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Cheese on the bottom, sauce on top - not too thick or doughy."], "output": "[['food', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I went for lunch yesterday and had a lovely time."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["yes as I sat at the table waiting just under 1 HOUR for my food, i was quite tempted to step across the road for a quick snack."], "output": "[['service', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Forget Brunch- there are usually people waiting outside, although the brunches are delish as well!"], "output": "[['service', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We didn't see the solitary waitress after seating ourself for over 10 minutes."], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Don't expect trendy atmosphere: room looks like it could have been designed in 1940s, but who cares - it's actually comfortable and inviting; with great food and unbeatable value, you can't go wrong."], "output": "[['ambience', 'negative'], ['food', 'positive'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The hostess was inefficiently seating people and disappeared for minutes at a time, letting the line grow to 15+ people waiting to put their names on the list."], "output": "[['staff', 'negative'], ['place', 'neutral'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The pizza is baked in a wood burning oven and the flavor is fantastic."], "output": "[['food', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The cultured wait staff were accommodating and helped explain and pronounce the items off the menu."], "output": "[['staff', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waitress was pleasant but slow, and the food is simply not good enough to be treated like a nuisance."], "output": "[['staff', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After 2 tries by the waiter to take it away (we hadn't even looked at it yet, we had full beers yet to drink), the manager approached and told us they needed the table for people with reservations."], "output": "[['staff', 'negative'], ['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Although we were seated right away and the waiter brought menus promptly as well as drink, he was almost never at our table despite being at the other tables right next to ours."], "output": "[['staff', 'positive'], ['menu', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter was conspicuously eyeing our table the entire meal and there was a lot of scurrying by the wait staff in general."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were rudely told by the waiter that chips are only available at the bar."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["AND, the waitstaff likes to lick its fingers when cutting cakes/pies and serves hot and cold drinks by holding the glass or cup around the brim/top."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It's very reasonably priced considering the size of portions."], "output": "[['price', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Disappointed in the selection on the restaurant week menu (which did not include any steak entrees) but impressed with the actual food- everything was very good- fresh and innovative- saffron risotto was not too powerful and the entrees were all good."], "output": "[['menu', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Its not cheap, it was $10 for a burger and fries, and when i was there, the waiter had dropped a FULL glass of coke on a patron, soaking her through!"], "output": "[['food', 'neutral'], ['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The specials of the day are the way to go."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We ended our great experience by having Gulab Jamun (dessert) recommended by the waiter."], "output": "[['food', 'positive'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Curries are another menu highlight, with several choices including Pa Nang with coconut milk, lemongrass leaves, onions and peppers, and Gang Paa with hot and spicy chili sauce."], "output": "[['menu', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The only downer was the fruit fondue desert from the prie fixe menu wasn't as good as it looked (the chocolate was runny), and the wait between our salad and main course was too long."], "output": "[['food', 'negative'], ['menu', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food was very good but the portions are pretty small, so while the prices are low, the place is not quite a bargain it seems to be."], "output": "[['food', 'positive'], ['miscellaneous', 'negative'], ['price', 'positive'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They lost our reservations and the manager quickly came over and apologized and then gave us a free round of drinks and free dessert."], "output": "[['miscellaneous', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service was unattentive and the only time she came over was to aggressively push drinks on us."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["From the overstuffed menu to the placemats advertising spectacularly festive drinks, to the comfy booths, the decor signals -- this is indeed your grandfather's diner and thank goodness for it."], "output": "[['place', 'positive'], ['ambience', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["For the price you pay, you get good quality and deliciously thin sliced beef."], "output": "[['price', 'neutral'], ['miscellaneous', 'positive'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waitress brought him a regular coke instead of a diet coke, and the salsa had OIL floating at the top."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene Cooing couples find some formality and open air up in the front room, while the subterranean back area offers hunkered-down seating for loungier dining."], "output": "[['miscellaneous', 'neutral'], ['ambience', 'positive'], ['place', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["This is definitely not a place to come for lunch because you can get the same food from a corner deli at half the price they charge here."], "output": "[['food', 'neutral'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["For example, the last time I was there the bartender seemed visibly irritated that I would ask him for a drink instead of the waitress."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food was pretty good, but a little flavorless and the portions very small, including dessert."], "output": "[['food', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I went for lunch and the staff does not welcome you upon entering."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I've had the ribeye, the salmon, and a burger/fries at the bar, and they were all exceptional."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I had the lentils and cous cous for lunch the next day because my friend and I had appetizers before our entrees-- portions are pretty decent for the price, and tasty to boot."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["At least you have the ambiance and lovely live piano musice being played for you while you wait."], "output": "[['ambience', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We asked for a side of dressing but the waiter told us that all the salads just had oil and vinegar so we should just use the oil and vinegar that was on the table."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Growling at us when we asked for water is one thing, but to just lie and make NO effort to satisfy, or apologize at these moderately high prices ($12."], "output": "[['food', 'neutral'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My advice: go the bathroom at home, and then go to Ginza for EXCELLENT sushi and service."], "output": "[['place', 'neutral'], ['food', 'positive'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our meal was capped of with the waiter rudely saying he needed the table for other customers."], "output": "[['food', 'neutral'], ['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["but the Server informed us that they wanted to make the soup their own and that she hopes we like it."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The hostess had us wait in the bar while our table was set up and we ordered what had to be the best mojitos in the city."], "output": "[['staff', 'neutral'], ['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["While the restaurant/space itself isn't so great (somewhat cramped cheesy interior, and the name implies its a burrito take-out place), the service and food outway its few cons."], "output": "[['place', 'negative'], ['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The music was a bit loud but the song selection was great, so we blew off desert and had another round of drinks at the bar."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Heartland is the best place in mid-town to grab a beer after work and meet the cuties that work in the building."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service was nice, although our food took longer than usual to arrive because it had been brought to the wrong table and accidently eaten."], "output": "[['service', 'positive'], ['food', 'negative'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The server was dutiful yet insincere, the brunch drinks above average."], "output": "[['staff', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It looks like a dive but serves up fresh authentic Mexican fare you won't normally find in your average Tex-Mex style restaraunt."], "output": "[['food', 'positive'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food was very good but portions were small."], "output": "[['food', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I prefer to sit at the bar as I don't have to listen to loud, boring conversations from the next table who always seem to be friends of the owner."], "output": "[['place', 'neutral'], ['miscellaneous', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I went there on my 2nd day in New York ever for a quick lunch and ended up staying and chatting with the owners wife and a waiter, Javi for two hours."], "output": "[['food', 'positive'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu offered unique options and my friends enjoyed their food, but my lentil avacado salad was not better or more interesting than the lunch counter at Saks and my John Dory was overcooked."], "output": "[['menu', 'positive'], ['food', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Just look at all those people waiting outside to feat in an unadorned space of cramped shared tables?"], "output": "[['service', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food was delicious, and the menu provided ample choices which suited all of the eaters in our party from the most daring to the most conservative."], "output": "[['food', 'positive'], ['menu', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My nice waitress even came running out of the restaurant to hand me a tiny box I had forgotten on the table."], "output": "[['staff', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["While waiting for a table, tried to get a drink from a bartender who seemed more interested in arguing with his waiters."], "output": "[['service', 'neutral'], ['miscellaneous', 'neutral'], ['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The chef insisted that the meat was cooked properly!?"], "output": "[['staff', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["warm orangey glow, nice old mexican prints, wee bar that my bf and i vowed to go back and linger at."], "output": "[['miscellaneous', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I looked for months for a reasonably priced place that could accommodate about 40 people for a wedding rehearsal dinner on a Friday night."], "output": "[['price', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were coldly greeted by a hostess and wait staff who, in spite of our reservation, did not want to seat any of us, including the elderly, until our entire party had arrived."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I had dinner here with a few friends recently, and while I must admit that the food and service was okay, the prices simply did not match the environment and cuisine."], "output": "[['food', 'positive'], ['service', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The birthday girl's dessert included a candle the staff came by with birthday wishes."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our meals were a moderate portion and they weren't too spicy."], "output": "[['food', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Although she was obviously busy, she was helpful in describing certain items on the menu and suggested a duck dish that was out of this world."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We had no problems with our resevations and found the service and the meal well worth a wait, had we run into one."], "output": "[['service', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The place was a bit noisy, but sitting on the edge of the restaurant helped, and although the portions were small, w/ an appetizer it was the perfect amount of food."], "output": "[['miscellaneous', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Although the sushi was fresh, I was disappointed with the size of the portions for the price."], "output": "[['food', 'positive'], ['miscellaneous', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The chef will not alter any of the three tasting menus."], "output": "[['staff', 'negative'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Sure the food was - as always - very good, but we were quite outrageous about the waitress."], "output": "[['food', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After our disappointing meal and terrible service we asked to speak to the manager (who was sitting alone having a glass of wine) when we were told he was too busy to speak to us!"], "output": "[['service', 'negative'], ['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When I asked to speak to a manager, I was sent to voicemail, and I still haven't received a callback."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Yesterday they had numerous bartenders as well as servers and the place wasn't packed and it still took 1/2 an hour to make a martini."], "output": "[['staff', 'positive'], ['place', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter handed us menus consisting of about 7 entrees, and after telling us the specials, informed us that there was no chicken."], "output": "[['staff', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Well, no secret that a brunch here on Saturday or Sunday will be a long wait - but once you bite into those pancakes, it will have been worth every minute."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We had to remind the waiter to pour our wine (white) and then he didn't show us the label."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["same atmosphere but food was better before years ago- octopus was like chewing a rubber tire- dumplings tasted artificial."], "output": "[['ambience', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food and beer make up for it, but it would be nice if the staff weren't such buzz kills!"], "output": "[['food', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiters seemed annoyed we all ordered the restaurant week menu and were going to cut into their tips."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["my waitress was unable to answer my questions about the menu, and forgot to put in my order."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I highly recommend the potato and cheese pierogis and the polish kielbasa entreesbut the real stars on the menu are the sides."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter was pretty much non-existent and when he did come to our table he practically tossed our plates and wine glasses in front of us."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Although my waiter had about as much personality as a dead fish, I loved the great solid food and would definately go back."], "output": "[['staff', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere was so fun that we decided to have another cocktail at the bar and enjoy the scene."], "output": "[['ambience', 'positive'], ['food', 'neutral'], ['place', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Dinner's nothing to scream about (although there are a few winners on the menu), but solid margaritas and appetizers are well-suited for a summer evening."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I was disappointed to hear another waiter (or it could've been the owner) was reading completely different specials (most of which I would've wanted to try if I didn't overhear at the end of our meal) to the table next to us."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Alongside the USDA prime dry-cut steaks, the menu features standard steakhouse fare: appetizers like shrimp cocktail, fresh oysters and clams, an array of salads, soups, pastas and vegetable sides, and non-steak entrees like lamb, veal and pork chops, lobster and more."], "output": "[['food', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["But the price tag was high, and the food was comparable to a Las Vegas buffet for flavor and quality."], "output": "[['price', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Forget about the staff and go for the food and pleasant, if a bit cramped Lancaster, Pennsylvania like decor for comfort."], "output": "[['staff', 'negative'], ['food', 'positive'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I mean Pho Viet Huong is at a good location, but face it, the broth is cloudy and oily -they're supposed to constantly dump the top layer off of the Pho broth, service is ran with attitude who cares about you, I have plenty of other customers to make money off of."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The lengthy menu includes the likes of mee krob (glass noodles with shrimp, chicken and pork in plum sauce), nur-yang-num-tok (barbecued flank steak served with a spicy sauce), pork with chili and basil leaves and spicy, bean curd coconut milk soup."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food The fun factor is high on the menu of experimental, multi-ethnic shared plates."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Although it lacks the patina of places like Peter Luger's and Sparks, it still has a steakhouse's telltale wood paneling, chalkboard specials and decorative wine bottles."], "output": "[['staff', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["This place is pricey, and yes, the food is worth it; but the service makes you feel like you should be paying a quater of the price."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food is just ok, not really memorable and not what you expect for the price but I guess the atmosphere is what you pay for."], "output": "[['food', 'positive'], ['price', 'negative'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food was good but for the prices, it was definitely not worth it."], "output": "[['food', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu is varied but I think it is the chicken which they do best as."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We waited over 30 minutes to get our drinks (which were brought over my the manager) and we could not find anyhting that looked interesting on the menu."], "output": "[['food', 'neutral'], ['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I'm totally into the space-age vibe of this place, but I wish they had more tables to sit down at."], "output": "[['ambience', 'negative'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["While the food was good (certainly no Il Mulino) the service was horrendous."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the regular prices looked pretty expensive (~$15 per appetizer, ~$35 per entre) so the restaurant week menu (at $35pp) seemed like a sweet deal."], "output": "[['price', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Went there a few months ago, and while the food was really good, and I was ready for it to be pricey, the one thing that bothered me was the waiter was standing in a corner watching us eat."], "output": "[['food', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I came in for brunch with my parents on Saturday and the place was packed."], "output": "[['food', 'neutral'], ['miscellaneous', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["While the space is exceptionally small and the seating can be uncomfortable, the food is well worth the few inconveniences."], "output": "[['place', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were planning to get dessert but the waitress basically through the bill at us before we had a chance to order."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter took my boyfriend's order, snatched away the menus and stormed away from the table without even looking at me."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["This is definitely a special occasion spot, unless you don't mind a hefty bill, but rest assured that either way, it's well worth it."], "output": "[['miscellaneous', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Went early with reservation, place was empty, and they squeezed our two top in between other diners at a banquette."], "output": "[['miscellaneous', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Food and service were very good but prices were a bit high for the portions."], "output": "[['food', 'positive'], ['service', 'positive'], ['price', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The new fall menu has a black cod with miso broth so good I thought I was at Nobu."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Went for lunch the bartenders were great, also they had a DJ playing music during the day, there was a Huge screen tv playing music videos and a bunch of other tvs with all the sports you could look at."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["and don't be ashamed to ask for more during the hour long wait for your entrees."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The only drawback is that the tiny cafe can only hold so many people with even less tables available, so if you are lucky enough to score a table, stay put with a date and some wine, because no place nearby can serve so much romance with such quality eats."], "output": "[['place', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The candle-lit bar is the destination of trendy wine-sippers and snackers, and the rustic-chic dining room, with brick arches that open onto a tight sidewalk terrazza, is booked weeks in advance."], "output": "[['place', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I used to live in Japan, and have had some pretty good raw fish, but I was blown away by the Chef's tasting plate, which includes 6 appetizers including a stunning octopus portion and some incredible sashimi."], "output": "[['food', 'positive'], ['staff', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I liked the place and the people, but we really went to have dinner no appetizers as the whole dinner."], "output": "[['place', 'positive'], ['miscellaneous', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter was a bit weird as well, but the lounge area looked like a nice place to get a drink after work."], "output": "[['staff', 'negative'], ['place', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service was really bad at several points our waiter would just leave for a cigarette for like 10 minutes while we waited for him to get us another drink or even pay the bill."], "output": "[['service', 'negative'], ['staff', 'negative'], ['food', 'neutral'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I took 8 clients to lunch and was appaled by the overall service."], "output": "[['food', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["While the hostess claimed to have lost my reservation, we were there early enough to only have to wait about 10 minutes to seat our party of seven."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["deserts were slow to order as waiters passed us twice, even with the menus closed."], "output": "[['food', 'negative'], ['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["12/24/03 Dinner was ok, service was so- so,the worst part was the hostess - we made reservations a month before Christmas Eve for three people, you would think the table would be large enough for all three of us."], "output": "[['food', 'positive'], ['service', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["So if he can't find fresh-good product, he'll remove a dish from the menu which I think is fantastic."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["There are some reviews complaining about the menu but I had the same dish the first three times that I was there - and any specials that I have had have been excellent."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The final blow came when the waitress scorned our 16% tip for the meal."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Recommend eating at the bar for an intimate, relaxed dinner."], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When the food arrived, the portions were really small, and didn't really reflect the awesome descriptions on the menu."], "output": "[['food', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We ordered the Tuna a la carte and Wild Salmon and chicken breast on the Prix Fixe."], "output": "[['food', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["oh, and if you're there for drinks at 3:30 on a weekday afternoon, when the place is empty - and ask for a bread basket - they'll charge you $6."], "output": "[['food', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Only problem was - an older gentleman (well-dressed but a little enebriated) chose to sit down right next to me - despite the fact that all 15 other seats were free - order himself a martini, and then describe how dry and dissapointing the burger was when he ordered it a few days ago."], "output": "[['staff', 'negative'], ['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["You can't fault them for serving up some pretty good food, even if it's a bit overpriced."], "output": "[['service', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We waited at the bar for only 10 minutes (we had a reservation) - can't complain about that, the restaurant was full and I enjoyed the lively atmosphere and music."], "output": "[['place', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Bartender made a bad drink for me and I sent it back and was charged for it."], "output": "[['staff', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The bar has a large selection of beers on tap,bottles or cans."], "output": "[['place', 'neutral'], ['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Waited 30 min for a brick they call bread and water, another hour for food (tiiiiiiiny portions)."], "output": "[['food', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My friends and I dropped by on a Sunday, and there was absolutely NO SERVICE (the supposed only female bartender even told us there was no one else but her, and given that there were people in there waiting to dine and drink, that was ridicoulas!"], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu was in Italian- might as well have been in Esperanto;that put us at the mercy of the waiter for recommendations."], "output": "[['menu', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We had to flag down the waiter even to refill water glasses!"], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Waiter spilled a decent amount of water on my friend's plate -and then walked away - didn't remove the plate!"], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["our waiter noticed it was my bday w/o me saying, and brought me cake w/ candles."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The decor is not special at all but their food and amazing prices make up for it."], "output": "[['ambience', 'negative'], ['food', 'positive'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Rather you are paying rock bottom price for a meal that could cost you triple any where else."], "output": "[['price', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Granted we were just the girls, but this would also be a great date spot b/c the ambiance is chic and bustling yet you can also hear the conversation at your own table rather than a loud din or worse, someone else's conversation."], "output": "[['miscellaneous', 'positive'], ['ambience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The portions are big so you can split an appetizer."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["In the front bar, boisterous neighbors and friends share bottles of wine; the large dining room, with its lovely painted ceiling and oversized portrait of a portly chef, is the destination for serious eating."], "output": "[['place', 'neutral'], ['food', 'neutral'], ['ambience', 'positive'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The calamari, the penne and vodka sauce, the friendly service the parking and the open area kitchen to see all the action in the making!"], "output": "[['food', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I've never been able to find a lunch place in the midtown with the same quality and service, until now."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["staff is still working out their kinks and learning about the menu but no real complaints."], "output": "[['staff', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It was worth the wait , an hour, without a reservation, for an out of this world meal."], "output": "[['service', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Among us, we ordered a large sampling of the menu, and everyone thoroughly enjoyed their meal."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Service was unbelievably on target down to the smallest detail; our waiter invited us to sample a new desert under consideration for their menu and a new line of ice wines."], "output": "[['service', 'positive'], ['staff', 'positive'], ['menu', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["In addition, the manager refused to come over to apologize - but told the waitress to offer us TWO desserts on the house- when there were FOUR people dining."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter disappeared after dropping off the food so I had no choice but to eat it as is."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I did not find the wait staff to rude at all, how involved do you really want them in your meal right?"], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Half way through the meal my husband had to go to the bar to order his own beer, since the server never came back."], "output": "[['food', 'neutral'], ['place', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["To the amusement of our server, I wrote everything down, lest I forget a single morsel (about 21 different dishes)."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Order the porterhouse and they put it between you and you kind of eat family style at a wooden table."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It's just a diner, but three decent hearty lunches for 12 bucks?"], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I ordered a medium Cub burger and it came out well done, not that my server would have noticed since we didn't see her again until she brought the check."], "output": "[['staff', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The bar gets out of control busy due to it's proximity to Fordham University--but the Fordham kids are cool, so it's alright!"], "output": "[['place', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter spent a long time telling us about the menu (and more about his own life history in the process."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Comfort standbys--including bacon-wrapped meat loaf and barbecued ribs, and upscaled interpretations--like tuna club made with wasabi mayo, share space with brunch favorites (Belgian waffles, fluffy buttermilk pancakes and wrecked eggs, or tofu)."], "output": "[['ambience', 'positive'], ['food', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["In other words, conserative types craving simpler things like grilled chicken or salmon probably would not appreciate Tabla's distinctive and unusual menu."], "output": "[['food', 'neutral'], ['menu', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I write that in quotes becuase iceberg lettuce, stale Pepperidge Farm croutons and bottled dressing does not a salad make."], "output": "[['food', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu sticks to standard Italian dishes--linguine with clam sauce, chicken parmigiana, and fettuccine Alfredo--but the reasonable prices add to the charm."], "output": "[['menu', 'neutral'], ['food', 'neutral'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter nearly yelled at me when I asked for more water."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When I asked for a particular drink, the waitress gave me dirty look and annoyed b/c they didn't know what it was."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["WAY OVER PRICED , HAD MUCH BETTER MEALS FOR JUST OVER HALF THE PRICE IN PLACES JUST AS NICE."], "output": "[['price', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["then, the waiter had nerve to charge me for the fruit salad and bloody mary (which we didn't drink) that came with the omelet (brunch special)."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I had the waiters bring back so much meat that that asked me if I wanted Flank steak for dessert."], "output": "[['staff', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["This was followed by various wacky hijinks: overly sweet foie de gras, lack of extra ginger/soy sauce, minute portions even for sushi, appetizers arriving at different times."], "output": "[['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter kept pestering us for our order even though we were among the last diners."], "output": "[['staff', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Waiter suggests a beer, and offers to bring a small glass, to taste it and see if I like it, before I even order the beer!"], "output": "[['staff', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I ordered dessert and it was they gave me the wrong flavor of ice cream."], "output": "[['food', 'neutral'], ['ambience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We started at the bar with a nice bottle of wine, which was priced fairly and sampled several different cheeses."], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["A 3 course-meal took 2 1/2 hours, including 20 - 30 minutes waiting to get the check after dessert."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["And the room is VERY noisy, but I suppose that's because everyone is having a good time."], "output": "[['place', 'negative'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We fully relied on our very capable waiter for choices of the menu and we were not disappointed."], "output": "[['staff', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food was abundant and good but wasn't worth the unpleasant wait."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["perhaps the place is better after the theatre crowd is gone but we were in the midst of it and it wasn't a very enjoyable experience."], "output": "[['place', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter didn't know the menu, didn't bring more than one item at a time, and put some orders in twice with the kitchen."], "output": "[['staff', 'negative'], ['menu', 'neutral'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene You won't blink twice at the restaurant's spartan decor: As the packed crowds and critics' praises wallpapering the front wall agree, this longtime local favorite is truly one of the area's most exquisite finds."], "output": "[['miscellaneous', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The rolls are tiny so you have to order more anyway and they will often get your order wrong if you stray from the menu."], "output": "[['food', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Into our appetizer, an adjacent table became available, and we asked if we could use it, but the waiter said it most likely was being used."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service has always been outstanding and even when we didn't have a reservation they worked something out, where I agreed to keep our meal to just eating."], "output": "[['service', 'positive'], ['miscellaneous', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We reserved the downstair lounge for private parties and the price was fairly reasonable."], "output": "[['place', 'neutral'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["To start with - the maitre'd forgot our reservation and then when it came time to sit us down - he told us we only had an hour."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["In Short The bi-level dining room, which resembles a bamboo-thatched hut, is a brightly-lit, wide-open space with high ceilings and laminated depictions of Indian village life."], "output": "[['food', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["At least the entertainment was free, as we were able to witness one customer wooing a waitress, and another being drenched in milk."], "output": "[['ambience', 'positive'], ['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The table next to us recommended that share because the portions are big(we split two entrees)The food was so good I wish that there was some left over to take home for the next day."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were immediately seated (the restaurant was no where close to being packed, surprise, surprise) There are very few selections on the menu and the food is not that great and the dining experience at Butter is completely overrated."], "output": "[['menu', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service was good, but not excellent; however, the waiter was initially huffy with me when my guest was only 5 minutes late, threatening to make me move!"], "output": "[['service', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When our entrees came, at least 3 or 4 waiters / waitresses came by at different times to wish us bon apetit."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the server absolutely did not know what in the world he was talking about when we aske questios about the menu, and he barely spoke English."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Warning Service is decent, but it takes forever to get the check."], "output": "[['service', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Good food, but bad service."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiters actually roll their eyes when you order something, as if you are imposing on them by ordering food."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter had started to circle around our table like a shark after our 2nd dish, taking out plates when we were not even done."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My reservation for 2 was during lunch and it seemed that because I was literally 2 minutes late, the hostess felt the need to seat every party before mine."], "output": "[['miscellaneous', 'neutral'], ['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I can't even remember if they serve anything else -- a busy hole in the wall sized place and atmosphere."], "output": "[['place', 'negative'], ['ambience', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We had to wait an hour before our food was served, then another hour inbetween courses, all the while whilst the staff were naughtily hiding in an attempt to avoid our 'where's out food?'"], "output": "[['service', 'neutral'], ['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Kitchen is only separated from its patrons by glass is immaculate and the service is undeniable heartfelt."], "output": "[['place', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It was also very reasonably priced, we had 4 bottles of wine, appetizers, dinner, and coffee and our bill was just over 50 per person."], "output": "[['price', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["While I would agree with the initial review that Asia de Cuba isn't really Asian or Cuban in its decor, the food was a nice fusion."], "output": "[['ambience', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It took a long time for the waiter to bring the check and we had to flag him down."], "output": "[['staff', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Only drawback is the sound level - quite a loud space downstairs - and that might be accounted for with their trendy bar and right off Times Square."], "output": "[['food', 'negative'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu is Prix Fixe, so be prepared to spend at least $60 per person, but it is Well worth itsuperb food."], "output": "[['menu', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Went the next day for lunch - menu too pricey for lunch and the waiter was the WORST !!"], "output": "[['miscellaneous', 'neutral'], ['menu', 'negative'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food It's billed as Asian street food, but since the menu is a creative collaboration between expert chefs Vongerichten and Gray Kunz, dishes show unmistakable finesse."], "output": "[['food', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Al Di La serves up an impressive selection of options ranging from meditarranean fish to rabbit to to duck to pasta."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["when someone from our table of 5 asked the waitress for refill on water, she comes back and fills only that person's glass, leaving the rest of the table with almost empty glasses."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We told the manager it was not worth a few appetizers to be treated that way and left."], "output": "[['staff', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food is decent, but WAY TOO SMALL of portions for what you pay for."], "output": "[['food', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We would have to flag down the bored looking wait staff to refill our tea."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Watch out for the overworked, stressed out waitress who dumps tapa dishes on the table and leaves w/out announcing what it is."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I would not recommend this place until they get a new staff that can complement the food."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food was pretty good, but due to our large size (~16) the manager asked us to limit our appetizers to just 3 selections b/c he didn't want to overburden his cooks."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waitress seemed less than happy about the prix fixe dinner choices and at one point said, Do you really need to hear the specials?"], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["On the table you will also find individual bottles of fine imported olive oil which we put on the bread-fantastic!"], "output": "[['miscellaneous', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service was good enough for a crowded place."], "output": "[['service', 'positive'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Then the staff behind the buffett just haven't gotten their groove yet, so you order your food and wait five minutes while it sits behind the glass on a plate, getting cold."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They are negligent in alerting customers when an order is ready - you could end up waiting for half an hour while your food is sitting on their counter getting cold."], "output": "[['service', 'neutral'], ['food', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The bar tender didn't know where the tea was, waiters started making the drinks if the bar tender wasn't around."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It took forever to seat us even though the restaurant was almost completely empty, then we had to ask to be waited on, it took another 15 minutes to get our drinks, and then another 30 minutes to get our salad and then even more time to get our pizza and then our bill."], "output": "[['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitress/hostess seemed a bit sad when we told her we weren't ordering dessert (those arepas are deceptively filling!"], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Nice decor and an extensive menu lured me in, but the horrible service and rude staff drove me out."], "output": "[['menu', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["As expected, the beer selection is perfectly in synch with the menu."], "output": "[['miscellaneous', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["yes Shrimp not lobster (those are 6 Lbs) try the exotic Fish not on the menu and a must have is the Flower stuffed with lump crab meat."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The House salad is big enough to split, The Fried Calamari is some of the best I ever ate, the bowties broccoli, broccoli rabe, square slices, broiled filet of sole, clam sauce."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The only problem my party found was that when people asked for knives and forks (there were only chopsticks on the table) the waitress laughed at them."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I have a litany of complaints -- being over-charged for wine that I didn't order, shady waiters, so-so food that arrived at the table luke warm, main course portion sizes barely large enough to be appetizer sizes, lack of fabulosity that Mr."], "output": "[['food', 'negative'], ['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Unlike the reviewer before me, what made me KEEP going back was the great reception I received from the bouncers and I needed several cocktails to endure the waitstaff."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were the only two people sitting out front and the waiter was unable to provide us with attentive service OR our dinner."], "output": "[['service', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We finally flagged down another server who brought us more to drink, and then they took forever with the check."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitress forgot our coffee, took forever to take our order, never checked in with us after the food came and when we were done, didn't bring us the check for the longest time."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Wish the Greenwich street location had more seating like their 2nd Ave location, because one invariably leaves it smelling of grease."], "output": "[['place', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Aside from that, the service is adequate (visible, and will help you if you ask, but lack initiative), and the food, well, could be a lot worse."], "output": "[['service', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The wait staff was better the second time around and our water glasses were always full."], "output": "[['staff', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I highly suggest you make reservations, as wait times can be extremely long."], "output": "[['miscellaneous', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["For a restaurant with such limited menu and wine list, each dish should better be darn good."], "output": "[['menu', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Waitress kept trying to get us to order more drinks while apologizing but wouldn't even bring bread to keep us from starving."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["You must think that the quality is poor for them to sell it for such a low price."], "output": "[['miscellaneous', 'negative'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Both appetizers arrived cold/luke-warm, which we had to send back, only to have the waiter tell us that one was supposed to be cold."], "output": "[['food', 'negative'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food Consulting Chef Douglas Rodriguez's forte is blending the diversity of traditional Latin cuisine with modern culinary chic: A celery sorbet cools the spicy-citrus bite of lobster; shrimp seviche and crunchy green plantains coat thick, juicy halibut resting on sweet plantain hash; and tart tomato escabeche moistens a chewy skirt steak."], "output": "[['food', 'positive'], ['staff', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The perfect meal; delux combo raw bar as an appetizer, King crab as your entree."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The place was not crowded for dinner on a Sunday night at 8:30pm."], "output": "[['place', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Waiter dropped check on table while I was in the middle of handing my wife her anniversary present."], "output": "[['staff', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Meat wasn't fall-off-the bone (a sign of over-cooking) but was tender and had deep flavor."], "output": "[['food', 'negative'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter came back after I had finished my appetizer to correct himself and let me know that it wasn't vegetarian (chicken stock) after all."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Food took over an hour despite at least two chasers, we had to track the server down to get extra drinks, the manager seemed to try and deliberately mislead us about the reason behind the delay and in the end the food was poor."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiters are nice, but weren't particularly good - waited forever to order and resented not being told that my dinner companion and I had ordered enough for a table of 10 (given the size of the sushi)."], "output": "[['staff', 'positive'], ['food', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The place is very loud, good for drinks by the bar not to eat and yell."], "output": "[['place', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene Less trendy than Plan Eat Thailand, less crowded than Veracruz and infinitely more charming is Bean, a Mexican spot on Bedford Avenue's college-town-like stretch."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["50, I got the Paella Marinera which was beyond filling in itself, but before it even came, the waitstaff provided more than ample appetizers for my group that by the time that the meal came to us, we were so stuffed, we could barely finish up the meal."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I thought the bar was fair in terms of decor, but how long do you have wait at the bar before a bartender with an attitude (he wasn't rude, but not friendly) makes you an awful drink, but food was delightful and music light and tasty as well."], "output": "[['ambience', 'positive'], ['staff', 'negative'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food A good way to judge a Thai spot is by its green curry: The all-Thai staff here fashions it spicy and smooth, filled to bursting with meat and thin-sliced bamboo shoots."], "output": "[['food', 'neutral'], ['staff', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["maybe its the cost of top ingredients but 17."], "output": "[['price', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Their menu is limited, they serve miniscule omelettes that may be suitable for a child (with what seems like a teaspoon of stuffing) with a salad (have to pay even more for fries) for $10- which was poorly washed and there were bits of soil all over it!!"], "output": "[['menu', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the place looks cool, but the food is not really that good."], "output": "[['place', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Spend your time sitting on one of their couches enjoying a cocktail from the bar."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I will have to say the food was good and the chance to sample wines not often found in other restaurants was a positive but the abyssmal service left a bad taste."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I don't know why people complain about the service - our waiter brought our drinks and food out promptly."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["And the service is unbearable - I waited for ages to get my drink, got the wrong sushi order, and had my appetizer whisked away prematurely."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Once they took our wine order, it took 45 minutes for it to arrive, even though the waiter was talking to a patron next to us."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["In Short Though it's more of a takeout and delivery operation than a sit-down restaurant, Risotteria does offer eight small tables for those who want to savor their risotto hot off the stove."], "output": "[['service', 'neutral'], ['place', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The space was unique (even though looking out the skylight windows on a tenament was a bit odd) and the service, happily, was fine."], "output": "[['place', 'positive'], ['food', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food and cocktails at SushiSamba were very good; however the seating is so tight and uncomfortable and the service so rushed that I will probably never go back."], "output": "[['food', 'positive'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Prompt local delivery, minimal seating and counter space."], "output": "[['service', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The kitchen turns out a long list of American bar food staples, like burgers and fries."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When I went back to the hostess (yes it was past the time we had for our original reservation) - she said that it was fine to get seated but we needed to leave in an hour."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["One price for dinner left for no surprises."], "output": "[['price', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The portions are small but being that the food was so good makes up for that."], "output": "[['miscellaneous', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The restaurant has a somewhat unique decor, with portrait of the owner meditating and books about meditation."], "output": "[['ambience', 'positive'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["This is one of my first dining experiences in NYC when I first moved here 10 years ago, and although Hudson Corner is consistently good, it has gone downhill over the years in both food quality and service!"], "output": "[['miscellaneous', 'neutral'], ['food', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Food turned out to be descent, but the waitress disappeared from the moment we placed the order untill she came back with the check."], "output": "[['food', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We asked for more coffee, water and couldn't even get that from our server."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We made a reservation for 5:30pm (20 people) and people were still arriving at 5:45 (over half the group was there) when the manager came over and literally yelled at us for not being on time saying it was a busy time for him, when in fact there were several empty tables throughout the restaurant."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Crystal Ballroom was closed for a private party, so we couldn't even enjoy the decor."], "output": "[['miscellaneous', 'neutral'], ['ambience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Even as a stranger, the service at the bar was excellent as was the wait staff who continuously checked back to see if I was okay while waiting for my party."], "output": "[['service', 'positive'], ['place', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter kept coming up and asking to take our plates while we were still eating and the manager stood and stared at us through half our meal!"], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service was fine, out appitizers took forever to come out, and then they dumped the rest of the food on us, without giving us a chance to enjoy our appitizers."], "output": "[['service', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Great deal for lunch; came to something like $11 with tip and tax!"], "output": "[['food', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The ambience was nice, but service wasn't so great."], "output": "[['ambience', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The restaurant was recently taken over by new managment and, having eaten there under the prior management, I can say that the quality of the dishes has improved."], "output": "[['staff', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food Pies come in three sizes, from a petite five inches (perfect for the solo diner) up to 10."], "output": "[['food', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I'd recommend going across the street to Recharge for some healthy burgers and fries before hitting the bar."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["But when the bartender messes up the returned drinks something is wrong."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Order ended up being double the price of a normal lunch."], "output": "[['price', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitress lost some points for not refilling our champagne glasses."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Although the homefried potatoes were not worth the plate space, next time I'll ask to substitute a nice salad."], "output": "[['place', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Service was good except the waitress brought over the check before I asked her."], "output": "[['service', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter (someone I know has been working there since it was just LCB) POURED MY WINE FROM THE DIRTY GLASS INTO A CLEAN ONE AND SERVED IT TO ME!"], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["In addition, they lack basic ammenities like a toaster, and the decor was shabby, at best."], "output": "[['food', 'neutral'], ['ambience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The ambience is extremely romantic, even if you get seated upstairs."], "output": "[['ambience', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The only blemish was our waitress, who left us with empty drinks for quite a long time."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The steaks are just as good, with an assortment of tasty side dishes that make Peter Luger's menu look like the slip in a fortune cookie."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Theme and actors are kinda cool but you are charged some entertainment fee on top of the expensive food and drinks."], "output": "[['miscellaneous', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Service is not what one would expect from a joint in this price category."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitress took forever to take our order, we waited almost an hour for our appetizers, and then she asked us whether she even put the order in -- as if we would even know."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["since it looks like everyone's already familiar with the rude hostess and long wait for a table (even with a reservation), i'll skip that part."], "output": "[['staff', 'negative'], ['service', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Waiters and busboys were taking our water glasses and the tip tray off the table before we had counted the change."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Try the Duck Confit Hash (topped with two eggs) or the Beer Battered Fish Chips on the Brunch menu."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It still took a little while to get our drinks and food - But the atmosphere made up for it."], "output": "[['food', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food This isn't for those on a budget, but portions are generous."], "output": "[['food', 'negative'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After our meal,the manager, even took some of his time to sit with us and give us a lesson in Sake 101."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The rest of the meal was good, but a little over priced for Chinese take out style food."], "output": "[['price', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["i mean the place was empty and it seemed to take for ever to get food, drink or the check."], "output": "[['place', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Adding insult to injury, the waiter had to ask for the wine bottle by number (where are we?"], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The drinks were water down and the only BIG thing was the bill."], "output": "[['food', 'neutral'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Flavorful Indian favorites like vegetable pakora, lamb tikka masala and tandoori chicken, as well as unexpected offerings such as Alaska king crab legs and fried coconut shrimp, are served at extremely reasonable prices."], "output": "[['food', 'neutral'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The server was so busy the night we visited that she forgot to put in our food order."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Service was slow and our drink order took forever (and the place wasn't crowded)."], "output": "[['service', 'negative'], ['food', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter was singing while taking our order- the food arrived 30 minutes later and the food was good, but the mules Frites were cold, the steak had to be returned twice-the spinach looked like it was grass from Union Square park with hunks of garlic in it-totally Unacceptable."], "output": "[['staff', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I asked the waitress what this was for and her responses were as follows: We put in an extra shot, We had to use ice in the drink, and It must have been the computer."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Prices are not cheap, but not expensive but the meal is worth every penny."], "output": "[['price', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service was not great, the wait staff were not clear on the ingredients and or preparation details of the meals."], "output": "[['staff', 'negative'], ['ambience', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food here is consistently good - the service is not - but it seems that they're getting busier than they can handle, good for them, bad for guests."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food is on the good side but not so terrific to compensate the bad service, crammed tiny-tables, dirty glasses, overly loud music, which is good for the bar part of the establishment but not when you want to seat down, eat and have a normal conversation at normal volume."], "output": "[['food', 'positive'], ['service', 'negative'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We should have had the entire restaurant, but the manager let some random lady sit up at the bar because she was a regular."], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I sometimes go here when in the area and though the food is always great, the Basil Chicken and Shrimp Tempura roll in particular, the service has much to be desired."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["In addition guys, please hire some waitstaff who know both English and your menu."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I though the service could have been better, the staff are not experience enough to know how to make the drinks without reading the instructions."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I just had dinner there with my girlfriend and we had the best time."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the water guy was extremely attentive, thank god he was because we had to ask him for our waitress many times: for ordering our food, more drinks, dessert and check."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Amazing views of NYC regaled us at lunch earlier in the week and then at dinner this evening."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter returned and said the bartender refused to take my drink back because there was nothing wrong with it and I would have to pay for it."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They ran out of the drinks my friends ordered, but the staff was eager-to-please and much appreciated."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Multiple televisions on both sides of the cozy room ensure unobstructed sight lines for fans, whether they're sipping pints at the oak bar or snacking on pub munchies--like baked clams, nachos, and buffalo wings--at tall tables in front."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Enjoy a drink at the bar over fresh shucked oysters."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food Crave's two chefs have resumes that boast stints at Payard, Nobu and Industry (food), so it's no surprise their menu is full of unusual twists on old favorites."], "output": "[['miscellaneous', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were seated quickly (and had reservations, but they didnt seem to be absolutely necessary) and our waitress offered much insight into menu bests and worsts."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Even with our large appetites we could not finish all the food or wine, which has never happened with a tasting menu before."], "output": "[['food', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The sexy waiter suggested the Pineapple Basil ( I Know is sounds yucky, but MMMM) Martini."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I don't understand the other negative reviews of the service because we had amazing waiter."], "output": "[['service', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It was well past 8 pm when they finally got us the check, and we asked for free rounds of champagne to compensate for the poor service (since the wine dinner had started, and were denied."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When the bill came, the waiter snatched it back so he could add the $3 difference to the wine."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The concoction was thrown away a mere two blocks from the Bar."], "output": "[['food', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The bright point of dinner was dessrt."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["A full bar and a dozen different margaritas attract a happy hour crowd, and a tortilla machine is often surrounded by children watching the dough-to-tortilla transformation."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Their appetizer portions are not huge, just right since the entrees are much larger."], "output": "[['miscellaneous', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our server seemed out of it, and drinks took 15 minutes to arrive."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the waiter didn't recommen any special for the night, didn't come back to the table to check if everything is okay, didn't even offer me the dessert menu at the end."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Just don't take the seat between the bar and the back half of the restaurant, i saw a woman get nudged 40times sitting there."], "output": "[['miscellaneous', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After I had complained to a bouncer (the manager would not see me) a waiter was sent over and did get us our drinks."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["although I don't think there is any beef on the menu (but there is plenty of fish and chicken)."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It has the most authentic Mexican found I have found in the Metro area and the margaritas are outstanding."], "output": "[['miscellaneous', 'positive'], ['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["food arrived quickly and was hot and v good, just don't be on a diet if you are going to eat here as no real options for slimmers!!"], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": [") And don't forget the svc, those waiters stare at you your entire meal, just waiting for you to put your fork down and they snatch the plate away in a second."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After we in fact moved to the bar, and I told the waitress which bottle we wanted - the one we had been drinking - we were told we had to order off the limited daily specials list."], "output": "[['place', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["True, the service is hardly on par with the finer restaurants in NYC, but I go for the energy and the tasty tapas-like seafood treats that are perfect with beer or sake."], "output": "[['service', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The manager came over to our table at the end of our entree course to get our review."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I love the food, and have gone back several times, but each time the waitress is a little nastier."], "output": "[['food', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The server rolled his eyes when we ordered only an entree per person (with no appetizers), spoke curtly to us, and ignored our requests for more water etc."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The wait for brunch is kinda long (what can you say?"], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu showcases Thai-French favorites: fresh chopped hai (white fish) and salmon with Chinese black olives and basil oil; mussels in coconut-lemon grass broth; and garlicky octopus sauteed with ground pork, broccoli rabe and lime juice."], "output": "[['menu', 'neutral'], ['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My friends and I tried practically every strange, inventive dish on the menu, most of which are very tasty."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The wait staff while attentive did nothing to address the hair that was found in one of our dishes."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["There were three parties of two standing in the front entrance looking like bumbling idiots while not a single host, waiter, or manager attended to us."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I understand its a very busy night of the week but it is unacceptable that I was hung up on by the hostess twice (I also called back and she refused to answer the phone for 15 minutes) and was told that I should have picked up my food instead of having it delivered."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Your drink is at your fingertips and you don't have to wait for the waitress to come back with your cocktail."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Captain was showing his impatience for a crowded Monday night and the dinner I was served was not prepared the way he told me it would be."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The characters were very entertaining, and while the prices are a little steep, it is well worth the cost."], "output": "[['miscellaneous', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Food was fine, and the place is pretty cool, but the waitstaff was slow and pretty clueless."], "output": "[['food', 'positive'], ['place', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We ordered a platter that was an asssortment of appetizers which was great recomendation."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If you don't mind eating great thai food in a schnazzy ambience with a hop hip lunch crowd, then come on over to SPICE."], "output": "[['food', 'positive'], ['ambience', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Beautiful rooms filled with beautiful people, but expensive for what it is ($68 prix fixe), limited menu, tiny portions, reeeeeeeally slow service, undercooked potatoes with the cod, less than fascinating desserts."], "output": "[['price', 'neutral'], ['miscellaneous', 'negative'], ['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The owners Pat and John are very friendly and can often sit and have a beer with you."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It's not going to win any awards for its decor, but the food is good, the portions are big, and the prices are low."], "output": "[['ambience', 'negative'], ['food', 'positive'], ['miscellaneous', 'positive'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It took an hour for us to order, another hour and 15 min to get our entree's I had to go to the bar to order my champange, and carry it back myself, the waiter got our entrees mixed up and placed them in the wrong place and sat there and watched me switch them around."], "output": "[['place', 'neutral'], ['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the atmosphere is that of a diner, but if you get a booth that is the best!"], "output": "[['ambience', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If you're tired of the long waits for table at nearby place, then head to Moutarde for a delicious meal that won't keep you waiting."], "output": "[['food', 'positive'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If you are undecided about which sandwich to choose, go for the Indecision, which is a trio of smaller sandwiches on the menu."], "output": "[['miscellaneous', 'neutral'], ['food', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["-4 waiters bustling around though no table was actually being helped -25 minutes to take our order -15 minutes to get the drinks we order -another 20 minutes to get our food -NO apology from the waiter In between our lunch, a man burst out shouting in anger at the lousy service (he asked for ketchup 20 minutes ago and never got it)."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food is ok, but not worth the prices."], "output": "[['food', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["not only did we not get our 'bombay' fries until after the entire meal, but we then had to wait nearly an hour for our inattentive waiter to bring our check, and only after we flagged him down."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["1 hour for water, 1 hour for drinks, 1 hour for food, as you can see we were there for almost 5 hours before our bill came, not for enjoyment but pure frustration."], "output": "[['food', 'neutral'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["She walked away in a huff, and had the BUSBOY pass on the same message: you can't order coffee because you've already paid (have these people never heard of someone changing their mind?"], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["What a pleasant surprise to have found a restaurant where you can sit at the bar and feel like a glamourpuss, yet whose staff and even other patrons make you feel like you are already a family friend."], "output": "[['place', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We didn't have reservations, and showing up at 8:45 we were told it would be about an hour wait."], "output": "[['miscellaneous', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Portions are small, they try to pass themselves off as family style by encouraging sharing and putting dishes in the center of the table, but it is glorified a la carte."], "output": "[['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["but no reservations makes for a very long wait, usually of an hour."], "output": "[['miscellaneous', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food The Korean dishes here are a bit more delicate than the potent fare found 30 blocks north, but the kitchen is hardly pulling its punches."], "output": "[['food', 'positive'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["And the waitstaff has very little knowledge of the food, they served me the wrong dish and no one could identify what it was that they gave me, someone said pork chop, someone said lamb, and then they insisted it should be fine since it was the same price."], "output": "[['staff', 'negative'], ['food', 'negative'], ['service', 'neutral'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It appears to be a charming french outdoor bistro, and the food wasn't bad, but the waiters were clearly tired of dealing with tourists, and didn't handle us with care."], "output": "[['food', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The wait staff was not as attentive as I would have liked, we had to ask several times for water and refills of water, and after the food was served, no one returned to check on us."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Basically the comfort is lacking but the food is the focus."], "output": "[['ambience', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["1) they gave us the wrong table had to wait 10 minutes until they gave us the one we wanted 2) had to wait 15 minutes for a waiter 3) ordered chicken and brocolli."], "output": "[['miscellaneous', 'negative'], ['staff', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When the food came, it was almost good, but the lack of AC, bad service, and overall apathetic staff, from the HOST, to the MANAGER to the WAITER, ruined the experience."], "output": "[['food', 'positive'], ['service', 'negative'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The bar area got a little too crowded but the ambiance was great."], "output": "[['place', 'negative'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The wine list was had some of my favorites which I have not seen anywhere in New York, and when I clumsily spilled both water and wine all of the my table the waitress and manager were there in a flash jovially helping me clear up the mess."], "output": "[['food', 'neutral'], ['miscellaneous', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Service was a little slow, but going on a Monday night during the Brooklyn Restaurant Week, where 20 bucks each got a friend and I appetizer, entree, and dessert was phenomenal."], "output": "[['service', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We went there on New Year's Day around 7 pm without a reservation and were able to get a table right away thanks to the very accomodating hostess."], "output": "[['miscellaneous', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["You'll have to wait for a long time if you're not in with the management or Fernando, but it's worth it, have some campari and cinzano at the bar!"], "output": "[['staff', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Not only did the food take an eternity to come out; but the waiter never checked in, explained the delay for the food, or refreshed our drinks."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene Opened in 1993, Nick's may be the only great pizza place in the city of New York that isn't older than most of the people who eat there."], "output": "[['miscellaneous', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I was tempted to try the dessert because I've heard rave reviews about it, but we were stuffed, as the portions are fairly large."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We sat for 20-40min without water or bread and were basically ignored by the waitstaff."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu has many choices, and the dining experience lends itself to being a great place for a date, client dinner, parents' dinner or even a start-off to a night out on the town."], "output": "[['miscellaneous', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Sure, the wait was a bit long for a table, but the service was good and the food was pretty good too."], "output": "[['service', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Since the waiter NEVER checked on us during the meal, she never had the chance to ask for hoisin."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Nonetheless, our waiter gave us prompt service and a smile every time he came over to take an order, bring us drinks, or check up on how we were doing."], "output": "[['staff', 'positive'], ['service', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The owner circles the place asking patrons if their meals are fine."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["small portions, average food 6) we ask for the check, the waiter says, ok, and 5 minutes later asks if we want coffee or dessert."], "output": "[['food', 'neutral'], ['price', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food is average the prices high and the whole experience was very upsetting."], "output": "[['food', 'neutral'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["prices were low, you got a good deal, sushi was ok; everybody wins."], "output": "[['price', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["i went on a thurs night and it was a bit loud due to the many businessmen eating their dinner, but the food and service more than outdid the lack of peaceful dining."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Instead, 4 members of the wait staff were giggling and carrying on at the corner of the bar."], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene Uncomplicated, tasteful touches--a soothing abstract painting, an exposed brick wall, a tiny bar--grace the restaurant's neutral-toned interior."], "output": "[['miscellaneous', 'positive'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They brought my mother a chicken enchiladas instead of cheese and then it took her 10 minutes to explain what the error was to the waiter and bus boy who then finally had to tell the manager who was also confused and my mother is fluent in Spanish."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They were seating people without reservations who were either friends of the employees or were slipping the hostess $20 to get seated without a reservation."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After dinner the manager grabbed my boyfriend, asked him: Where are you from."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I went to the tasting before Nobu opened and the menu and service has greatly improved since then."], "output": "[['menu', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["There is a long bar area wide enough to accommodate large crowds, large screen tv's on the walls to view games, but not that do not dominate the atmosphere, and up front there is a large lounge are with several booths and a working fireplace."], "output": "[['miscellaneous', 'negative'], ['ambience', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My party did not love the meats on the menu maybe the pork dumplings but nothing else."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I absolutely hate communal seating and closely spaced tables and this place had both, but the atmosphere and the food were such that I was able to get beyond the grumpy mood that put me in to have a really good experience."], "output": "[['miscellaneous', 'negative'], ['ambience', 'positive'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They need to change the overall decor if they want to get a serious dinner crowd though."], "output": "[['ambience', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It would have been nice to find that out on the website but it took us an hour of waiting for Godot before calling and being told the news that no lunch was prepared for us."], "output": "[['service', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Also, the waiter wrongly described a wine I had inquired about causing the sommelier to have to make a trip to the table to offer an alternate recommendation."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I love to go there on weekends and have the delicious french toast (made from baguette slices) or the granola with fresh fruit, sometimes I am so torn that I end up getting both!"], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["i've been there for lunch - when the place is empty- and the waiter spent more time outside, soaking up the sun for himself, like he was a patron."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I realize that this place has a huge menu and, therefore, will have some not-so-good things, but it's the rudeness of the service that gets to me."], "output": "[['menu', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere is still to die for, but the wine list has so clearly been pared down and marked up (as a result of higher foot traffic brought in by lots of rave reviews in local publications, perhaps?"], "output": "[['ambience', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Not only is it the nicest atmosphere with an antique bar and allabaster globes sconces, marble fireplace."], "output": "[['ambience', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Last, but not least, when we walked in, most of the clientelle was Vietnamese and next to us was a food critic whose review was on the back of the menu."], "output": "[['miscellaneous', 'negative'], ['food', 'neutral'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After leaving the traditional 15% tip, the waiter ran after us for half a block to confront."], "output": "[['price', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Excellent Steaks, the attitude of the Servers could be a little better but the food makes up for everything."], "output": "[['food', 'positive'], ['service', 'negative'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The pooris were miniscule, about 2 bites each; they serve 4 of those as a dinner for $25!"], "output": "[['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Oh, the prices were not so bad either, we paid $58 for chicken, salmon, one sushi roll, one ceasar salad and soda :)."], "output": "[['price', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene Honeycomb-colored walls, random wall art, a peek into the kitchen from paper-topped tables--all combine for a casual, thrown-together ambience."], "output": "[['miscellaneous', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": [") The food was good, but not at all worth the price."], "output": "[['food', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The music is a little bit louder, but the food is excellent."], "output": "[['ambience', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It's sad that everything about this place was great (even the service and decor) except for the steak."], "output": "[['service', 'positive'], ['ambience', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the sushi is so-so, the 70s orange-themed atmosphere is 2000ish, and there is no reason for the staff's attitude."], "output": "[['ambience', 'neutral'], ['staff', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food It's a people-pleasing menu, with spaghetti and meatballs, calamari, eggplant Parmesan and other red-sauce classics alongside several more upscale dishes."], "output": "[['food', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the service was very slow and his knowledge of the menu wasnt that good."], "output": "[['service', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Service was bad enough that we decided to head out after the first round of drinks."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitress told us the portions were not big, so we each got an entree and shared a side."], "output": "[['staff', 'neutral'], ['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If you live downtown, definitely grab one of their menus, make a phone call and relax in front of the tv while they pound the pavement to get to you (although they do take about 45 minutes on average to get to you)-- the in restaurant service is likewise very very good."], "output": "[['menu', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Even if you have to wait a bit for a reservation, the hostess will come over to apologize, update you on the wait and make sure you are comfortable."], "output": "[['miscellaneous', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The mole sauce is not too sweet and adds a nice flavor to the otherwise bland chicken."], "output": "[['ambience', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We went to Steinhof about a week ago and sat at the bar since the place was packed, but they have the full menu at the bar."], "output": "[['place', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The 'people watching' and table location (on boardwalk) made up for the rude service."], "output": "[['miscellaneous', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["very nice servers, but they seemed more interested in conversing with the regulars than bringing food and being attentive."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Food was good but portions were quite tiny."], "output": "[['food', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were charged for the missing appetizer and when I complained to the manager, who never thought to apologize, he blamed the kitchen."], "output": "[['food', 'neutral'], ['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["One of the waitstaff spilled a huge drink on the floor that splattered everyone nearby, no offering of apology was made or to foot the drycleaning bill and no comp was offered either."], "output": "[['staff', 'negative'], ['food', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["went here w/ great expectations and was greatly disappointed; the food was good, not great and vastly overpriced- one salad, two pasta dishes, two demi-carafes of red wine- $100 (tax and tip); rediculous; orechiette came w/ so little brocoli rape that it did not have its characteristic flavor; and it is very very loud."], "output": "[['food', 'positive'], ['ambience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Between the seven of us we sampled just about everything on the menu, and nothing disappointed (ribs pulled pork seemed like the biggest hits)."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The salads were amazing in themselves - mixed greens andtomato wedges in a delicious balsamic vinagrette with slices of Italian bread with warm goat cheese."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Two Tom's food is excellent, it more than makes up for the lack of decor."], "output": "[['food', 'positive'], ['ambience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If you are looking for service and all the frills $$$ - Il Mulino is the best for both - if you are looking for a fabulous dinner in/out - this restaurant is it!"], "output": "[['service', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Unfortunately for them, we would have ordered twice as many drinks if we didn't have to wait half an hour for the waitress between every drink."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I made the mistake of coming here with 5 friends for brunch so the wait was extremely long and then we got stuck at the only table big enough for 6 (downstairs near the bathroom away from all of the other patrons) so that was dissapointing but I will be back soon with 1 or 2 friends."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter told us he knew all the wines on it quite well, and he did!"], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["There were about 4 tables filled in the entire restaurant yet the hostess made us sit at the bar for 20 mins--she never would have come for us had we not approached her asked to be seated."], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["This newly opened restaurant is another one of those Indian places that has a hugely promising menu and a greatly disappointing food."], "output": "[['menu', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Yes, this place is good, a cut above some of the other local diner food and a nice, friendly atmosphere."], "output": "[['place', 'positive'], ['food', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Nice ambience and bar while waiting for a table."], "output": "[['ambience', 'positive'], ['place', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The kicker was when there were three items on our check that were priced higher than stated on the menu and by the server."], "output": "[['price', 'negative'], ['menu', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If you're looking for barbeque like Dallas BBQ (soaked in sauce from a bottle, generic, homogeneous food) then you won't like Blue Smoke."], "output": "[['food', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["For the price I paid for a cup of Bustelo coffee w/ milk I could buy 2 vacumed packs for 3 bucks."], "output": "[['price', 'negative'], ['miscellaneous', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Three course meal for lunch was $13, the prices for dinner were just as great!"], "output": "[['food', 'neutral'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Lost reservations, out of liquor, jam-packed, waiting room, out of wine, sent steak out raw, no choices for dessert, no room to breathe, terrible service, etc."], "output": "[['miscellaneous', 'negative'], ['place', 'neutral'], ['food', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Although we were seated 35 minutes after our reservation the service from then on was outstanding."], "output": "[['miscellaneous', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food The menu includes lovingly made renditions of panini, bruschetta and tramezzini (cocktail-style sandwiches with fillings like tuna with black olive pesto and bresaola with arugula), along with a roster of cured meats, cheeses and olives that have been imported from Italy."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My meal here was awesome, the appetizers, the bar finger food, the service, the drinks, the entrees of Smoked fish, Lamb salad, Clay pot salmon, Lobster rolls, and the dining room is spectacular."], "output": "[['food', 'positive'], ['service', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The place is small, but loaded with plenty of goodies that range from Italian inspired treats to Greek pastries all well prepared."], "output": "[['place', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The pizza is thet always fresh and just made they hav an outdoor seating area that is partially covered they also have a full service restaurant on the premises they make everything on premises."], "output": "[['food', 'positive'], ['place', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["A friend was dieing for chorizo but it was only in the tapas menu which we couldn't have."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Just make sure you make reservations a few days in advance because there aren't a lot of tables."], "output": "[['miscellaneous', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They had a prix fixe menu with the most amazing cooked quail appetizer, then lobster bisque, followed by a divine choice of entree, and then the chocolate mousse dessert."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["In summer, the small outdoor garden is an ideal place to sip coffee while reading under a canopy of trees and sky."], "output": "[['place', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If you had good service there, try to get your waiter's name and request him/her by name the next time."], "output": "[['service', 'positive'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter was stuffed with attitude and didn't bother explaining things on the menu that he clearly knew we could not understand."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["not having a menu was rather strange at first but the food was superb."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If you are a person who wants perfect service, you should probably skip it, you may wait for your server to sing a song before you get your drinks but that is half the fun."], "output": "[['service', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Casual and kid-friendly, the red-and-gold colored restaurants offer quick drive-thru or dine-in service with a menu of burgers, sandwiches and more."], "output": "[['service', 'positive'], ['food', 'neutral'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When a seemly accommodating Le Souk manager assured you that he had no problem serving a group of twenty on a Saturday evening, I expected him to keep his words or shall I say our table."], "output": "[['staff', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["dining with my mother this past Saturday must have signaled to the wait staff that I wasn't cool enough to merit their attention."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the staff knows the regulars by name and the sushi chef even yells goodbye from behind the bar."], "output": "[['staff', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Overall, the food makes up for what is missing in the ambience and service."], "output": "[['food', 'positive'], ['ambience', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["FINALLY the waitress came with our food after an HOUR!"], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Before our server took our drink order she told us that the prices on the menu were going to be higher that night because of the party."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['price', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["when tables opened up, the manager sat another party before us."], "output": "[['place', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After arguing about this and requesting tap water instead of a bottled variety, we were exiled to customer Siberia, and the staff seemed eager get us out of the restaurant as soon as possible."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Instead of being smart business people and treating us as paying customers, we were told they do not serve drinks, only food (only food?"], "output": "[['miscellaneous', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["However the casual atmosphere comes in handy if you want a good place to drop in and get food."], "output": "[['ambience', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["A narrow corridor leads to a tiny space where there are three tiny white tiled counters, a great deal of mess (stacks of bottles, cans) and a small counter holding 12-14 entrees."], "output": "[['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were ignored by our waitress after our entrees had been served."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When I was there with a friend the waiter who served us was pretty friendly."], "output": "[['staff', 'positive'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My greek salad cost about $9 and for that price, I would not have expected chopped olive (as opposed to whole), and shredded bits of lettuce."], "output": "[['price', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The retaurant is know for the long wait but they do take reservation for group of 5-8 people, so it was just perfect for my friend BD dinner for 3 couples."], "output": "[['service', 'negative'], ['miscellaneous', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["since we're informed its service isslow we had dinner in midtownwent for dessertb-day thing."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the soups were superb and only $2 a bowl, and the entire dinner, with beers, cost less than $30 for two people."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The place was practically empty when my friends and I got there for dinner."], "output": "[['place', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["On top of that, when we tried to order more food half-way through our first entree order, the waitress told us that we couldn't because they needed the table for another reservation!"], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["8pm reservation, place was half empty on a Saturday."], "output": "[['miscellaneous', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene The bright mix of colors painted on the cafe's walls matches the vivid margaritas that sit on nearly every table and litter the sceney bar."], "output": "[['miscellaneous', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The busboy kept our glasses full; the waiter warmed up to our table at the end of the night by cracking jokes."], "output": "[['miscellaneous', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Desserts were visually inventive but lacking in flavor."], "output": "[['food', 'positive'], ['ambience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The place was packed and while our food took time to be prepared, our waiter earned points for his sparkling conversation to pass time and for also knowing practically every ingredient of every special under consideration."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["i recently had brunch at the new hill diner let me tell you it was great."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The festive crew serves from a gigantic menu of American classics: chili, burgers, cobb salads, baked potatoes, wings, philly cheesesteaks, club sandwiches, you name it."], "output": "[['staff', 'neutral'], ['menu', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The head-on shrimps with anchovy butter had me licking the plate."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["You can only sit on the stools with a slice, as the main dining area downstairs is for real food."], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The wine list didn't look all that great, but there was a very interesting selection of beers on tap."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Unfortunately the food and the service don't live up to the spectacular setting."], "output": "[['food', 'negative'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food was OK, but trying to get anything, like a drink refill or the check, was an ordeal, and this was when the place was nearly empty!"], "output": "[['food', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Seating is limited, so you will probably want to order take-out, but a better take-out pizza you will not find!"], "output": "[['place', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The clientel, however, make it a scene for creative, talented people--inlcuding a soon-to-be-famous theater director who used to waitress there!"], "output": "[['food', 'negative'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I liked the overall setting A LOT and it was only improved by the fact that our waiter was pleasant and attentive even though we only ordered entrees (no drinks, no appetizers, no coffee)."], "output": "[['ambience', 'positive'], ['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["However service was quite slow for a lunch hour."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu was much too narrow - 4 pastas and 6 meat dishes or so."], "output": "[['menu', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["(We did make reservations, since we had a group of 8, but had a short wait when arriving a little early."], "output": "[['miscellaneous', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["first of all, the hostess was not pleasant and had a bit of an attitude when seating us."], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We are laidback diners and as we've both waited tables, we tend to be forgiving of irregular service."], "output": "[['price', 'neutral'], ['place', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We only saw 2 - 3 boring appitizers on the menu and not a lot of choices of meat to select from."], "output": "[['food', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It gets crazy busy like any other bar on the weekends, so don't go there on a busy night if your looking for a quiete dinner party or fine dining service."], "output": "[['place', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service may be a little slow (what can you expect in this laid back atmosphere), but a Sunday brunch is a rewarding experience."], "output": "[['service', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Get in before peak dinner time (7-8 PM) to avoid harried service."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The mussels and frits were great, but the host had an attitude and my friends and I waited about 1 1/2 hours to be seated on a random Tues."], "output": "[['food', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My date knew the waiters from years of dining here, so we were treated like royalty."], "output": "[['staff', 'positive'], ['food', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["While the appetizers I sampled (gnocchi; shrimp wrapped in coconut or somesuch) were not so impressive (the gnocchi portion is meager and overpriced), my table was 100% satisfied with their entrees too."], "output": "[['food', 'negative'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Were told we could not share one menu and called over the horrible manager."], "output": "[['menu', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The bill came out to quite a lot though, considering there were 14 of us some of us ordered way too many drinks."], "output": "[['price', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Many Thais top off spicy dishes with a fried egg, but in many places it's not on the menu and when requested, I will either get charged $1."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It had not been made fresh at the bar, but kept in the freezer till we ordered, they also forgot our soup, kept us waiting for the frozen sushi for close to an hour."], "output": "[['place', 'neutral'], ['food', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The owners couldn't have been more accomodating -- we had the entire restaurant to ourselves on a Saturday (before it opens to the public for dinner)."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We would have left and gone to another restaurant but the host kept saying that a table was opening up in 5 minutes, people had just paid, etc - except when I went to check the table, they were ordering dessert."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter was pushing us all night to take our plates, and swiped my dessert before I was finised with it."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Or better yet, if on a budget and want to do something romantic, stop at the bar for a drink and enjoy the sunset."], "output": "[['place', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It is a nice diner atmosphere, they have booths all around and a couple of middle tables."], "output": "[['ambience', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitress had an ongoing diatribe with a waiter the whole time she served us-it was ALL BAD!!"], "output": "[['staff', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Food was good, but not worth the wait."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service was rather slow but our waiter was very pleasant and obliging."], "output": "[['service', 'negative'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Didn't like having to flag down waiters for drinks, nor having to wait almost 15 minutes for a check after asking two servers."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I don't usually go there over the weekends or during prime dinner hours--but for a weekday dinner it's great, and I've never had any problems with crowds, waiting, or bad service."], "output": "[['food', 'neutral'], ['miscellaneous', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["A+ for the food but the wait staffs need to educate themselves better."], "output": "[['food', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food was awful and took forever to arrive - which considering the limited menu, few diners and the fact that we ordered chili, mac cheese and a grill cheese was annoying."], "output": "[['menu', 'negative'], ['price', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Finally got our food after waiting a long time for oysters, doesn't take that long to shuck 'em, the place isn't that big, and it was OK."], "output": "[['food', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After a crazy day @ work, with no reservation, we were so lucky to score a seat at the bar on an incredibly busy evening."], "output": "[['miscellaneous', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I also asked for a chef (thought that may be able to talk about the food for the party), but the waitress said that there was no chef at the restaurant."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter (who also seemed to be the manager) dropped red wine all over me the contents of my purse and all he did was apologize quickly, hand me some club soda and avoid me for the rest of the time I was there."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The place was so dark, I needed the table candle to read the menu and could not properly see what I was eating."], "output": "[['place', 'negative'], ['miscellaneous', 'neutral'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["People were leaving because they had been waiting for hours, however we decided to stay and have a complimentary drink at the bar which was absoloutely beautiful along with the view, the only plus."], "output": "[['service', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Dining experience begins with cracked, filthy vinyl tile flooring tables so small close together that you couldn't move."], "output": "[['food', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["*Food:Just about anything on the menu, however the sandwhiches are most popular and recommended."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["To be fair, I realize I was there for lunch and that the food is probbably better at dinner service when a full kitchen staff has arrived and prepped, but I doubt I'd return to find out with so many other options in the neighborhood i already trust."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Food and Service of the same high quality elsewhere in NY would have been twice the cost."], "output": "[['food', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Silky black bass with porcini mushrooms carries smoky, earthy and buttery overtones that somehow never overpower the fish, and whole-roasted baby pig includes belly meat, braised for 24 hours in five spice-ginger glaze, and yet the pork flavor is still fully present."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Overall,it's a good place to have dinner and hang out if you do not mind waiting for food,weird music and rude manager."], "output": "[['food', 'neutral'], ['service', 'neutral'], ['ambience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Went there for dinner last night w/ my boyfriend and a friend after work and got there around 7 so we were able to score seats in this tiny cramped space."], "output": "[['food', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The chips and salsa are good, but the meal is not worth the wait."], "output": "[['food', 'negative'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["There is NO waiting area - waiters, diners,and staff all converge in a tight space."], "output": "[['staff', 'neutral'], ['price', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The chefs and staff are welcoming and happy to make substitutions or tune the spice up or down to your requests."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["So I go into the bar, and I ask the (extremely hot) waitress, what's the soup of the day?"], "output": "[['place', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The wait could be long because of the limited number of seats but it is worth it, especially if you leave your cell phone # with them and go off for a drink at any one fo the excellent bars nearby, like lokie, great lake, etc."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When the manager came to our table at the end of the meal and asked how our experience was, I complained to him about the cold."], "output": "[['staff', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food took forever to come out from the kitchen."], "output": "[['food', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The meal arrived just as we were finishing the appetizers, each good portions."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Aperitif was the Casablanca; it was served carelessly with ice chunks large enough to sink the Titanic."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["both appetizer and main were poorly made by some random cooks the picked up from who knows where."], "output": "[['miscellaneous', 'negative'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["While I liked the place, I'd never come back in a weekend night again, and with reservations."], "output": "[['place', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The inattentive waiters never refilled our water glasses, never offered more drinks, our silverware was never replaced, and it took almost half an hour at times for them to clear our table after we finished a course."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["when the waitress finally took our order after being seated at the table for over 30 minutes only to wait another 45 minutes for food and when the food arrived the order was incomplete."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The choices on the menu were very limited-discounting raw items, there were practically no appetizers The foie gras de canard was mediocre with a syrupy sauce."], "output": "[['miscellaneous', 'negative'], ['menu', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Lastly, the bartender didnt give me detailed bill, just my credit card receipt to sign."], "output": "[['staff', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food The restaurant boasts an impressive raw bar and samplings from the bait menu a big draw."], "output": "[['food', 'neutral'], ['place', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["In the hour we waited for our food we had to remind our mentally challenged waitress 3times to bring our chipssalsa."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The strong suit of this place is the decor, alas we was seated and served by some guy who looked like he was out of a seedy 70's porn movie and everything went downhill after."], "output": "[['ambience', 'positive'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They did a great job on the decor but it seems that the food has gotten a bit less in the quality department, as well as in the portion size!"], "output": "[['ambience', 'positive'], ['food', 'negative'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We decided to order soup (over $6 a bowl), thinking that would be quick, however our waitress then said the soup is OUT OF A CAN and still would be a 20 minute wait since the tickets are processed in order."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Waitress didn't know anything about the menu, but other than that I would recommend."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the service was somewhat spotty, but we were rewarded with free drinks and the waiters were all sweet and lovely, genuinely french-speaking but not snooty!"], "output": "[['service', 'negative'], ['food', 'positive'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The irony of it all is that I tried the fish and chips at a sports bar across the street the following week, 1/2 the price (w/ fries included), and the portion was bigger and much tastier."], "output": "[['food', 'neutral'], ['place', 'neutral'], ['price', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["brunch menu had nice variety to choose from, miniblueberrrymuffins better than some bakeries, included in their price mimosa/bloody mary's were nice."], "output": "[['menu', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The man working the door (red hair)-very funny and warming."], "output": "[['staff', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["One of my friends told them it was my birthday and the staff relally surprised me when their came to me singing with the mexican hats and a dessert with a candle on it."], "output": "[['staff', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The spaghetti with ricotta cheese is hands down my favorite thing on the menu and I am big fan of the house wine."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": [") I also noticed the table next to ours didn't enjoy her dish and they went above and beyond to try to make up for it."], "output": "[['miscellaneous', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The ambience is cool, and the cocktails might be worth coming by, but head somewhere else for dinner."], "output": "[['ambience', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After sitting without any beverages for about fifteen minutes, the manager got up and poured a glass of water for his smacking companion."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["PDiddy need a new staff you would have thought it was a bunch of old people cooking the food and waiting on us."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We ended up having appetizers in the lounge, while listening to a really great DJ."], "output": "[['place', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["No extra pickles, no AC, no ice water, slow service, the whole thing was just dissapointing."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Keep in mind, no one else was even in the restaurant and we were asking the waitress questions about entree options."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["i went in one day asking for a table for a group and was greeted by a very rude hostess."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitress was kind and helpfull with the menu."], "output": "[['staff', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Dishes feature intriguing names, and interesting combinations of fresh ingredients."], "output": "[['food', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The servers, casual in their striped button-downs, anticipate and fulfill needs as if they were trained as mind readers."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu prices are a bit expensive for what you get in quality and portion size."], "output": "[['price', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Fortunately the hostess was nice enough to take our appetizers off the bill after we complained."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["What it lacks in decor it more than makes up in the cuisine."], "output": "[['ambience', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It was not the mistake of the frozen lasagna, it was the icy service of the manager which has spoiled this restaurant for me."], "output": "[['food', 'neutral'], ['service', 'negative'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Since it changed owners/chefs, the portions are smaller (I always used to ask for a doggie bag for my chic-parm), now I can finish and still be hungry even after appetizers (which aren't as good anymore)."], "output": "[['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I was their for Saturday lunch, adn I think that there's a different dinner menu, but everything was great."], "output": "[['food', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Greek Glasswine is still on menu along side good value bottle selections fromaround the world."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Though we had to wait about 45 minutes from our dinner reservation time, we were given breadsticks, olives and parmasean to nibble on while we waited, albeit in the very cramped bar area."], "output": "[['food', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The manager (or someone very important that was able to be seated 1/2 hour before opening) sat in the corner, with a glass of wine, a date, and talked on his cell for about an hour, loudly, while the first arrivals were sent to the hotel tearoom next door."], "output": "[['staff', 'negative'], ['place', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We had to ask for bread after 45 minutes and even though our waiter was GREAT, he had to ask the stiff manager to comp us a round of drinks for waiting so long."], "output": "[['staff', 'positive'], ['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["These are all new items on the menu the waiter told us, and they were delicious!"], "output": "[['menu', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They offer a sushi bar with very fresh fish, and the side dishes are excellent."], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["you go all out with dress, tastes, and performance, and in the end its really about having a good time where you truly indulge yoursef in good vodka, compnay, music, and food."], "output": "[['miscellaneous', 'neutral'], ['food', 'positive'], ['ambience', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["There's even a nice menu of savory items served during late lunch and dinner hours."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The only reason they seem to taste so good is because the food is well decorated with its super small portion."], "output": "[['food', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The wait time for food can be long, so don't dine here if you're in a hurry."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["On another occasion, this same gentleman brought bottled water for our entire party [4] on the house again, when we missed our cab and asked to wait inside."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The only thing whihc i (and my partner) never heard before was: the waitress mentioned the price of the specials (?"], "output": "[['staff', 'negative'], ['price', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I live around the corner and I miss the unpretentious and always lovely, Irving on Irving, that used to occupy this space where you didn't need a reservation three weeks in advance to eat dinner after 5:30 and before 11 pm."], "output": "[['place', 'positive'], ['miscellaneous', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitress did try to get the manager to at least give us the Sangria on the house but the manager refused."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["One friend's pizza arrived about 15 minutes before the rest of our meals (the remainder of our entrees did not even arrive at the same time), and our waiter half-heartedly apologized for the delay while rolling his eyes."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["large portions so unless you are of large stature you should not get 2 appetizers."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We asked for bread plates when the bread was brought to the table and the server's response was management has decided not to offer bread plates."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["First, the waiter brought us to a table where people were still finishing their coffee from their meal - he told them the restaurant was busy and they needed to finish now and to pay their bill inside."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If you can't tolerate slow service at a pizza place, then spend more money elsewhere."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food This Cajun-Italian menu is lengthier than its Manhattan counterparts--here, adventuresome diners can still design their own pies, but they can also feast on oversized plates of peel-and-eat old bay shrimp and cajun spaghetti with meatballs enlivened with andouille sausage."], "output": "[['menu', 'positive'], ['price', 'positive'], ['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["In Short It's a bakery, takeout place and cafe all in one, and thanks to dishes prepared using the same ingredients stocked at famed gourmet food emporium, Zabar's, prices and quality are upscale."], "output": "[['place', 'neutral'], ['food', 'positive'], ['ambience', 'neutral'], ['price', 'positive'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["And then he'll forget to bring your drink every time you order one, won't pay attention to your table of 8, will give you unwarranted attitude, and never be friendly or smile."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["complaints were shrugged off and service was slow, causing the dinner to go on for over 2 hours."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["' When I called the waitress on it, she said that they simply couldn't serve tap water."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["With all of the kitchen goof-ups (appetizer coming out before the entree and one entree coming out ten minutes before the other) you would think that the wait staff would have been more attentive."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The decor was mediocre and honestly, I can get a better brunch at a Cracker Barrel restaurant."], "output": "[['ambience', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Once seated, there was no waitress to give us our menus."], "output": "[['service', 'neutral'], ['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We initially ordered a bottle of wine and the waitress though we may not like it, so she offered us a taste."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I go generally with one friend but on occasion have popped in with more, if a table is not possible, as they are booked solid every night, well, the food and service is just as over-the-top amazing at the bar or in the lounge as it is in the dining room."], "output": "[['miscellaneous', 'neutral'], ['service', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food was certainly fine, although prices were high by any standard, with dinner for four being over $300 without drinks."], "output": "[['price', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The cajun food is great but there is something for everyone on the menu and I have yet to be disappointed."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The staff was accomodating towards our daughter and nice enough to check up on her after they served dinner (I was a little concerned about the spices and they suggested a dish)."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The price is cheap - 5 dumplings for $1."], "output": "[['price', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The portions were pretty small for the price, I thought, and I never got the coffee I ordered."], "output": "[['miscellaneous', 'negative'], ['price', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["She then sent over the owner, and his only recourse was to give us a free bottle of sparkling wine."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["While the decor is a bit bland--a white room with a few fake palm trees and thatched roof--the service is fast and friendly."], "output": "[['place', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Service during dinner was alright, but one's perception to a restaurant usually starts from the very beginning: the entrance."], "output": "[['service', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The pancakes I ordered were nothing like the menu's description."], "output": "[['food', 'negative'], ['menu', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I've had Gnocchi from the Bronx to Coney Island and this place is, hands down, the best."], "output": "[['food', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I went to Joy hoping to find some great Indian, but unfotunately found curry that was no better than average."], "output": "[['miscellaneous', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food, congeniality, and service have all deteriorated overf the past few years and so the wait is not worth it."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I was not allowed to transfer my credit card to the table, and was treated disgracefully while the hostess waited for the bar to sign off my card."], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When our first order came, they forgot the torro (which we later learned it was finished for the night."], "output": "[['food', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["service, one would be overpaying for the experience and for the food."], "output": "[['service', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["(try the Queso Fundido and fire) Upstairs there is a dining room which is decorated with brightly colored mexican theme."], "output": "[['food', 'neutral'], ['place', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I don't remember the dessert item but when it was brought out flashing lights overhead threw colored beams on the walls and a young waiter came over to our table and did a little dance that was Bollywood MTV for the East Village set."], "output": "[['food', 'neutral'], ['staff', 'negative'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They've also got a huge salad/sushi/appetizer bar that you won't even get to if you're eating the meat."], "output": "[['place', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The first time I went, and was completely taken by the live jazz band and atmosphere, I ordered the Lobster Cobb Salad."], "output": "[['ambience', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The fact that the resteraunt staff couldn't even keep a reservation straight, not to mention that after screwing up, they told us to go scratch and made us wait almost 2 hours."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["One waitress was downright rude when we asked for the check."], "output": "[['staff', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Drinks took a while, and after a few rounds pf the we're sorry, we don't have this bottle sir routine."], "output": "[['food', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["A waiter looked me in the eye and said we did not order wine, as if to infer we were making this up."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Moules were excellent, lobster ravioli was VERY salty!"], "output": "[['miscellaneous', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I am not good with using chopsticks and asked for a fork, instead the owner insisted that I try using a chopstick an made me an easy-to-use chop stick right there on the spot!"], "output": "[['miscellaneous', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When the bill came, both appetizers were charged even though we had one bite of the first and it should not have served competely overcooked."], "output": "[['price', 'neutral'], ['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Basic facts: sub-par limited menu; poorly made drinks; random crowd; and a waitress (although entertaining) that was doing shots behind the bar."], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The store has a great atmosphere amd amazing staff who are always there to help if its a cup of coffee or a nice chat."], "output": "[['ambience', 'positive'], ['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene The main dining room of this boisterous Carnegie Hall restaurant, dubbed the New York Room, is a cavernous space with high ceilings and sweeping glass windows."], "output": "[['miscellaneous', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The only drawback was slow service, but the food and ambience are so nice that your wait is A) pleasant and B) worth it."], "output": "[['service', 'negative'], ['food', 'positive'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It's interesting but after eating dinner here once the only thing I remember is that the bar was nice, drinks expensive and food was only average."], "output": "[['place', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["however the dessert porportions somehow ballooned to regular conventional sizes."], "output": "[['food', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I went on a saturday and the atmosphere was no more exciting than eating dinner at home."], "output": "[['ambience', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["why go there to deal with staffs' attitude and eat bad food?"], "output": "[['staff', 'neutral'], ['service', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The only concern i have is with the slighly all-business waitstaff who order and throw the food down, rushing you out."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When my group complained to our waiter about a cake cutting fee that involved no cutting, the manager came over to the table and basically told us that it was our fault for not knowing that their policy was just to serve the plates, not to cut."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They don't offer recommendations, take a long time with drink orders, don't check back after serving the entree, and plan on waiting a long time for the check."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Diners sit around large tables where chefs ostentatiously chop, slice, stir-fry and grill."], "output": "[['staff', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Interestingly, cost only becomes truly apparent when dinner is over, as there is no menu before that presented for deserts."], "output": "[['price', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu was nothing special (I had to switch my entree choices several times because the server told me that the portion is really REALLY small!)"], "output": "[['menu', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I had to wait quite a while to get my food and the waitress almost knocked me in the head with her tray."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["For a menu in a similar price range with some similar items, but mostly unique entrees, try the less formal Toast 13 or so blocks north on the same side of Broadway."], "output": "[['price', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We waited about 10 minutes for a table and enjoyed peanuts and cocktails at the bar (drinks are $3."], "output": "[['miscellaneous', 'neutral'], ['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I even had a waiter who was carrying a tray of beers actually TELL me to get out of the way as I was making my way towards the door."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu is pricey and the food was not tasty - except for the tostones with garlic and oil."], "output": "[['menu', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the place had open doors and windows and a very relaxed, candle-lit type of atmosphere."], "output": "[['place', 'positive'], ['miscellaneous', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Beyond the green awning and floor-to-ceiling windows, sophisticated (and often European) patrons drink wine from the bar in back and dine on French fare like nicoise salad, foie gras, and steak tartare at tightly packed tables."], "output": "[['food', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Coffee served without sugar/milk and took more than 10 min to catch the waiter to ask for it."], "output": "[['service', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I had read good reviews about the value and food quality at this restaurant, so I was not surprised to see a decently priced menu (pasta under $10 and entrees approx $12 to $15)."], "output": "[['miscellaneous', 'neutral'], ['food', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu of upscale American fare is somewhat intimidating as there are almost too many choices, but our wonderful waiter Eric came to the rescue suggesting and describing specials as if he had just polished off dinner himself."], "output": "[['menu', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter simply comped off our appetizer and then stayed away for the rest of the night--we waited an additional twenty minutes after we were done eating for the check!"], "output": "[['staff', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I have tried to make reservations, but both times, the hostess didn't have my name."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Otoro tuna, gorgeously marbled with fat, is captivating; hamachi sashimi, topped by the chef with a whisper of sea salt and a barely-there squeeze of lemon, creates eye-rolling pleasure."], "output": "[['food', 'positive'], ['staff', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The place is huge, but it's always packed with people waiting to be seated because they made the mistake of not making a reservation!"], "output": "[['place', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If you're not looking for a pretentious atmosphere and a restaurant that serves the best steak you've ever eaten."], "output": "[['ambience', 'positive'], ['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It took about ten minutes to get out drink ordering after sitting down and once we recieved the bottle our waitress never once refilled our glasses!"], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Save the $$ and go to to curry hill (just 2-3 blocks away) or spend the $$ at a midtown indian eatery (Also: I commented to hostess prior to seating that there were a lot of tables empty when choosing my seat, and she snapped back that they had a lot of reservations coming in at one time."], "output": "[['staff', 'neutral'], ['place', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Upon entering Alta the bar and restaurant decor ironically misguide the patron."], "output": "[['place', 'neutral'], ['ambience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitress conveniently added in her tip into our bill, charged $10 for each margarita."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The space is grand with a very high ceiling although it is one of those places that they keep so dark you are not really sure what you are eating anyway."], "output": "[['place', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Waiters take your order and you don't get your food for at least 1 hour so you can prchase drinks."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["waitstaff was more into pushing the sparkling water than give me a wine menu."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Beer selection is a bit slim, but seats are plentiful and there are several sports monitors placed about the bar."], "output": "[['miscellaneous', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The place got really crowded around 8ish when I went right before Christmas so reservations might be necessary."], "output": "[['place', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We ordered 1/2 bottle of Gruner, 2 appetizers - foie gras and oysters, 2 entrees - steak and diver scallops, and 1 dessert, the pastry chef's favorite a mixture of crushed avocado, salt glazed caramel and lime sorbet (which really tasted like margarita infused guacamole, to try only if you're feeling wd-50 adventurous) for around $100."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter was very attentive and always kept the bread and drinks coming."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The drinkers beside us had fresh glasses of water brought on trays to replace the empties and a smiling waitress to cater to their every whim."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Never on the menu or in my inquiry to the waitress was the word garlic mentioned."], "output": "[['menu', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Also, be wary of what time of the day you go; around dinnertime, the restaurant becomes a jungle of diners and hustling waitresses."], "output": "[['price', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I went there recently with my boyfriend and not only did it take the waitress 20 minutes to acknowledge we were even there, 20 minutes to get us water and coffee and even MORE time to place our order and get food!"], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The ingredients used are of a good quality and the taste is superb."], "output": "[['ambience', 'neutral'], ['miscellaneous', 'positive'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We are 30 plus year olds, very gainfully employed, were not being loud or obnoxious, there were other diners around us as well as a bunch of people at the bar and nobody seemed to have a problem with us except for this manager."], "output": "[['place', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["we ordered simple salads, which were outrageous in price and def."], "output": "[['food', 'neutral'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Limited menu but for STEAK,,, and giant onion and tomato salad."], "output": "[['menu', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["In Short Many Murray Hill locals gladly overlook the dull green walls and fluorescent lighting for Jaiya's quick and affordable Thai cooking--if not, they take meals to go or get them delivered."], "output": "[['miscellaneous', 'negative'], ['ambience', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service was non-existant, the manager spent all of his time at the bar."], "output": "[['service', 'negative'], ['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["(So long that it prevented me from increasing their sales by getting more possible drinks) If i just saw my one waiter the whole night I would have known who to talk too."], "output": "[['price', 'neutral'], ['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I went here for a fun dinner with friends - they do not take reservations during the week, but we were seated pretty swiftly for a Friday night, having had a delicious glass of Spanish wine at the bar."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Wide range of dim sum and food."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food is decent at best, and the ambience, well, it's a matter of opinion, some may consider it to be a sweet thing, I thought it was just annoying."], "output": "[['food', 'positive'], ['ambience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Mojitos were good and prices werent bad but sides should be included in price as portions are tiny."], "output": "[['food', 'positive'], ['price', 'negative'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["About a half hour wait with reservations."], "output": "[['service', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We stumbled onto this diamond in the rough after our dinner plans at Schiller's were thwarted by a 90 minute wait."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["And when a waiter, in answer to a question by a diner, turns to another table and asks excuse me, do you know what this is?"], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Party of 4 after a Sunday matinee, no reservation, seated promtply, but service was slow."], "output": "[['miscellaneous', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I go to Hing Won pretty often for lunch because it is close by and the prices are right."], "output": "[['food', 'neutral'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Whether it is a weekend brunch, dinner, or just hanging at the bar for cocktails, we always have THE BEST TIME."], "output": "[['place', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Although I usually go out mid-week for lunch, I now make it a habit to stop out Thursday or Friday evening to enjoy the live Jazz band."], "output": "[['food', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Out waitress never came back to our table after taking our food orders."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["However, after speaking with the manager on the phone for about 15 minutes, the waitress said they couldn't give us any discount but would gladly give us a free pitcher of sangria."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter suggested a fantastic Greek wine that was far less expensive then we were willing to spend."], "output": "[['staff', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service is disorganised, no one gave us a menu for 15 mins once we were seated, but after that it went smoothly enough but no where near the stella performance of many half as pretensious restaurants."], "output": "[['service', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food and the value had been ok on our meal, and then after only a little more than an hour, the check was slipped onto the table for our large party, and a few minutes later, waiters began yelling at us to leave."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["sam adams on tap, french fries served out of a brown paper bag and a burger cooked perfectly."], "output": "[['miscellaneous', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When asked to explain the hostess told us she would lose money by seating us instead of them."], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The prices are reasonable but they don't have a sushi lunch."], "output": "[['price', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I asked one waitress if I could change tables and she didn't say no outright."], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Food is okay for the price, however there is definitely better thai restaurants!!"], "output": "[['food', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The whole fish was excellent--not overcooked and served in a light tomato broth."], "output": "[['food', 'positive'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After we sat down and started ordering, the waiter informed us that they were really only into serving dinners."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": [") Howver, we didn't expect to be bumped by waiters a few times during our dinner."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Sat at the bar and orderd a few appetizers, the humus and cheese plates along with some calamari - all very tasty."], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I realized that you dont have to wait hours and pay crazy prices for food."], "output": "[['price', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["On the other hand, the food was good but not awesome as had been described, furthermore I found the portions fairly small for this type of restaurant."], "output": "[['food', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After we finished our salad our waitress told us that they had run out of roast lamb and pastitichio."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Upon finishing our meal that same waitress that ignored us, suddenly appeared at our table asking if we needed our check, we were finishing our coffee and drinks, yet she was blatantly trying to get us out so that the table could be turned over."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I'm also a big fan of the chicken pizza on their new bar menu (no bread - weird, huh?"], "output": "[['menu', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Although I didn't pay for the meal (and it's about $22 bucks a plate, way over my normal eating range), I have to say that it was better than any food I've ever had in little Italy, and there weren't any touristy elements to be found."], "output": "[['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Too bad the food and service aren't nearly as nice as the decor."], "output": "[['food', 'neutral'], ['service', 'negative'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["waitress brought different food."], "output": "[['staff', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The ambience was all wrong, the bar opened into the main dining room causing the noise to flow into the room."], "output": "[['ambience', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Bartender seemed cool, so maybe I'd go back for a drink."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter recommended thZt we share a few of the appetizers; they were great."], "output": "[['staff', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["In all cases, service is slow but it's not the waiters fault."], "output": "[['service', 'negative'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Horrible service, below average cuisine, asked to leave the table before finishing our wine, and forced to have our port at the bar."], "output": "[['service', 'negative'], ['food', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Each dish is carefully prepared and is a tribute to the ingredients being served."], "output": "[['food', 'positive'], ['ambience', 'neutral'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We waited FOREVER for a table and when the appetizers arrived they were cold or frozen in the middle!"], "output": "[['miscellaneous', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Let me count the problems: music so loud it hurt, sticky unclean tables, the waitress took a long time to take our order, and then didn't bring a glass for the beer."], "output": "[['ambience', 'negative'], ['place', 'negative'], ['staff', 'negative'], ['miscellaneous', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I have been back for several dinners and lunchs and especially like the terrace when weather permits."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Best value is the sushi/sashimi lunch combo - get the large for double pieces on sushi!"], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Music was blasting (speakers located practically on top of every table), and we asked the waitress if they can turn it down."], "output": "[['ambience', 'negative'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My only quibbles are service - which was confused (we waited 10 minutes for menus), and the wine list, which is over-the-top expensive."], "output": "[['service', 'negative'], ['menu', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["food is heaven we were greeted by the hostess and sat down immediatly the space was very crowded and and we decided to order drinks promptly food can wait."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["With one drink each, apps, entrees, and three desserts (nothing great) the bill came to $200 for four."], "output": "[['food', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Part of the charm is in the earnest service; part of it is the colorful clientele; but the real charm comes from what emerges from the kitchen."], "output": "[['service', 'positive'], ['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the wait staff looks like were doing us a favor giving us service and two loud guys at the bar made my evening with my wife quiet miserable."], "output": "[['staff', 'negative'], ['service', 'neutral'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitress encouraged to come for dinner and brunch, and I followed her recommandation."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Not being familiar with Vietnamese cuisine, we found the menu descriptions very helpful."], "output": "[['food', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["i had the smallest martini, which the waiter spilled part of."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["To sum it up, the steak is indeed the best out there, but the servers and especially the hosts are big time jerks."], "output": "[['food', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Patrons can choose to be seated in the front room with a little more activity and more of a bar feel or in one of the 2 back rooms which both offer slightly quieter, more relaxed environments."], "output": "[['place', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["For dinner we decided to take our servers advice and order several items to share."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["He prepares the most authentic dishes, I guess that's why the bar is usually filled with Japanese."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene Superfine is an easygoing, instantly appreciable neighborhood hangout that boasts a kitchen staff armed with serious cooking chops."], "output": "[['miscellaneous', 'positive'], ['staff', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We waited for 1 hour each time the waitress came over to our table."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["On my last visit we arrived around 9 on a Saturday, and although it wasn't crowded, the waitress acted like we were inconveniencing her, forgot bread, drinks, etc."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When we arrived, our table wasn't ready and we waited 30 minutes in the bar."], "output": "[['miscellaneous', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter snubbed us when we asked if there was dessert (there wasn't), and my meal would have been the same price had it not been restaurant week."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Actually she want to eat sushi, but their staff reject to serve it."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["26 seats also has the most reasonable prices in NYC, it is a true gem."], "output": "[['miscellaneous', 'neutral'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["For entrees, the Ground Lamb in Spicy Sauce (can't remember the name on the menu) was perfectly cooked and had just enough kick for the average person."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The best tasting pizza by far, a long long wait for service but well worth it."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Tony's gone, sadly Ernie's passed on and now the waiters have corn rows and less finish to their chosen profession but it still maintains it's class and place as a brooklyn landmark."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitress took our menu away, without taking our food order!"], "output": "[['staff', 'negative'], ['menu', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We told the waitress a few more were coming and ordered drinks."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["One time the waitress left in the middle of our dinner."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["There is no waiting area, so we had a crowd hovering over our table, this is just testament to how many people want to eat there."], "output": "[['place', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My dining experience with friends started off very badly - 40 minute wait WITH a reservation and having to repeatedly ask for bread and water - but ended on a better note."], "output": "[['food', 'negative'], ['service', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We have been waiting for months for a 8pm reservation at this very average restaurant."], "output": "[['service', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the best thing is the atmosphere, but even that is overshadowed by the lack of taste and originality in the food."], "output": "[['ambience', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I dined at Belleville and my meal was distrupted by the manager yelling at the wait staff in the middle of the dining room."], "output": "[['food', 'neutral'], ['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["For fun on the run, sip a mojito at the bar while a portrait of the Virgin Mary bizarrely watches over you."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Seated by a moody hostess and presented a menu that included live food-samples."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["For the price and quality of the food we got, I would not dine here again."], "output": "[['price', 'negative'], ['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our server didn't have the sommelier stop by when we were trying to decide on wines, he never brought the bread we requested and didn't crack a smile the whole evening until he saw that I was paying the tab when he suddenly became nicer."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I like how the ambiance changes from the cafeteria style of lunch to a sit down dinner in romantic lighting."], "output": "[['ambience', 'positive'], ['miscellaneous', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Mostly, this small restaurant offers eggs, hot sandwiches and traditional American platters."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene The bar's upbeat Latin music, colorful stools and cocktail napkins, and a fruity drink menu are the first confirmations that Agozar lives up to its translation: A good time."], "output": "[['miscellaneous', 'neutral'], ['place', 'neutral'], ['food', 'positive'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The two vegetarian dishes on the menu were just an afterthought--why did they even bother?"], "output": "[['food', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["He was not accommodating at all and the handful of dishes I sampled that night failed to compare to anything you would find elsewhere in the city for less than half the price."], "output": "[['food', 'neutral'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["At first I was shocked by the price, but the excellent and friendly service from our waiter Jack was great and the duck salad was the best ever."], "output": "[['price', 'negative'], ['service', 'positive'], ['staff', 'positive'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu features such sumptuous fare as lobster ravioli in a light aurora sauce, double-cut grilled veal chop with an aromatic salsa verde, and octopus salad with steamed potato, red onions, and caper berries."], "output": "[['menu', 'neutral'], ['price', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["At the end of the meal the manager stopped by and said dessert was on her."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Came here for a b-day and ended up waiting so long even for a reservation."], "output": "[['service', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I would say that the atmosphere was nothing amazing, I didn't feel like the authenticity of the history of the place was nearly as prevelant as it could have been in the experience."], "output": "[['ambience', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our server never bothered to inquire as to whether or not we wanted coffee."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The hostess finally seated us at a table for two when there were three of us in an empty restaurant."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["i think friends coffee shop makes great food the service is great and they are very poilte i think that they should open more because there the best food store i ever ate from the food is addicting and you cant stop eating because it so delious."], "output": "[['food', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["But Bobby Flay really steps up at Bar Americain--his passion and heart shine through the food."], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The ravioli was the better of the two, but the serving was tiny, and the skin a bit rubbery."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I didn't even have time to finish my single cocktail and the waiter didn't even ask if we wanted coffee but instead, gave us our check without us even requesting it."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It was somewhere between our waiter not knowing what sushi came as part of the tasting platter and the copious amounts of wine that he spilt while trying to pour me a taste that I realized."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["But the karaoke downstairs is the real draw: You and your friends can sing yourself silly in absolute privacy, for nothing more than the cost of dinner and drinks."], "output": "[['food', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["after booking reservations at Danube, only to show up and not have any tables available, the Danube somelier graciously called over to Bouley and got us a table for immediate seating."], "output": "[['miscellaneous', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The owner and his sister make you feel like you've been invited over to their house for dinner."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["we all liked the brunch items we had but when we later asked if the chips were supposed to come with the meal, the waitress explained it away by saying sometimes they forget instead of apologizing and offering something extra."], "output": "[['food', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["In the winter they have the fireplaces working which immediately creates a cozy romantic feel."], "output": "[['place', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service was horrible- the 'manager' took my our order - did not write it down- and two of us were given the wrong apps and or entrees."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["On the menu says Free delivery (Minimun order $10) but I was charged a couple of dollars on both opportunities."], "output": "[['menu', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["While the recently added outdoor seating was what drew me and my friend to the restaurant, the food, service and overall experience were what drove us out!"], "output": "[['place', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The next thing we know, the bartender comes over and says (and I quote verbatim), I already gave you two beers (which he hadn't)."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Call it a bar with weak but tasty sangria and leave it at that."], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We a menu that rearely changes,e xcept for one or two specials, the quality and care they put in thier food in evident."], "output": "[['miscellaneous', 'positive'], ['service', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The simple menu focuses on standard pies and chicken-centric specialty pizzas--the Hawaiian BBQ, BBQ chicken, and bacon and chicken club--each topped with fresh ingredients like baby portobello mushrooms and roma tomatoes."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After some good food and spotty service, my friends and I were surprised to get a bill that had a 20% tip included post-tax."], "output": "[['service', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food is simply remarkable as is the fiery female master sommelier!"], "output": "[['food', 'positive'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitress interrupted us halfway through our meal to say that if we wanted dessert we had to order it then, because the kitchen wanted to close."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My friend and I enjoyed choosing from a very diverse menu of appetizers and entrees."], "output": "[['menu', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The space was so fantastic that once we heard they were serving dinner we decided to go one night and try it out."], "output": "[['place', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The wait staff had good recommendations and when i broke a wine glass, they reacted in a way to put me out of my embarrassment quickly and even filled me a new glass of wine."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If you can get service, you might enjoy the surroundings- especially the upstairs lounge."], "output": "[['service', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Waiter brought white instead of red wine."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After the wonderful anipasto tray came, it was 60 minutes before our plates were removed and dinner was brought."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["An unpretentious sexy atmosphere lends itself to the above average wine-list and a menu that can stand-up to any other restaurant in NewYork City (or Paris)."], "output": "[['ambience', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I for one do not plan to go back, there are many other places in Manhattan that have just as good food if not better, at the same prices with much better service."], "output": "[['food', 'positive'], ['price', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The decor there is nothing special, though somehow the service manages to deal with the large crowds in an efficient, friendly manner."], "output": "[['ambience', 'negative'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I've since been back for a regular dining night out, it was packed and I should have made a reservation (the wait was a little long)."], "output": "[['food', 'neutral'], ['miscellaneous', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["one of us still had wine, so the others tried to order dessert drinks, but the owner told us no because there were people waiting and the waiter said if he served us more he would be fired."], "output": "[['food', 'neutral'], ['staff', 'negative'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When we sat, our dinner was delivered promplty (Like FAST) and we had plenty of time to make The Goat, which by the way I also recommend highly (Great Show!"], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["you may have to wait a bit for service but you will not be disappointed with the food."], "output": "[['service', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The fondue was good, but not worth the very expensive price tag."], "output": "[['food', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were hassled about seating by our waiter who seemed at the end of his pony-tail, so we opted for the bar, quaintly decorated with giant fly strips."], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When we first walked in, we saw other diners wiping their plates with bread- so we though that the food was good -but we very soon realized that the portions really were so small that you really have to lick your plate clean - afterall, their dinners costs a fortune."], "output": "[['food', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When our turn came to get in, we were told that the place was full due to the Labor Day weekend and we could not get inside unless we bought a 200$ bottle of vodka."], "output": "[['place', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["South American additions to the menu, like perfectly fried green plantains and garlicky pork, are uniformly successful."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter did not take a drink order from us."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I went there about three times, one for dinner on a sunday evening which is a salsa night after dinning, the service was slow and a bit rude, the plates average some shrimp octopus and empanadas."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Get some drinks and listen to the free live music."], "output": "[['food', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I've been here several times for Sunday brunch now - (note: it helps if you're a late riser as I find the wait is always reasonable if you show up after 3pm)."], "output": "[['food', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["hard to work a buzz with the server taking so long between every round, but worth trying the signature african rum cocktail and happily surprised they had our favorite white - sancerre by the glass at this japanese restaurant."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Why would anyone ever go here when the same food (and menu) is double the price of Baba and Jaya in Chinatown."], "output": "[['food', 'neutral'], ['menu', 'neutral'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["While we were trying to have dinner, all of the waiters spent their time playing with spilled milk at the counter, not paying any attention to the diners."], "output": "[['food', 'neutral'], ['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After confronting the counter clerck he assured me the soups would stay warm as long as I wasn't walking 20 minutes to my destination."], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["(they should if you are willing to spend $400 on dinner) if the owner of this restaurant saw how the staff was acting he would fire ALL of them."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Sushi is consistently fresh, service pleasant Sushi rice is a bit hard."], "output": "[['service', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["One example, I ordered an appetizer that was not prepared as the menu stated and had to argue with waitress to get it fixed."], "output": "[['food', 'neutral'], ['menu', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We ask the waiter where's the chocolate?"], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Usually you lose food quality the trendier you go, but not at this place."], "output": "[['food', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food was good but not worth the price."], "output": "[['food', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It is not a very stylish place, but we had some of the best Chinese food we ever had."], "output": "[['place', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Aged beef charred on the outside, red on the inside."], "output": "[['food', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The bar had a hip DJ and the crowd was ultra chic."], "output": "[['place', 'neutral'], ['staff', 'positive'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["A cute restaurant and average food (with a small menu)."], "output": "[['food', 'neutral'], ['menu', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter never came by to check on us after the bus boy brought us our food."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitstaff is nice, but is pushy and seemed irritated when we did not order an a la carte side vegetable (we already had a cheese plate, appetizers and ordered 2 entrees)."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter took our drink orders and never came back!"], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After a show we had surperb steaks and had cocktails at the bar."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The new server we had was surprisingly well-versed on the menu and gave really solid service."], "output": "[['staff', 'positive'], ['menu', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu was small, but the food delicious."], "output": "[['menu', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the solitary waitress was friendly though i found her service a little slow."], "output": "[['staff', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter didn't know the menu or the ingredients."], "output": "[['staff', 'negative'], ['menu', 'neutral'], ['ambience', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Later in the evening after our meal we finally found the real owner behind the bar of the restaurant and explained to him the situation which he had been made aware of by the waitress."], "output": "[['food', 'neutral'], ['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The bar was so crowded there was no point in ordering a drink, and when we were finally seated we got no service at all for 20 minutes."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We politely asked our server for the regular menu, but were told that for large parties they could only offer us the banquet menu (would have gone elsewhere had we known)."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene Service bustles through the energetic, sprawling space with the precision of expert merengue dancers, and everyone else goes along with the flow suggested by the tall, curving ceilings."], "output": "[['service', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The ambience is diner-like and the wait staff is rushed, but at these prices, I can't complain."], "output": "[['ambience', 'positive'], ['staff', 'negative'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["But the place is so great that patrons don't mind waiting outside rather than go to another restaurant which you can find at least 10 in short walking distance."], "output": "[['place', 'positive'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Then the menu is all in Italian well I don't speak Italian so it took forever for the waitress to translate."], "output": "[['menu', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It's really great to go in here and be able to get a creative cheap drink (they have things like blueberry mohitos for $4), a $4 plate of veggie spring rolls, and be able to joke with the bartender."], "output": "[['food', 'positive'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After waiting for 90 minutes, the host gave away our table to a couple who arrived after us."], "output": "[['service', 'negative'], ['staff', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We started with some drinks on the front porch and then continued at our table with a bottle of delicious red wine."], "output": "[['miscellaneous', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They need to expand the menu some, and offer additional toppings for the pizza."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Its two massive rooms are frequented predominantly by Greeks who chow down on traditional mezze--spinach pie, feta cheese and stuffed grape leaves--and entrees--kebabs, sandwiches and pasta dishes."], "output": "[['place', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["(They even let us bring our own cake for the event, which many restaurants may not allow you too) They food was good as I only sampled so I can't really comment."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I asked the waiter about the vintages of the wines, to which he replied, I don't know, probably 2003/2004."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The filet was NOT on the menu, but my friend had the bouillabaisse, which he found delicious."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We tried explaining nicely to them that we were just finishing up a drink, and after a brief, unprofessional discussion with the two waiters, they told us never to come back again."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["A friend of mine and I bumped into this restaurant last week and it didn't look like any special place on the outside, but when we looked at the menu we decided to give it a try."], "output": "[['place', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The desserts were both essentially the same, and the service was on the slow side."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["For Manhattanites like us that are used to pretentious attitudes and expensive tabs, this place is definitely a nice change from the rest of the meatpacking district."], "output": "[['service', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Althought the menu is more expensive than your average Mexican restaurant, it is not more expensive than any other hip, increadibly well designed, bar scene and dining room in Manhattan -could be less in fact."], "output": "[['menu', 'neutral'], ['miscellaneous', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Tried it again for brunch, when the service was worse."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The manager sent us a complimentary glass of wine for the steak not being cooked like he wanted."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I guess if you order the chef's tasting menu, which is a seven course meal with an optional wine matching for $125pp then your tummy will be well satisfied."], "output": "[['staff', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It is expensice, but the portions are big and include a side, salad, nan and rice along with your main meal!"], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We explained that we had left a standard 15% on food, and a slightly smaller percentage on alcohol (At least 10%)."], "output": "[['food', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We weren't sure we'd even get a table,surprisingly the lovely hostess assured us she'd get us in if we gave her 15 minutes in the bar."], "output": "[['miscellaneous', 'neutral'], ['staff', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If it's atmosphere you want go to the River Cafe under the bridges and pay an arm and a leg for hospital-type food."], "output": "[['ambience', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Even with our reservation, they had us waiting at the bar for over an hour."], "output": "[['miscellaneous', 'neutral'], ['service', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Perhaps it's early and they will improve but service is VERY slow - took a good 25min for waiter to take our order on both visits and the second time I was one of three tables at a 5:30pm reservation so not like it was busy."], "output": "[['service', 'negative'], ['staff', 'negative'], ['place', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu is limited so I opted for the jalapeno potato soup and a romaine salad."], "output": "[['menu', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["was yelling at the rest of the waitstaff audibly enough that I was able to follow his entire tirade from where I sat in the secondary dining room."], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Ive personally tried almost everything on the menu and been amazed at the quality and presentation."], "output": "[['menu', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My friend was looking forward to her favorite dish on the menu had made reservations for the 14 of us a few weeks beforehand."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It's cheesy, great herbs,good bread and large slices But it's in a very dirty area, good for take out and bring it home kind of place."], "output": "[['food', 'positive'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The downside is that perhaps due to rice's eclectic nature, the chef has trouble cooking any single type to perfection."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["By the time you get to the table, it'll have been WELL worth the wait."], "output": "[['miscellaneous', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The steak is brought to the table soaked in grease."], "output": "[['food', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I lived next door and loved to go down for a drink at their uplit marble bar under the beautiful lighting or sit by the fireplace when the live band is not playing."], "output": "[['place', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["As if the 2 hour wait wasn't bad enough, the host/manager was so busy flirting with attractive female customers, he didn't seem to notice we had been sitting at the bar and we ended up missing his call."], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["17 for a small cup of tea."], "output": "[['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the kimchi and other sides were off, the rice had red bean mixed in, and the waitress gave us a double order of the bulgogi instead of two single orders of different meats."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After being seated took our waiter 10 mintues to get us a menu, 15 minutes to come back for our order, by the time we finally got our food it was almost 1 1/2 hour since getting there."], "output": "[['staff', 'negative'], ['menu', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After waiting forty minutes for our brunch, learned that the waitress had -- oops!"], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Teenie weenie overpriced appetizers were served at an agonizingly slow pace, one at a time 30 minutes between each."], "output": "[['food', 'negative'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the staff prefers to watch TV in the main dining room infront of their waiting customers then serve their customers."], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Perhaps I chose the wrong place, not fully appreciating that another reviewer's remark that diners here won't be rushed could translate to my timely-arrived party having to wait 'til 9:50PM to be seated for a 9PM Saturday reservation."], "output": "[['place', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["), but our waiter was had a horrible attitude, couldn't remember to bring lemon for our water, or soy sauce for our sushi rolls, the food was wonderful, but unfortunately the service ruined our visit."], "output": "[['staff', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I have never tried anything else on the menu the burgers are so good."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I had one of the worst service experiences in memory having the prix fix brunch there--waving arms, calling, asking two or three times for everything from coffee to the check."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We wouldn't bother quibbling over the price of a few drinks anyway but I wonder why they would offer if they weren't intending to back it up."], "output": "[['price', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Finally, the manager had the audacity to lock the doors, presumably to prevent us from skipping out on the bill, while one of our friends went to an ATM to get cash."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["And for families they have high chairs and waiters were really nice to my kid."], "output": "[['miscellaneous', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service sucks every time, but the food is usually tasty, even though the menu leans toward the boring and expected of French fare."], "output": "[['service', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Then, we discovered that not ordering guacamole for your table is tantamount to asking the wait staff to roll their eyes at you and then ignore you during your entire meal (I had to eventually go to the front of the restaurant to ask for our check)."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Their main chef Louie, makes the oddest specials you will ever see and the portions are quite large."], "output": "[['staff', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The wait staff were incredibly attentive, though as a warning, if you like wine, but also a little privacy, this might not be a good idea, since they have the tendency to hover a bit."], "output": "[['staff', 'positive'], ['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter brought us the desert menu, and when we refused asked if we were really sure we didn't want anything."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service was average - the waiter did not check in on our meals and did not even refill the water, but was a bit pushy on desert (we both ordered schnapps)."], "output": "[['service', 'negative'], ['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When we confronted the hostess, she told us that there were 3 of them and only 2 of us, and that the 3 women had a reservation at 8:30pm."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["For appetizers, wine, dinner, desert, great convesation, expect to spend a couple of hours."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They crumbed the table once, although it was solied the entire meal."], "output": "[['miscellaneous', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I tried the price fix and te waiter looked offended when I requested the price fix menu."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Service is wonderful- I've sat there for over 3 hours at dinner and never felt rushed to leave."], "output": "[['service', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["But then there's the sluggish and absentminded service: twice someone tried to serve us something for another table and it took a long time to get our check."], "output": "[['service', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitress was not very responsive to requests and was slow to return with drinks."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The staff is cool and friendly, and the place has been around since J."], "output": "[['staff', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The seafood is out of this world and priced accordingly."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Most of the food has a vinegary flavor (I think because of the injera)."], "output": "[['food', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["One of the managers offered us a seat at the bar to wait for a table, there we had the most amazing empanadas and red sangria."], "output": "[['staff', 'neutral'], ['miscellaneous', 'neutral'], ['place', 'neutral'], ['service', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter ignored us for ten minutes, the restaurant was empty, got our drink orders wrong, got one main dish order wrong and the disappeared for another ten minutes before we could get the check."], "output": "[['staff', 'negative'], ['food', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["While the design of the space and the atmosphere is quite enjoyable (with a great view of Union Square), the food has once again proved to be less than favorable and the service mediocre."], "output": "[['place', 'positive'], ['ambience', 'positive'], ['food', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I think they just tried to get a little too creative with the menu and actually ended up losing flavor in some of the dishes."], "output": "[['menu', 'neutral'], ['ambience', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We tried to place the order and the waiter had no clue what we wanted even though we pointed it out on the menu."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The restaurant didn't mind me sitting on their doorstep to the extent that the bartender invited me in for a drink."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["That said, I made sure to pay before we had coffee, so that the server was not waiting on us to pay; and I left a 30% tip, knowing we'd be there for a while."], "output": "[['food', 'neutral'], ['staff', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The sevice and food were excelent, but at the bottom of the menu were the words, cash only."], "output": "[['food', 'positive'], ['menu', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When the hostess finally appears she tells me that she can't seat us on the mostly empty patio because all the open tables are for dinner not drinks."], "output": "[['staff', 'negative'], ['place', 'neutral'], ['miscellaneous', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu, fortunately, matches the other locations, covering the basics of Ethiopian cooking, and includes sambosas, kifto (chopped beef often served raw), tibs (lamb sauteed with rosemary), and, of course, injera, the spongy bread that doubles as a utensil."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If going for lunch, best to go by 12:30, even if getting take-out, the place is tiny and fills up quickly, both with people eating there, and standing waiting for take-out orders."], "output": "[['food', 'neutral'], ['place', 'positive'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["That was totally acceptable and we found some great seats at the bar."], "output": "[['miscellaneous', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They were playing top 40 music the day I went which just didn't work with the whole theme, but they had the trippy sci-fi music playing in the bathroom, so it was almost right."], "output": "[['ambience', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Come-as-you-are atmosphere, jukebox, value and James behind the bar work as a magnet."], "output": "[['ambience', 'positive'], ['miscellaneous', 'neutral'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["In retrospect, that was kind of foolish, as the portions for dinner were obscene."], "output": "[['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The space and furnishings are too spartan and the service amateur and scattershot (no smiles offered here - busboy serves mains with who gets the."], "output": "[['place', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["All in all, it was a decent meal but dinner for two came to $172 with tip."], "output": "[['food', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The scene is reasonably cool but unworth more than a drink."], "output": "[['miscellaneous', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Apparently, the waitress informed us that they change the menu at 5 Ninth every few days, which kind of explains the hit or miss situation."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["had dinner there last night, max the waiter was great."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I was really excited when our waiter read off the list of specials."], "output": "[['staff', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["05 bar of melted chocolate in a cup."], "output": "[['place', 'neutral'], ['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Even without this hiccup, the service seemed very amateur--not snooty, as I've read in other reviews--just nowhere near as good as it should be given the price of the meal."], "output": "[['service', 'negative'], ['price', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Last night the dining room was crammed and seemingly only had one waiter which is ludicrous."], "output": "[['place', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["A bright spot: the server was immeadiately apologetic and whisked problem plates away, and replacements were prompt."], "output": "[['staff', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Management had always been rude, but without the great staff as a buffer, Jesse's is just another pubby place with poor decor and average food."], "output": "[['staff', 'negative'], ['ambience', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu holds no letdowns: Desserts, like a cone of stiff kulfi with licorice, ot cinnamon souffle, extend dinner's spice into the sweet realm."], "output": "[['menu', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were a large party, over 6 people, and after our initial drinks, which included a couple bottles of wine, and order were taken we did not see a waiter or a busboy again for over an hour!!"], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["In my experience, Olympic Flame, a traditional NYC Greek coffee shop, offers good value for one's money in terms of food cost but passable to rude service, depending on who you get."], "output": "[['price', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food Diners are prompted to order several shareable dishes which, considering the food isn't what's drawing most of the crowd, are surprisingly good."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Having just returned from Bourbon Street, I thought I had experienced the steepest drink prices in the US, but this is worse than N'awlins, where at least the expensive drinks cover wonderful live music."], "output": "[['food', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Everything on the menu is satisfyingly savory, from a simple pot of mussels in a choice of sauces (beer-and-bacon, creamy mushroom, or white-wine-and-garlic broth), to beef stewed with beer and prunes, to a juicy croque-monsieur, and beyond."], "output": "[['menu', 'neutral'], ['miscellaneous', 'positive'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We approached the host and manager politely after the meal but only received a simple and insincere Sorry."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The execution in the dining room was on point and we never had any service or food issues."], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were left waiting a while after our food for our waiter to return, and thus we did not have time for dessert."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Again in a group 6 months ago, the service was even worse this time, practically begging for water and other drinks while we waited an age just to get our orders taken."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere is bland and non-descript and the service is fine."], "output": "[['ambience', 'negative'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["FOOD WAS OK,SERVICE NOT SO OK,WAITED FOR THE CHECK WHILE OUR WAITER WAS GOSSIPPING,WAITED FOR CHANGE,WHILE OUR WAITER WAS GOSSIPPING."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food at Mercer Kitchen is great, flavorful and nicely portioned."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere is fun -- dark, pulsing, basement room; a place where you feel like you can relax."], "output": "[['ambience', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Waiting for a table is par for the course."], "output": "[['service', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The server seemed drunk, he forgot mixed up our food with some other table, ignored our requests for more water, drinks etc."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service is good, but the staff is not too friendly."], "output": "[['service', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The wait was not very long and the staff was great."], "output": "[['service', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Tiny slices of pie with a dribble of cream topped off the evening."], "output": "[['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["There is no service at this bar, which means no drinks or food -- ultimately leading to a very frustrating night out, and you end up kicking yourself for not leaving an hour earlier."], "output": "[['service', 'negative'], ['place', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene The bruising thoroughfare that is East 57th Street is the last place you'd expect to find an intimate, adorably decorated Northern Italian spot where it's actually possible to have a quiet, pleasant dinner."], "output": "[['miscellaneous', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["i love this pizza, its not greasy or filled with mounds of cheese, its just fresh tomatoes basil and buffalo mozz."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["This place is even good for just drinks after work (nice bar) I am going back there as soon as I get a chance."], "output": "[['food', 'positive'], ['place', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Desserts were pleasent enough, if not trying way to hard on presentation, lacking portions and interest."], "output": "[['food', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Although the food what adequate, the service was preposterous."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter, even though he was serving dinner, was SO out to lunch."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene There are two distinct personalities to the place: The loud, seemingly always-crowded bar with hanging paper decorations and dim lighting, and the two main dining areas, where the noise level and decor is notably more subdued."], "output": "[['place', 'negative'], ['food', 'neutral'], ['ambience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Although the decor is lovely as usual, service has detiorated."], "output": "[['ambience', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Food again was not just a name on the menu but very well made and fresh."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If the staff actually got it together and showed some customer service this place would be good."], "output": "[['staff', 'negative'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I let the waiter know and he offered me a free dessert."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["But it's the ambience that is the draw for me---sipping red wine and sitting under the red awning on a warm night."], "output": "[['ambience', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Customers choose flavors like sweet cream, cake batter or banana, add mix-ins--ranging from candy bar chunks and Gummi bears to hot fudge and peanut butter--then servers mash it all together on a frozen slab of granite."], "output": "[['food', 'neutral'], ['staff', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If the food is out of your price range then at least go for happy hour for a drink - although the drinks cost a bit more then the average happy hour bar after you receive one you would agree that it is worth it."], "output": "[['price', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["So, if you don't care about speedy service, go; but if you aren't in the habit of lighting your cigarette with twenties, avoid the tapas."], "output": "[['service', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our server spilled a drink on the table cloth and it was cleaned up in an instant, no mess, free drinks to compensate, and left us impressed at how seamlessly this was fixed."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food is consistantly great, but the wait is often long and the noise is often deafening."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If you want to avoid the long lines, arrive at 5:00 PM and have an early dinner."], "output": "[['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were seated fastly enough, and ordering was painless, but I got the wrong appetizer, we both received the same item instead."], "output": "[['service', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I agree with the many posters addressing an oppressively aggressive waitstaff, and I'm in particular support of the review directed at Franny's bizarrely adamant refusal to cut pizza (or provide adaquate knives/plates for us to do it ourselves)."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["finally they wanted to take our app order before taking our wine order, seemed like the waiter couldnt handle it all at once."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Nonetheless, it's an excellent pie -- and don't let the long lines scare you off -- they keep them moving."], "output": "[['food', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Across the menu, and even within a single dish, there is a stunning variety of scintillating, distinct flavors."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["In fact you can find their menu offerings at other places for better qualities and lower prices."], "output": "[['menu', 'neutral'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They may love the wacky/tacky decore, the overly gracious host, Gus, and his staff, the loads of freebies (oranges, cookies, lollies and wet naps), but the food is just mediocre."], "output": "[['ambience', 'positive'], ['staff', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["probably not worth the wait on the weekend when pomodoro is a block away but worth getting for delivery if you are in the area or for dinner during the week."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["5 minutes later the same waitress came back to have us move to the next table so she could seat a party of 4."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The margaritas were mediocre, but it did not make up for the muzak they played in the resturant nor the bad food and drink they served."], "output": "[['food', 'negative'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food as always was fantastic, and the pricing was moderate although I was not happy about the 18% gratuity being added for parties over 6, especially after the horrible service we recieved."], "output": "[['food', 'positive'], ['price', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["sushi portions were bigger than most places and service was average, far better options available in the area."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["food for fancy prices; menu consisted of one page; antipasto, and pizza; that was pretty much it; the other 3 pages was to my surprize the wine list."], "output": "[['price', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I always thought the food was decent, but not spectacular and the price fair, but no bargain."], "output": "[['food', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the waitress was not attentive at all and we had to keep getting the attention of the water servers to get more drinks."], "output": "[['staff', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Its the perfect place to take a date, start out with dinner and then stick around for dancing!"], "output": "[['place', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Waitstaff is preoccupied dancing on the bar and googling at beautiful people, but who can blame them."], "output": "[['staff', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My Moon spent all their money on an architect/interior designer and forgot about the chef."], "output": "[['price', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I asked one of the more elderly managers what we were eating and he joked that he didn't really know so he referred someone else to us who basically repeated what was written in the menu."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["In the dim lighting, I thought the portions were impressive and dug in."], "output": "[['ambience', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Meanwhile, our server was dancing and posing by the bar."], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The whole table must participate and you have to be willing to let the chef cook for you with no menu."], "output": "[['miscellaneous', 'positive'], ['staff', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When we went up to get what we assumed would be our second drink at no charge, the bartender charged us $5 a piece."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We saw problems with our waitress immediately when she frowned when we opted for tap water instead of bottled."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Waiter was very arrogant, though tha staff was attentive and when a waiter pilled a glass of water on one of our guests, the hostess ran with a dry cleaning voucher even though we did not make a big deak of it - just an accident and only water."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["For the money, it's a dependable and fun place to get sushi - bring friends and share the 2 for 1 rolls (they have to be 2 of the same."], "output": "[['price', 'positive'], ['place', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service was lacking a bit, we waited about 20 mins for a waiter and water to come to us once we were sat and we had to ask for everything twice, even drink orders - I think maybe we just got stuck with a bad waiter though."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When I asked the manager to remove the coffee, she did so without question, but never asked why and never followed up on the issue (she was far too busy flirting with the male waiters)."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We both orderd drinks that we never recived, but were charged for, and when we said something to the waiter he rolled his eyes and asked if we wanted them anyway (after we were done eating and more than ready to go."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["waiters were very nice, they dont take reservations during the week end, we waited at the bar with some sangria, Very good experience, loud music but we were able to communicate easily, overall i recommand this place to groups and dates, Will be back more often!"], "output": "[['staff', 'positive'], ['place', 'neutral'], ['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I discovered recent new management has made major improvements at this location ie the bar, dining areas, party room and bathrooms and keeping the kitchen open after 11PM."], "output": "[['staff', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I would not suggest dining here unless you get a different server."], "output": "[['food', 'negative'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Decor is old, but the bathrooms are clean and updated."], "output": "[['ambience', 'positive'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After having the table cleared and recieving fresh warm plates, we shared the Chicken Tikka Masala and the Chicken and Lentils."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I will say that often times they make their drinks very strong (may tell your bartender / waitress to keep it mild)."], "output": "[['food', 'negative'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food is worth going for, but the boys in behind the bar in the lounge are what keep me coming back!"], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The server spilled beer on the table when he poured it; he dropped ice cubes for another one of our guests and water everywhere else."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The only downside was the service was slow and our waitress kept forgetting to bring our drinks."], "output": "[['service', 'negative'], ['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["too bad that the 2 sushi chefs have become a bit too busy to chat away with the guests at the counter, but they try and hey, we are here for the food !!!"], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": [") I'm sticking with Cafe Mozart--which has the same desserts, bigger slices, and lower prices!"], "output": "[['food', 'neutral'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["There is a litte bit of a wait on the food, but it is well worth it!"], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitstaff is charming and knowledgeable about the menu."], "output": "[['staff', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We got up from the bar and got pushy with the hostess and finally were seated at an excellent table."], "output": "[['place', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our hostess was more concerned about the appearance of the banquets than wether we had the right menus."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The second time we went the waiter didn't put in our pizza order!"], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Atmosphere in the formal room was nice, but the informal dining room was extremely loud which ultimately made the formal room louder than my perference."], "output": "[['ambience', 'positive'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We showed up and waited 30 minutes in line 30 minutes to get our drinks -after we asked twice, the service was the worst I've had in nyc."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I tried almost everything on the menu, but my fav is the pumkin raviloi, too bad it's only seasonal."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It was more than enough food even though the portions are tiny."], "output": "[['food', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The place was small and simple, but I never cared about service or decor."], "output": "[['place', 'negative'], ['ambience', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The bill came out to like $100pp, and noone touched their food, and drinks were left untouched because after the first bite/sip you want to never touch it again."], "output": "[['price', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It is a small restaurant so without reservations, there can be a long wait."], "output": "[['miscellaneous', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Additionally the bar upstairs is picturesque and spacious, even though the techno music is horrible."], "output": "[['place', 'neutral'], ['ambience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The ensuing dinner was definitely worth the wait; I'll be dreaming about chef Jodi Williams' extraordinary fried squash blossoms for a long time."], "output": "[['food', 'positive'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Beers on tap were pretty good and we had a great waiter but the food left much to be desired."], "output": "[['miscellaneous', 'neutral'], ['staff', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["But the service, though invariably genial and helpful, can be weirdly haphazard -- waiters disappear mysteriously, only to reemerge just when you've decided their shift must have ended -- possibly an understaffing issue?"], "output": "[['service', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["on the food-front while adding just enough of a civilized atmosphere where you won't worry about either your neighbor or the wait staff biting off one of your fingers."], "output": "[['ambience', 'positive'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I think that argentine cuisine can be match more interesting better that the insipid expirience that I had in this overpriced place."], "output": "[['food', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["DINERS serve better french toast than Balthazar."], "output": "[['price', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Arrive at 7:00pm, the waiters didn't give us our menus till an 1 1/2 hour later."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The hummus was not flavorful and when we ran out of bread and asked for more, it never came."], "output": "[['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["That's almost enough to prove its legitimacy to me, but eating there, both for a quick slice and sit-down for pasta with my family has always been a delicious, inexpensive and fun experience."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I love the decor but would not recommend sitting in the communal tables unless its a very big group, much more fun getting a table and people watch while you chomp on your $20 palm sized truffle pizza."], "output": "[['ambience', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Then another pleasant surprise - the menu said we had to share the entree for each couple."], "output": "[['menu', 'neutral'], ['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I can't imagine how small the fish portion on the $10 lunch menu must be if I got the large one."], "output": "[['food', 'negative'], ['menu', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food Most restaurants with more than 250 items on the regular menu don't do any of them particularly well."], "output": "[['food', 'neutral'], ['menu', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitstaff was helpful but watch out, after you pay your hefty bill managment will ask you to leave if they think you've lingered too long."], "output": "[['staff', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It's too loud and the cheesiest music is played throughout the meal."], "output": "[['ambience', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Yellowtail tuna carpaccio, lightly dressed with a hint of mint, sings of summer, and crab salad partnered with sweet-hot mango mustard and greens hits all the right flavor notes."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu alternates between typical American fare (salads, potato skins, Angus burgers and grilled chicken) and modestly international cuisine like fajitas, wraps and pot stickers."], "output": "[['menu', 'neutral'], ['price', 'positive'], ['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The pro's: Good ambience,service The Con's: For the 4 to 5 star price (200 dollars for 2 people which included 2 drinks each, an appetizer, main course, and a hsared dessert), the food and presentation was just average."], "output": "[['ambience', 'positive'], ['service', 'positive'], ['price', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu had some slight twists to conventional upscale Mexican."], "output": "[['menu', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["my one complaint is that when we were finished with our dinner, it took an abnormally long time for our waitress to get with the program and bring us our check."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service was average and the tables are really close together (but who cares when the food is this good)."], "output": "[['place', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["In Short This restaurant, an offshoot of the celebrity-besieged East Hampton eatery of the same name, is enlivened by a copper-topped bar, an on-display wood-burning oven and a royal blue oceanic mural running along its walls."], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My friend was a vegetarian and the staff went out of their way to provide her with a special entree."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They ended up cramming 10 of us on 3 small tables, then taking forever with our food."], "output": "[['place', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["For dessert we split the combination platter, which had rather small portions but they were good."], "output": "[['food', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If you go in, make sure to listen to the unbelievably loud microphone that the folks at the counter use to dictate orders to the cooks who stand about two feet behind them."], "output": "[['place', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Service was not snooty and you'll be treated the same whether you order one of the $150+ kaiseki dinners or a single entree."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Unfortunately, that lunch can take a loooooong time as the waiters seem to forget food orders, forget drink orders, and forget to refill water glasses."], "output": "[['food', 'neutral'], ['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Ordered a beer from the bartender, she opened it and the told me that she didn't know the price !!"], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food Recalling an era of calorie-defying decadence--hard liquor, red meat, cigars and mammoth portions--gluttony is the operative word here."], "output": "[['food', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Personally, I like my food fresh, so you just have to tell the waiter that you would like to order by ear."], "output": "[['food', 'positive'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The tasting menu experience lasted close to three hours and included six or seven food courses and three desert courses."], "output": "[['menu', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My partner had ordered an appetizer that was no longer available; the waitress did not inform us when reviewing the specials."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["i went here on a whim and found out you could get sushi for half price kind of like happy hour."], "output": "[['food', 'neutral'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It's called OYSTER BAR, and yet no oyster selection at all!"], "output": "[['place', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They kept the chef, margarita machines, and practically the identical menu from Miracle Grill (the restaurant that formerly had the space); how is it that everything here is so much worse?"], "output": "[['menu', 'positive'], ['food', 'neutral'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu was filled with of course the standard sushi fair, but the real gem was the unuusal and creative combinations of sushis and sauces and other ingredients they had as well."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The complete and total rudeness and frustration surrounding this place started with the hostess calling us in the middle of the afternoon asking if we could change our reservation."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Not the most adventurous nor exquisite food, but generous portions (at least, on the 3-course prix fixe) that were faultlessly executed, complemented by a varied wine list ranging from that special bottle for a celebratory splurge to excellent choices under $50."], "output": "[['food', 'negative'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The only redeeming factor of the night was the dessert which was very good but certainly not worth the cost of an overall horible experience."], "output": "[['food', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter must have been a 'stand-in' because he did not know the menu, choices or basic service protocol (bread plate on the left)."], "output": "[['staff', 'negative'], ['menu', 'neutral'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If your friends persuade you to check this place out, I suggest that you order all of your drinks, apps, entrees, desserts, and the check up front, because you'll never see your server again."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["So are cooked plates: Marinated Kobe beef practically melts on its skewers, soy-buttered scallops collapse with sweet brine and Chawanmushi custard, quivering in eel-soy broth with black truffles and foie gras, is over the top."], "output": "[['miscellaneous', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I've been here twice for brunch, and I found the ambience and food to be much better than the overly-hyped Kitchenette next door."], "output": "[['food', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Not the ideal spot when you're really hungry -- the plates are tiny and the prices not (like every other upscale tapas place)."], "output": "[['miscellaneous', 'negative'], ['price', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter knew about every item on the menu and explained it very well."], "output": "[['staff', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitress only stopped at our table to take our order and pick up the check."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We got there before our reservation and the seated us quickly."], "output": "[['miscellaneous', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene Tucked away on the second floor of a small, nondescript Madison Avenue building, Caviar Russe feels more like a private club than a restaurant."], "output": "[['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["While the server offered nothing, the host apologized, and said that he hoped that I would return again, perhaps for brunch."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food was good, the service was fine, and the place has a lot of visual atmosphere, but I would not go back unless I was stuck eating with someone I didn't want to listen to."], "output": "[['place', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I noticed many of the other comments had negative things to say about the service and food - my thoughts and suggestions are: eat at the bar to avoid a rude waiter or bad service here and Artisanal's reputation is based on the cheese, get the CHEESE and not the steak or whatever."], "output": "[['food', 'neutral'], ['place', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["However, the service has SIGNIFICANTLY declined since they expanded into the back room."], "output": "[['service', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waitress was very nice, not snotty - she even gave us a free apertif after the meal (and left the bottle on the table)."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Nice decor - but the place is so crowded and noisy you can't enjoy it."], "output": "[['ambience', 'positive'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter, of course had no knowledge of the yet to be produced wine list and no wine steward or manager bothered to come by the table to check in."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The prices seemed reasonable with entrees ranging from $14-$25."], "output": "[['price', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The only complaints (minor) was a 15 minute wait when we had a 10 PM reservation and the tables are pretty close to one another."], "output": "[['service', 'negative'], ['miscellaneous', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["What I liked the most is that the staff listened attentively to what I asked for and my meal was prepared EXACTLY the way I asked, what a treat."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Although we had to wait a long while and the hostess was very busy behind the bar, she was very apologetic and sincere which made it feel ok to have to wait."], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The wait staff is very attentive, and you can smoke at the bar while enjoying the view of the river."], "output": "[['staff', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the prices are right and i strongly recommend this place for any time of day: early breakfast or late night snack."], "output": "[['price', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Also, if you order a dinner, plan to have leftovers for the next day because the portions are HUGE, the salad that comes with a meal is large enough to be a meal itself."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["-the bread served was cold -the choices for restaurant week was very slim (no meat dish except pork) -there were no chef's treats or delights -the food was ok but not up to the quality expected There are more exciting, romantic restaurants in the city to visit."], "output": "[['food', 'negative'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Lovely place with the kind of Chinese food I like -- clean presentation, sizeable menu, and a bit of a French twist."], "output": "[['place', 'positive'], ['menu', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter showed up two minutes later to take our order and showed up with our drinks 25 minutes later and they were not crowed."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Food is decent but portions are so tiny and the whole meal is served on huge plate which makes it look even more ridiculous."], "output": "[['food', 'positive'], ['miscellaneous', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Went to Public last Saturday, couldn't get a table so the lovely host suggested that my partner and I dine at the bar."], "output": "[['miscellaneous', 'neutral'], ['staff', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I am an extremely low maintenance diner and the staff at this restaurant managed to insult my dinner party and refuse kitchen service minutes after seating us and informing us that the kitchen was open."], "output": "[['place', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food came out wrong, the waiter was no where to be found and the wine showed up at the end of the meal."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Aside from the service being slow, the place was packed w/ a good crowd and music was amazing."], "output": "[['service', 'negative'], ['place', 'positive'], ['miscellaneous', 'positive'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When after 2 hours we did ask for our entrees, the waiter and busboy were both extremely rude."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitress came three times: to take our order, to bring the order, and to bring the check."], "output": "[['staff', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It's got above-average diner and italian fare, and it's right near the subway."], "output": "[['place', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The small bar is always packed with people, and you have to constantly contend with waiters asking you to move as they navigate through the crowd to make it to their tables."], "output": "[['place', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After making reservations almost a month in advance, I was very disappointed to be seated in a secluded area for dinner next to the sushi bar and KITCHEN!!!!!!!"], "output": "[['miscellaneous', 'neutral'], ['service', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I mean no disrespect to the owner, just constructive criticism - improve the decor and dine-in service, but DON'T change the portions or the recipes."], "output": "[['ambience', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Recommended to those who want to try a different setting for a diner."], "output": "[['ambience', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Although the waitress had clearly our reservation on her book, she told us somebody arrived one minute ago and being first to arrive, he could have our table."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["He did do the service part well enough -- brought the food, etc."], "output": "[['service', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["it is too bad because the food, ambiance, and drinks were great but they need serious help on the service."], "output": "[['food', 'positive'], ['ambience', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Hey - What better excuse to sit at the bar and try another one of their fantastic drinks."], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Come in the evening, sip a glass of wine, or two, and enjoy the great live jazz along with your dinner."], "output": "[['ambience', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Hunan Delight has one page in their menu full of Vegetarian dishes."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Starting off with an excellent carafe of Cotes du rhone suggested by the waiter, we soon ordered a few appetizers like the steak tartare, the escargot and the goat cheese tart."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Although there were many open tables, the manager insisted my party wait at the bar for over one hour."], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["it would be better to place the bar closer to the front of the restaurant and away from the tables."], "output": "[['place', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We tried the Tasting menu', and the manager offered to select the items to be served after taking inputs from us ( Choice of meat, allergies etc."], "output": "[['menu', 'positive'], ['staff', 'positive'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After they were done poking and prodding our food, the waiter took it right from their table and tried to give it to us."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I have worked in the restaurant industry for 5 years, and so am understanding of things out of my server's control, and I have never experienced such poor service!"], "output": "[['staff', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Don't go for the decor or the location, go for the food!"], "output": "[['ambience', 'negative'], ['place', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The hostess failed to inform us of that the restuarnt was hosting a private company party when we made the reservation."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We waited forever for our orders, our drinks came out AFTER our food, we never got refills on water, we had to ask like three times for extra dressing, and our waiter was rude."], "output": "[['food', 'neutral'], ['ambience', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We asked the chef if it was possible to have two different tasting menus, to which he was quick and eager to comply."], "output": "[['staff', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service was very rushed and as we were finishing our drinks and paying our bill, the owner asked us to leave so he could seat other people at our table."], "output": "[['service', 'negative'], ['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter was great and we even got drinks and some food courtesy of the cheff- maybe because it wasn't so busy when we went."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The manager very politely told the drunk man that he could leave and then gave everyone on the resturaunt a free glass of port for having to witness it."], "output": "[['staff', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Oh, you should have seen the look on the waiter's face when we told him we didn't want any coffee after the meal."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["All the dishes that we had at our table were consistently good, although not great (nor poor, either)."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Delivery portions are bigger and 2 can easily share 1 entree."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["No specials and no crab limited the menu choices, and the toast for my (very average) foie gras arrived 5 minutes after the rest of the food, and was cold and burnt."], "output": "[['food', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If I went back, I'd have dinner in the bar--better service and even better atmosphere."], "output": "[['food', 'neutral'], ['place', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We felt the waiter and captain rushed us through our meal."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The worst occasion, and the final straw for me was when myself and four friends were told that we could have a table if we moved away from our stools at the bar."], "output": "[['food', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Servers are layed back, but food arrives rapidly."], "output": "[['staff', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Wine has had C-Tails at the bar(SUPRISE!!!)"], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I went there for lunch a couple of times but whenever I went there (even though we pinpointed our order on menu), waitress messed up our order and they never said sorry."], "output": "[['food', 'neutral'], ['menu', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Xunta's tapas dishes were great though a little pricey for small plates."], "output": "[['food', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Their Billy-Cheese steak sandwich is very good, too, but last I was there it wasn't on the menu, at least not for dinner anyway."], "output": "[['food', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We had the tasting menu -- which was not a meal!!!"], "output": "[['menu', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We had a very nice and entertaining waitress who was very much on top of our table."], "output": "[['staff', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Portion was just a bit small compare with other restaurant but the price was lower than usualy as well (7."], "output": "[['miscellaneous', 'negative'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We actually gave 10% tip (which we have never done despite mediocre food and service), because we felt totally ripped off."], "output": "[['price', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We sat soaked in red wine for 20 minutes eating our meals w/o the wine b/c the server saw us like that but did nothing until we stopped him."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I've eaten at this Zen Palate location a few times, and each time have had the same reaction- I feel the food's sub-par, but decide to give it another chance and order something else."], "output": "[['place', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Diners at the bar watch busy chefs scoop lobster salad onto warm brioche rolls."], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food and appearance of Alfama is quite nice but the menu is a bit deceptive in that my grilled shrimp (Peri Peri) consisted of an entree plate with three shrimp, no veggies or starch."], "output": "[['food', 'positive'], ['menu', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My vegetable Napoleon was good; although i first got the veggie burger because the waitress mis-heard and stood my friend up for another 15 minutes of waiting to have it served."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Went with a large group of 7 ladies before a show, and the staff was extremely obliging, even when one person was late and we had to wrap up her dinner to take to her."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["A cocky, arrogant and shockingly condescending manager (all of 22 years-old) then told us we should leave the restaurant if we wouldn't move to the bar."], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Then the huffy hostess when we asked to be seated at a table not directly on-top of another couple."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waitress left halfway through dinner, without explanation, and was replaced by another waiter."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Service during either brunch or dinner could be quicker and more attentive at times."], "output": "[['service', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["You can undoubtedly get better food and service for the price at other places, but certainly not with those views!"], "output": "[['food', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Not including the tip for our server, who we saw twice in an hour?"], "output": "[['price', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Other than its impossible reservation (no matter how many months you call in advance, the only available time slots for dinner on a Saturday are always 4:45 or 9:45), Peter Luger is worth the drive over to Brooklyn."], "output": "[['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Reservations are no guarantee of prompt seating, have a pre-game drink, pop a xanax and you can handle the drama of having a res and getting no love from the hostess."], "output": "[['miscellaneous', 'neutral'], ['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They were out of cherry, so we got a few slices of apple and one key lime."], "output": "[['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I have no complaints about the wait or the service but the pizza was not at all something to write home about."], "output": "[['service', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["and you have to order through a pane of bulletproof glass, but the fact of the matter is, after a night of hard drinkin', college style, nothing hits the spot like a big box of inexpensive chicken and fries."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The snooty manager asked us to leave and gave us our check in the middle of our meal."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Maybe go there for the view, but don't bother eating there, go to the bar."], "output": "[['miscellaneous', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Service was prompt, although at times the waiters seemed to be spending more time dealing with the overflow from the bar than the diners (ever heard of cocktail waiters)."], "output": "[['service', 'negative'], ['place', 'neutral'], ['price', 'neutral'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Its good to go there for drinks if you don't want to get drunk because you'll be lucky if you can get one drink an hour the service is so bad."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My companion went to the bathroom and overheard the waiter singing near the back of the place The cappuccino machine is broken, It's broken."], "output": "[['place', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I am vegetarian - so this review applies only to the veg portion of their menu."], "output": "[['miscellaneous', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["after such a strong showing, dessert was a letdown per our waiters recommendation, we ordered the raspberry softie the coconut-stuffed apricots the softie tasted like a mixture between cough syrup a starburst, whereas the apricots were extremely sour."], "output": "[['food', 'negative'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Asked for wine recommendations and the waitress told me her favorites and described them in detail - I don't encounter this much in NYC."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["That being said, they do have a nice lounge area downstairs where you can just hang out, have a seat, and relax (no more waiting out in the cold or at the crowded bar)."], "output": "[['service', 'negative'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Just expect to wait a good twenty minutes before they take your order (even when the restaurant is half empty), you'll have to ask at least 5 waiters and a manager for coffee before they bring it to you and when they bring your orders out wrong, expect the manager to side with the chef and not you."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were not seated by a hostess (and as a result didn't receive menus or water for a good while) and were rushed out as the restaurant closed an hour after we arrived."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Seconds after we permitted our half-eaten fattened goose livers to be whisked away, our waitress materialized, bearing two cold drinks and the chef's profound apologies for the dish - a completely unneccessary but vastly appreciated gesture."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When one of our party brazenly asked to substitue a flavor of gelato for one of the desserts on the menu, the waiter snobbishly told us that, Mario and the chef don't like to do that."], "output": "[['food', 'neutral'], ['menu', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Remember the 80's when you have to wait 1-2 hours for a table even though you have a reservation + the wait staff treated you like the idiot that you are for paying $2-300 per head for this treatment, then you should definately come to experience this jewel!!"], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["While the place looks rather small and undecorated, I will definitely go back just for the food."], "output": "[['place', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I love the complimentary hot salsa and fresh chips that they put on the table !"], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After ordering our food was brought to our table very quickly despite the huge crowd."], "output": "[['food', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I guess Mars 2112 keeps the food bland for the family fare, but it only serves to detract from its overall experience."], "output": "[['food', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We had a plate of smoked meats, some stinky cheeses (that's how they were described on the menu), delicious marinated anchovies, and crostini with various vegetable toppings."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["A good restaurant would have at least comped desert or sent over a round of drinks for such a long wait -- we didn't even get an apology from a manager."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Actually, upon being seated in the tea room, we weren't even offered the tea menus and had to ask for it."], "output": "[['place', 'neutral'], ['menu', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene Behind the often-fogged windows at this small restaurant is a homey atmosphere, full of smiling employees and Filipino families crowded around simple red tables."], "output": "[['miscellaneous', 'neutral'], ['ambience', 'positive'], ['staff', 'positive'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The staff was knowledgeable about the cuisine and answered my dining questions with professionalism and style."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I like to drink a variety of teas, but I've had some here that are really weird that I would avoid next time."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Sit at the bar, order a glass of wine, and grab an appetizer: they'll also bring you olives, parmesan cheese, a huge loaf of delicious bread and 3 dipping sauces."], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We recently went for dinner with two kids and the staff were very accomodating even without reservations."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Service was slow (20 minutes wait time before they came back with our drinks, not including 10 minute wait for them to take our drink order)."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["But, as I said, it's a dive bar, so it's not someplace you'd take a high-maintenance individual."], "output": "[['place', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["sometimes i've just ordered arepas and empanadas for my meal; other times, i've split a dinner entree and an appetizer with a friend and been satisfied, since the portions are so huge."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Go there for dinner this time and find it unusually bad in taste and not pleasent service at all."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["my table of four was not totaly neglected, but there was a lag in how promptly we were being served."], "output": "[['miscellaneous', 'negative'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter was constantly puching us to have drinks, he told us that we were not ordering properly and insisted on bringing to the table his recommendations."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Avoid this restaurant on a busy night at all costs -- they have yet to learn how to make the appropriate number of reservations; the front of the house and the managers are amateurs."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When we finally had to see the manager because I had lemon juice spilled on me from the waiter- she even took over 10 minutes to come to the table."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Worth the trip and the wait (and the higher than average price)?"], "output": "[['service', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The journey may be long and the wait may be longer, but there is nothing that could keep me from this pizza."], "output": "[['service', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My friend ordered the scallops which were served in a light red sauce that was complemented very nicely with atichoke palms."], "output": "[['service', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Service is not particularly warm, but I've gone back again and again (for dinner) over the years on an almost monthly basis."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["However, another server kept hovering over our table, wanting to take our half-finished plates away."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When questioning our server about a certain dish, she kindly brought over the Union Sq."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Instead of going to a fun lounge after dinner, as planned, everyone had paid so much, that we went to a dive bar for the rest of the night for cheap drinks."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food The versatile Austrian menu, fused with French and American, rewards both high and low-end appetites: rich, cheese-laden onion soup, grilled Gruyere and country ham sandwiches and big-bunned burgers are as satisfying as velvety liver terrine with kumquat-cranberry compote, speck and sausage charcuterie and inexpensive cheese plates."], "output": "[['food', 'positive'], ['menu', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Bar has, french fries, bunch of different vegs and fruits, sushi, ribs (not great, wait for the waiters that come around with the meat)."], "output": "[['place', 'neutral'], ['food', 'positive'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter seemed astounded that I ordered no wine or alcohol -- just water -- with my meal."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food and drinks held up to eatery's rep and the service was just as good if not better."], "output": "[['food', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Those who choose an omakase (chef's choice) menu will be happily surprised with accents of jalapeno or swaths of homemade sauce cleverly accenting rolls and sushi alike."], "output": "[['food', 'positive'], ['staff', 'neutral'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["As for the food, apart from the Chef's Omakase, the appetizers and rolls are just below mediocre for the price they charged."], "output": "[['food', 'negative'], ['staff', 'neutral'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Not only did they refuse to give me any milk but they charged me full price ($9) for plain udon noodles - no broth, veggies, or meat just wet noodles in a bowl."], "output": "[['price', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When the ice cream cake I ordered didnt hold up in their regular freezers temperature, Giovanny immediately had a server run out and got an identical cake in 15 minutes."], "output": "[['miscellaneous', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I went on a Saturday night on the recommendation of the new General Manager, Mike who also did Cheetah Club and Le Souk."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I definitely liked the vibe in the restaurant - the food is good with enough variety to please everyone - i'd say the portions were quite skimpy where it counts - meat whether fish or steak- and for those prices this is very irksome."], "output": "[['ambience', 'neutral'], ['food', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["At one point, I spilled my water glass--when I informed the waiter of this he said he would clean it up--he never got around to it."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Ok, it's not greasy steak and juicy burger good, but it's a light healthy fare, if you are into that kind of stuff."], "output": "[['price', 'positive'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food had a somewhat elevated price tag but but fair considering the Nobu origin - The cocktails highly recommended including the spide and lobster roll - we were well plated and did not encounter any arragance from the staff - maybe the other student reviewers are used to cafeteria service."], "output": "[['price', 'negative'], ['food', 'positive'], ['miscellaneous', 'positive'], ['staff', 'negative'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The only bad thing was that the third alien was so friendly and took a lot of time at the other tables, so she didn't come see us."], "output": "[['miscellaneous', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After being seated outside by the host, a waitress came over and yelled at us for taking a table that belonged to people waiting at the bar."], "output": "[['staff', 'negative'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Summary good service, bad food!"], "output": "[['service', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were able to get a table right away on Friday night, but we only saw our server twice and he failed to give us the specials, we overheard him tell the table right next to us after we had ordered and were already into our salads."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["People will literally spend their entire lunch break waiting and for what - an average fastfood burger."], "output": "[['food', 'negative'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["huuge portions, which made it much easier paying the $350 bill."], "output": "[['miscellaneous', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food Brasserie favorites are prepared by the book: Onion soup gratinee bubbles with a thick layer of Gruyere cheese, and grilled shell steak is served medium-rare, with a side of crisp shoestring potatoes."], "output": "[['food', 'positive'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Unfortunately, as we were finishing up, the manager hovered around us and asked us to go to the bar to finish our drinks because there were other people waiting."], "output": "[['staff', 'negative'], ['place', 'neutral'], ['food', 'neutral'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I adore Zen Palate - and both the formal upstairs dining room and the crowded, counter-style cafe downstair, have their pros and cons."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The last time I went to the restaurant, the waitress made me wait to take my order, then left me without anything to drink throughout the entire meal."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["There's very little on their menu if you're trying to avoid cheese and oil - not many grilled entrees at all."], "output": "[['menu', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The entree menu is not diverse, but the items on it are all very good."], "output": "[['menu', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waitress asked us if we wanted anything else, we said only the check - she quickly scooped up our not-yet finished food."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The upside of Zen Palate is the open kitchen, which allows you to watch the cooks at work and removes fears of who only knows what the chefs are doing in the back."], "output": "[['miscellaneous', 'neutral'], ['place', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Waiters had to reach over people to deliver food."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The bar bites weren't anything special (we had calamari and wings, very ordinary), but our dinner was phenomonal, as was our service."], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It took the waiter over 30 minutes to get our food because the order was misplaced."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["This seems to be a big hit and draws a large crowd, so be prepared for a wait."], "output": "[['miscellaneous', 'positive'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene Though this looks like any other sushi counter, with purple vinyl booths and a koi pond in the small dining room, there are glimpses of superiority."], "output": "[['miscellaneous', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["One of my favorite places to get a cup of tea or to have a casual brunch with the newspaper."], "output": "[['food', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["(The booths remained unoccupied throughout our meal, unless you count the not-very-busy waitstaff."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["95 all-you-can-eat lunch is tooted as a good deal but a the ambiance is dreadful and you can get a terrific meal, also kosher vegetarian, in peace with service just around the corner for $2 more."], "output": "[['food', 'positive'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The place was very crowded usually it is a good indication that the food would be worth the delay."], "output": "[['place', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Low-fat and low-carb options (such as flatbread) lure in health-conscious diners, while everyone else can sink their teeth into warm, crispy baguettes piled with mesquite chicken or smoked turkey, Philly cheese steaks and more."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our server seemed to be new because he continually had to go back to the kitchen to check on menu items."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I finally cancelled our order, the waiter came back in 5 min with our plates."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu has many dishes that one can't find anywhere in the city."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Called to complain and the response was well, we didn't charge you for the falafel sandwich we shorted you."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I ordered the strip steak medium - the waiter or the chef reversed our requests."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The tasting menu was delivered at a break-neck pace, leaving no time to enjoy the wine or even digest the food."], "output": "[['menu', 'positive'], ['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The owner himself one time came to our table to clear our dishes when our waiter didn't show (a rare occurance, but it was late at night)."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food is really great but the service is absolutely horrible!"], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I went back a different night, once again I can't remember which, probably Friday and the place was a ghost town, with a corny DJ and a waitress who couldn't get my friend's drink right after several tries."], "output": "[['place', 'neutral'], ['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My next thought was god i could use a few drinks and a bathroom."], "output": "[['food', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When asked to compare between two dishes, the server said whatever you like."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Start by enjoying the atmosphere while having a glass of wine at the bar and we you are ready, go and enjoy your food!"], "output": "[['ambience', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Apparently the same hostess was also trying to kick out a group of women having drinks at a table and giving them a hard time for holding up a table."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Needing a sugar fix, my husband and I walked in here to find a wall to wall adornment of delightful confections."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["One of our diners didn't like her fish and both the waitress and the manager insisted on replacing it."], "output": "[['food', 'negative'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My friend and I were the ONLY 2 people in the entire place seated for dinner and after sitting there for 15 minutes, I had to walk over to our surly waiter and ask for menus."], "output": "[['service', 'neutral'], ['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The tables weren't bussed and they forgot to make my chai tea, which wasn't all that delicious, not was my friend's coffee."], "output": "[['place', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Don't miss the crema catalana the waiter recommended us for dessert."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The place is a little over-priced for brunch but it is a nice restaurant so that was expected Food (i had the omelette with cheddar, mushrooms and herbs), service, coffee, atmosphere were all fantastic."], "output": "[['place', 'negative'], ['food', 'positive'], ['service', 'positive'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I went for an early dinner the other night and encountered the worst service i have experienced in a long time."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The hostess told me she could accomodate my group without a reservation but we ended up waiting nearly an hour and were seated in the smallest cramped area."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Super friendly neighboorhood atmosphere where even a lady can go alone and have a drink and feel comfortable."], "output": "[['ambience', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If coming to Tea and Anthipathy (yea u heard me) during conventional dining hours, expect a good long wait on the curb till tables open up."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Thought I didn't have reservations, the hostess politely informed me that it would be a 45 minute wait and we were actually seated in 40."], "output": "[['miscellaneous', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the staff is great, but the food is just ok."], "output": "[['staff', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["And Mondays fajita are half price all night."], "output": "[['food', 'neutral'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The staff is very friendly too~ Everything is wonderful about this place except for the bathroom."], "output": "[['staff', 'positive'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["To make matters worse an hour into our dinner we see a waiter take mojitos to another table."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Bringing a large group on a busy Saturday night ,I was afraid quality of food and service might not be up to par, but we were seated promptly and the service by our waitress was fantastic considering how busy it was."], "output": "[['food', 'negative'], ['service', 'positive'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Fifteen minutes later, when we asked about our drinks, another server went to investigate and found that they'd run out of one of the liqueurs they needed and had gone out to get more -- which is fine, but it would've been nice to know."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were also seated promptly at the time of our reservation and the service was very quick and professional."], "output": "[['miscellaneous', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After 45 mins of waiting in an sans air conditioned bar, we grew tired of paying for over-priced drinks."], "output": "[['place', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["PLUS the best wine can be found in the bar but they refused to sell us a bottle!!"], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I recently attended a celebratory dinner here and I just want to warn everyone that the service is the worst I have ever experienced!"], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It's very cheap, food is great you can bring your own bottle of wine (saves sooo much money) The waiters will uncork it bring you glasses too !"], "output": "[['food', 'positive'], ['staff', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene Inconspicuous Bottino is an ideal stop for a light lunch or full dinner while gallery-hopping through Chelsea."], "output": "[['miscellaneous', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our lovely waiter sent us off with scones for breakfast the following AM!"], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter took his sweet time bringing the menus and telling us the specials and it wasn't until almost 10:15 that we put our order in."], "output": "[['staff', 'positive'], ['menu', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["On the menu, there are many inexpensive snacks, drinks and meals to choose from."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The presentation was clever, and the food tasty however the service that accompanied it was so slow it made us feel neglected."], "output": "[['miscellaneous', 'positive'], ['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I especially love the korean dish's they add into there menu consider its 2 for 1 its hard not to resist with asian cuisine being so expensive in all in New York."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["While the people here were nice and the service was very good, the food was not very good - it was extremely greasy, the place did not offer alternatives such as egg whites and PAM spray instead of oil, coffee was average Crystal Rock Office Flavored Coffee - not the good coffee."], "output": "[['service', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["SQC is great in the evening, the light is excellent and it's perfect to sit at the bar, eat oysters on the half shell and have a glass of wine."], "output": "[['ambience', 'positive'], ['place', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["great trendy spot for a night out but to be honest the food was not worth the cost."], "output": "[['miscellaneous', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I would have told the wait staff if anyone had asked me if I enjoyed my meal, but no one asked."], "output": "[['staff', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Upstairs they have an entirely separate hostess, as if it was a different restaurant all together, where after being asked once again if we had a reservation we were seated in a small seat, in the corner, of a practically empty room."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["And although I've noticed that the prices have gone up a little since they opened, it's still a great menu."], "output": "[['price', 'negative'], ['menu', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Service was a little but flawed, (they brought us beers without the glasses brought the main course out before cleaning off the appetizers) but nothing that would ruin your evening."], "output": "[['service', 'negative'], ['food', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["With only 2 tables occupied in the whole place, the waitress spent her time behind the bar and only came to help us when we got up and asked her to."], "output": "[['place', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["As we attempted to digest our meal and browse the dessert menu, the same staff members approached us to move along our order."], "output": "[['food', 'neutral'], ['menu', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I went there for lunch with co-workers and found the service to be prompt and very friendly."], "output": "[['food', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They moved us upstairs to an area where they were setting up for a private party -- we had no server, and had to flag down people setting up for the party to get us drinks, silverware, water, etc."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When we received the bill, we asked the manager to do something about the drinks, considering how poor the service was and her reply was, Well, you got them!"], "output": "[['price', 'neutral'], ['staff', 'positive'], ['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I had a party of 9 reservation and was very disappointed at the service."], "output": "[['miscellaneous', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our apetizers took quite a while to be served, in fact, while all the other tables that sat way after us were being served I asked the waiter what happened to our appetizers, the calamari was tough; The entrees were tasteless and really!, one have to be really bad to mess a simple pasta dish."], "output": "[['food', 'negative'], ['place', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Expect a crowd while waiting, but they seat quickly."], "output": "[['miscellaneous', 'negative'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I must admit the times my family (6 or more) have had dinner there the service seemed to forget us after serving the main course."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were seated promptly, and after an inordinate wait, somebody took our drink order and disappeared for half an hour."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Although the atmosphere was lacking, I could definitely recommend a trip to Esca for the fish alone!"], "output": "[['ambience', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Though it might be a wait and the service might leave a little to be desired, anyone that has ever eaten there agrees that the food is worth it."], "output": "[['service', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Best Baked Ziti in the area, great classic NY pizza."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We had reservations, and so did the strangers, and yet the management claimed the other tables were reserved."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene North Square's discreet, sedate decor appeals to the largley older crowd occupying the dining room whilst a younger set parties in the back bar."], "output": "[['miscellaneous', 'positive'], ['ambience', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When I asked the waitress she told me it was because I ordered pancakes."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We went out on the town with the idea that we were going to mingle with the in crowd, you know, go to a place where you pay an outrageous cover charge, have to wear all black to fit in, and pay $12 for a watered-down martini, and if you're lucky, have a good time."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Much has been made of Island's lack of french fries--space and cost are cited on the menu--but an order of thick crispy salt and vinegar chips almost satisfies the craving."], "output": "[['food', 'negative'], ['place', 'neutral'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Service was atrocious: appetizers came out 3 minutes after we ordered, and 10 minutes before we finally tracked down the bottle of wine we had ordered, the waiter rushed us from start to finish, we had to repeatedly track down someone to pour us more wine since it wasn't at the table, etc, etc."], "output": "[['service', 'negative'], ['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["mapQuest before you go and you'll arrive early enough start off at the bar with a fabulous old school cocktail."], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The white tablecloths covering closely-packed, old wood tables; waitresses with accents and up-turned noses; warm firelight ambience; boisterous crowds drinking wine -- it's all here."], "output": "[['staff', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My appetizer of endive and bleu cheese salad was a surprisingly large serving which balanced the striped bass entree (served on a bed of vegetables)."], "output": "[['food', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When we got there, they refused to seat us because our 4th wasn't there yet-even thought there were only two other people there and we assured them we would order some starters and drinks."], "output": "[['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Great roofdeck, nice group of 30 somethings, but no music, kind of quiet."], "output": "[['food', 'positive'], ['ambience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Though the service leaves a lot to be desired, and the waitstaff runs around like chickens without heads, the beer is cold, the sake is hot, and the sushi is out of this world!"], "output": "[['service', 'negative'], ['staff', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["People waiting for tables stand at a drink rail next to large windows which open out over a leafy garden in the summertime."], "output": "[['service', 'neutral'], ['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When the group arrived for the Noon lunch the restaurant was only partially set up and the group was forced to eat lunch while the staff noisily set up the restaurant around them."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["About 10 of us came here for drinks last friday, the atmosphere was good for chatting and hanging out, but not enough lounge or bar space, they should open up the back area w/ more loungable chairs or booths if they want to catch any after dinner sort of bar crowd."], "output": "[['food', 'neutral'], ['ambience', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiters can shoot off a 5 minute long list of specials, and they know the menu very well."], "output": "[['staff', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My friends and I went to dinner last weekend and had a great time."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["beside i have to wait long time with my food, waiter service ok but unfriendly."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter said 3 words to us, wisked away our food as we were finishing, and the maitre'd could not take his eyes off our table waiting for us to leave."], "output": "[['staff', 'negative'], ['food', 'negative'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The only downside was our waitress -- she forgot to order one of our side dishes, was not attentive, and then gave us our check before we finished our bottle of wine."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I spent more time looking for a waiter than I did enjoying my meal."], "output": "[['staff', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After sitting at the table with empty glasses for a 1/2 hour, we had to ask the busboys to get us drinks as our waiter was nowhere to be found."], "output": "[['miscellaneous', 'neutral'], ['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The texture of their flat noodles is something that has to be experienced to understand."], "output": "[['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The only thing that was a little annoying was that the hostess didnt want to let us finish our first drinks at the bar and kept rushing us to sit down."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["You get plenty of food for the price, enough leftovers for lunch and they actually serve garlic chicken with lots of chicken and chinese vegetables."], "output": "[['food', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We heard two different servers telling tables about these specials, and when we asked to hear them, they wouldn't tell us them."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the service was slow took ten mins to get me a glass of water."], "output": "[['service', 'negative'], ['miscellaneous', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The freshness of the ingredients down to the perfection of the crust, it is truly the best."], "output": "[['food', 'positive'], ['ambience', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu looked good, except for offering the Chilean Sea Bass, but the server does not offer up the specials that were written on the board outside."], "output": "[['menu', 'positive'], ['food', 'negative'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter, and someone at the next table, were both correct when they said that the lobster was delicious, but I though the price was a little steep."], "output": "[['staff', 'positive'], ['food', 'positive'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The wait staff is very attentive; though if the place is really packed, then you may have to flag someone."], "output": "[['staff', 'positive'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They were rude, didn't know their drinks and were unable to demonstrate any professionalism in their service mentality."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["But the service was absolutely terrible, and we watied 45 minutes for food."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Yes, the prices SEEM afordable, but the portions are so small that you end up spending $100+ just to fill 2 people and get a couple drinks."], "output": "[['price', 'positive'], ['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food was good but we were dissatisfied with waiting too long for a uncomfortable table."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I asked the waiter to move us to another table because we didn't want to rush our meal."], "output": "[['staff', 'neutral'], ['miscellaneous', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Like the other Bromberg Brothers establishments, expect the customer is always wrong attitude from the staff along with overpriced wines you never heard of, no bar, tiny waiting area and lousy desserts."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative'], ['food', 'negative'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Service was horrendous the night we went for dinner."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The manager claimed that he could not compensate us for anything on the bill which just shows the lack of sophistication from the entire group."], "output": "[['staff', 'neutral'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The sangria was served quickly and often."], "output": "[['food', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The servers and/or bus persons dart back and forth through the dining room, never even making eye contact to see if you have any needs."], "output": "[['staff', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We ordered coffee, and then he ordered a bacon cheeseburger (for $12, ridiculous even for New York) The waiter then announced he was going to charge us a $4 sharing charge."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They might be all business at the counter when you give your order, but their food says I love you."], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were seated promptly for a Saturday lunch, but service was incredibly slow."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene With its long zinc bar, plush couches and patterned suede walls, the lounge is a swank spot for midtown's cocktail crowd."], "output": "[['miscellaneous', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu offers favorites from all over China: mellow Lake Tung-Ting shrimp from Hunan; peppery Sichuan tofu with minced pork; and Shanghainese soups with pickled mustard greens."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My only complaint is waiting a bit between the appetizer and the main course but it was well worth it."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere was fun and if you sit by the window, there is a lot of people-watching to be had!"], "output": "[['ambience', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Despite talking to the weekday manager on the prior Monday, who gave me a hard time but agreed to make a reservation for me since my group was so big."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service could be better but the management (Mariano) is quite helpful if there are any problems."], "output": "[['service', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["There are no price listed in the menu, and she will not provid them with a smile."], "output": "[['price', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["As we were finishing our dessert, a nearby waitress dropped a tray and HOT CHOCOLATE SAUCE splattered all over my neck, hair and sweater and my boyfriend's clothes."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The manager refused to talk to me sending the waiter to tell me to tell me that he was not available, when I had previously seen him doing absolutely nothing at the bar."], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu consists of a tasting selection, Austrian, traditional American, and the chef's recommended menu."], "output": "[['miscellaneous', 'positive'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["And forget about having a drink at the bar to take the edge off because the space between tables is so narrow that you'll be shoved by the wait staff who are desparate to get their job done."], "output": "[['food', 'neutral'], ['place', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Also, try to get a seat at the main bar, because I sat at the smaller bar by the entrance and it was getting so crowded with people waiting that it became a bit unpleasant towards to end of the meal."], "output": "[['miscellaneous', 'neutral'], ['place', 'neutral'], ['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The sandwiches, platters, and pitzas are top notch too, but I could make a meal just out of their pita bread and babaganoush."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["(The band is positioned in front of the windows, in a space roughly the size of a living room."], "output": "[['staff', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["At dinner on a Saturday night, I was enthused by the bustling, unpretentious crowd and the lusciously warm lighting."], "output": "[['food', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Definitely make reservations if you can -- they'll honor them, and you can skip the massive wait!"], "output": "[['miscellaneous', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It's the New York you thought was long gone; orders are spoken, not yelled, and the staff knows the names of patrons' dogs."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Their service can use a little assistance, but their food is great."], "output": "[['service', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I told the waiter that my drink tasted very bad and asked if he could swap it out for a Petron Margarita."], "output": "[['staff', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiters, all wearing black suits, are serious, courteous, and knowledgeable; the dining rooms are ornate and convivial, with large parties celebrating various things interspersed with dressed-up couples on dates."], "output": "[['staff', 'negative'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When you're sitting in their main dining room (which has a spectacular, hand-painted high ceiling) you'd never know there was a world outside."], "output": "[['place', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The overpriced ice cream is delicious but the service is atrocious - not only do I have to wait to be admitted into this ice cream joint, but the waiter is a snide, gruff man more suited to be a trucker than an ice cream shop server."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We didn't see him the rest of the night, the other courses come out sporadically, and no one ever asked if we wanted more wine (which we did) or refilled our water -- even after we flagged down another waiter, nothing happened."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After demanding a free round of drinks from a third manager, our party decided to bail on this horrific french import."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["You have to wait in line most of the time, but the burgers are worth it and the beer is cheap."], "output": "[['service', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We had a reservation for Monday lunch and were seated promptly, which was a pleasant surprise."], "output": "[['miscellaneous', 'neutral'], ['food', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Maybe it was the choices the chefs had put on the Restaurant Week Menu, but much of our food was just so-so."], "output": "[['menu', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our dinner was enhanced by a 1999 Pinot Grigio, recmmended by the waitress."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["And the ambience is very cool, stop by on a Saturday afternoon and you can play some old school games while having a beer."], "output": "[['ambience', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitress even gave us a complimentary dessert- warm chocolate lava cake with a scoop of cinnamon ice cream, what a perfect end to a perfect dinner!"], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu can give you price shock but the food, service and drinks are worth every stinking penny."], "output": "[['menu', 'neutral'], ['price', 'neutral'], ['food', 'positive'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["However, the service was so excellent, we added $10 to the tip!"], "output": "[['service', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After the rude waitress took our order we were sipping our drinks when the manager comes over and says we have to leave as the tables are reserved for dinner patrons."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Don't know if the bar is really that bad, BUT the food would more than compensate!"], "output": "[['place', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were promptly seated - the waitress was very attentive, got us drinks and menus."], "output": "[['staff', 'positive'], ['food', 'neutral'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The staff was courteous and explained the menu with detail."], "output": "[['staff', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I think I'm going to start taking the food and coffee to go b/c everytime I go there (which is quite often) I get more frustrated with the service."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The best aspect of Dylan Prime is that it's a perfect spot for a first date, a business dinner, a casual night-on-the-town or even just a quite bite at lunch."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We too had reservations but the gentleman never checked a book to see our names or check us off."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The host was aloof; my waitress, though sweet, didn't seem to know the food or the menu very well; and the waiter we flagged over to order our wine seemed as if he had never looked at the wine list before."], "output": "[['staff', 'negative'], ['menu', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our food was delivered in a timely fashion but if you wanted another drink or your check you had to hunt down your server."], "output": "[['food', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter knew his menu and what to recommend."], "output": "[['staff', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I liked the beer selection!"], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The manager never came to our table and the restaurant didn't offer anything to compensate for the error (they could have taken the two cocktails off the check )."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter did not know the menu, and was very unaccomidating about substutions."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["There was a ten minute wait with a reservation, but the bar kept us entertained."], "output": "[['service', 'neutral'], ['miscellaneous', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I don't expect an enormous, heaping plate of food, but c'mon."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Generous portions of rice porridge and noodles really hit the spot after fighting the crowds on a busy weekend in Chinatown."], "output": "[['food', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["With so many $20 bottles of wines from which to choose, our waiter helped pick a good one."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It's a small and quaint place so have your expectations in check, but that doesn't mean anything bad - know going in that you are gonna eat some serious food!"], "output": "[['place', 'negative'], ['price', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Relaxed neighborhooders treat the spot like a second home, calling the staff by name and lingering despite the smallish bar and hurried courses."], "output": "[['miscellaneous', 'positive'], ['staff', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The party space worked out well for our rehearsal dinner."], "output": "[['place', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Wasa Waffle was different but when we spoke to the manager he inmediatly changed if for another dish (He suggested the Chocolate decadence French Toast."], "output": "[['miscellaneous', 'neutral'], ['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We waited 30 minutes to be seated, 40 minutes for water, bread, menus, 30 more for wine and soft drinks and when the food finally arrived an hour later, it was inedible, burned on top from sitting under a heat lamp."], "output": "[['food', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Meals not served at once and service was inattentive and forgetful."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Seated in the upstairs part of the restaurant my party and I were subjected to rude, abrupt service and unmercifully long waits for our food."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food is very good for the price."], "output": "[['food', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The good service started from the moment we walked in the front door."], "output": "[['service', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The owner lied to me when i asked where our food was 1 hour after we placed the order - he said oh your friend said you were not ready for it."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Now, I expressed my surprise and then the bartender and manager chimed in with a simpleton's remark sir, with restaurants at this time, reservations start coming in."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Never heard anything about a minimum required food order of $30 or had any bad experiences with the staff."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["we saw another waitress spill hot coffee on another diner's foot."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter took his time taking our drink orders ('97 Italian red was good)."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["we wanted to join another 2 top table to ours and the manager abruptly said, that won't work for us!"], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I've heard all the complaints about food and staff at this place, and perhaps some people have had an unfortunate encounter with the host or a cranky waiter."], "output": "[['food', 'negative'], ['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I waited for 45 minutes for my entree to realize that the waiter never put the order in."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Got a seat quick, and had some weird fill-out order form for a hard to understand menu."], "output": "[['miscellaneous', 'positive'], ['menu', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We waited in standing at the entrance for 5 mins to get seats due to just slow service, another 10mins to get menu, and then another 10mins to get water bread."], "output": "[['service', 'negative'], ['menu', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The guacamole at $7 is a small portion served with a stack of Si!Ortega flat taco shells."], "output": "[['food', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The sign outside said, 26 beers on tap, however the bartender was unable to pull a pint from any of them."], "output": "[['food', 'neutral'], ['miscellaneous', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["no need for reservation) you'd expect the crew to be alittle more attentive."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["At one point I noticed the grime on the mustard bottle and asked the waitress for a clean one."], "output": "[['miscellaneous', 'negative'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Superfine is my preferred destination in the city when I'm looking for a casual, hip atmosphere, extraordinary food at decent prices and/or just a place to get a good drink, chat with the bartender and shoot some (free) pool."], "output": "[['ambience', 'positive'], ['food', 'positive'], ['price', 'positive'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They have a lot of beautiful clientele, gay and straight, plus you#146;ll spot random famous actors on occasion."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When spending upwards of $200 for dinner for two, I expect better service."], "output": "[['food', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I left feeling unsatisfied, except for having a nice chance to people watch in the cozy atmosphere with my over-priced pasta bolognese."], "output": "[['ambience', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I had dinner with a few of my friends, and it was the best we've had in a long time."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The crowd doesn't disappoint: A well-heeled, fashionable clientele packs the polished-wood-and-glass-partitioned space, settling into one of two dining rooms, or the bar, which is located at the farthest corner from the entrance."], "output": "[['miscellaneous', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Their bagels have the perfect softness to them, but on the outside there's a bit of crispiness to give it a bit of texture."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["our appetizers came out relatively quickly, but it was near impossible to get a hold of a waiter to order and get our drinks."], "output": "[['food', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food is average, however the service is way below average (our waiter was a stuttering fool when it came to the specials and left our drinks empty for the majority of the night) The atmostphere is cheesy as well as the crowd."], "output": "[['food', 'neutral'], ['service', 'negative'], ['staff', 'negative'], ['ambience', 'negative'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["$25 prix fixe sounds like a good deal, but dinner was still $100 for two, the portions were small, and the ($35) wine, clearly where the money is made, mediocre."], "output": "[['price', 'neutral'], ['miscellaneous', 'negative'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The manager came out very defensively and insisted that it was a 2 lb lobster."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Nice family place, nice atmosphere, but don't go there for pizza."], "output": "[['place', 'positive'], ['ambience', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The host's explanation was they could not control when people finish dinner."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Service at the bar was fine, just as you would expect."], "output": "[['service', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The bartender has a nasty attitude, and it took a party of two 1 1/2 hours to get seated while party after party of the hosts 'friends' were given seating immediately."], "output": "[['staff', 'negative'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If you're going to label spicy items on your menu as spicy (like the Buffalo and Cajun wraps), I think you should go ahead and label all the spicy items as spicy."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our salads and appetizers were brought at the same time and we barely had time to enjoy them before a team of waiters whisked them (and our bread!)"], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Mysteriously, the reserved tables all stayed empty throughout our meal and were still empty when we left an hour later."], "output": "[['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our booth style seats would've been more romantic if our waitress, though nice, was less intrusive, and the loud music from its bar didn't filter thru so much."], "output": "[['food', 'positive'], ['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My grandmother-in-law had a problem with her meal, and the manager AND chef came over and offered to replace it and/or take it off the check."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I don't have much to say about the cafe itself; you can order out from the family-run cafe in the front, or take a seat in the back, which opens up to the outdoors and can offer a less seedy and more homey atmosphere."], "output": "[['miscellaneous', 'negative'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Large portions of food to share."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["During the summer the outdoor area is a great place to sit and eat you pizza."], "output": "[['place', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["From making the reservation (not required) to the before dinner drink (cava), to the table (romantic), to the the ambiance (candles, spanish antiques, etc) to the food of course (original, incredibly deep and rich in flavor) to our departure and saying goodnight to the waiter."], "output": "[['miscellaneous', 'neutral'], ['ambience', 'positive'], ['food', 'positive'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Staples are available every which way--tacos hard and soft, wrapped in tortillas stuffed with guacamole, cheese or black beans; burritos of beef, breaded catfish, pork pipian and chipotle chicken; plus a choice of four sauces from mild to just plain stupid."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If you can get a corner table you can see the entire room while eating in elegance."], "output": "[['miscellaneous', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After our waitress brought us menus took our drink orders, a diff hostess came over asked us to give up our table."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitstaff told us that they had already run out of one of the entrees (before 8 p."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["(food was delivered by a busboy, not waiter) We got no cheese offered for the pasta, our water and wine glasses remained EMPTY our entire meal, when we would have easily spent another $20 on wine."], "output": "[['food', 'negative'], ['staff', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitstaff chatted at the bar amongst themselves and completely ignored us for the entire meal-- which took some work, as the place is small enough with the garden closed!"], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The noise level is equivalent to a sports bar."], "output": "[['ambience', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I am hoping the stale service was a one shot deal because it was deplorable for what we paid for dinner!"], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["There are a few chefs who aren't very enthusiastic and not very theatrical, but the end product is always great food."], "output": "[['staff', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The crust was a crispy tan dream come true with those little blackened air bubbles and chewy center."], "output": "[['food', 'positive'], ['ambience', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitress, host, and bus staff were sitting around at the bar while the patrons were all complaining about the service."], "output": "[['staff', 'negative'], ['place', 'neutral'], ['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu options were not appealing, we had to beg the waiter to ask the chef if we could have just a plain dinner salad to start as their salad choices were not appetizing."], "output": "[['menu', 'negative'], ['staff', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My only complaint is that the place is over crowded on weekends, but that's the price you pay for having such great food."], "output": "[['price', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food In a health-conscious century, it's as likely to be the pub grub as it is the booze that does you in."], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["But the food here is excellant and there are just too many appetizers (in the traditional custom of Korean restaurants) to sample."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The smell near the bar is unbearable, the food is so so, nothing out of the norm, just very plan."], "output": "[['place', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["This happened while many diners were enjoying their meal and it was rudes."], "output": "[['price', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food and wine selection is superb and the chef brings it all together each and every time."], "output": "[['food', 'positive'], ['staff', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["But even on New Years, when they were busy, the owners took the time out to visit our table frequently, even pouring us drinks herself from her own creations."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["However the manager came over and aplogized and all drinks were on him."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service is excellent and always informative without an air."], "output": "[['service', 'positive'], ['ambience', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service was horrendous, not only did the waiter take an hour to remember we ordered drinks, we were rushed to eat and get out so they could seat the next party."], "output": "[['service', 'negative'], ['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["A friendly staff works the room, delivering favorites like crisp, crackling spring rolls and shredded pork rolls wrapped in rice paper."], "output": "[['staff', 'positive'], ['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["They gave us desert menus but never came back for a desert order, instead we had to ask for the check and a bus boy retreived it for us."], "output": "[['menu', 'neutral'], ['food', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The hostess did offer free drinks to my party due to the wait, but we were more interested in eating after said long wait."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The french fries are soggy, the service is so/so and while it looks like a cute little homestyle cafe you'd find in SF, the food is below average."], "output": "[['service', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I had to wait 1hr since I got there around 8pm but you could have a few drinks by the bar since the ambiance is very loungy/ club like."], "output": "[['food', 'neutral'], ['place', 'neutral'], ['ambience', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The portions were so big that after a cocktail drink we had no room left for desert."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We sat way before 2 other tables ahead of us that rec'd their appetizers before us; the waiter neglected to apologize."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I also watched several other frustrated customers getting the wrong orders or trying to catch the waiter's attention (he was posing at the soda fountain)."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter ask us what kind of soufle we wanted and told us to get 2, making us believe that it was part of the pre-fixe, nope soufles are seperate and we were so full from dinner we could barely finish one."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The manager then comes over to the table and asks us to leave - to help him out because there were people waiting!"], "output": "[['staff', 'negative'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The atmosphere was embracing and enticing and the costs of the meal, $45 to $55 in value."], "output": "[['ambience', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After our initial order, the waitress wasn't very attentive (we had to wait 15 minutes at a time to get her attention to refill drinks, order desert, etc)."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The first time my husband and I went there, both the appetizer and entreee I ordered were not available, but we had a waitress who was really on top of things."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It is nearly impossible to get a table, so if you ever have the chance to go here for dinner, DO NOT pass it up."], "output": "[['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The staff treated them like true royalty."], "output": "[['staff', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Great when the band is playing, not so great when there's a large party at the bar."], "output": "[['staff', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The hamburger showed up long before the mussels, and the waiter suggested I start eating because he didnt want my food to get cold."], "output": "[['food', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["B/c the dinner focused on good friends and good food, not waiting around for service or being bothered by rude staff to leave."], "output": "[['food', 'positive'], ['service', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["(Though the filet won't be enough if both have hearty apitites."], "output": "[['miscellaneous', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The prices were moderate for fine dining, and although the restaurant is relatively small, it was easy to have a quiet conversation even though the tables are fairly close together."], "output": "[['food', 'positive'], ['place', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter was not attentive, we waited about 20 mins just to order drinks."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["i ate here with a friend by default-- we were in the meatpacking district on a saturday night, every place in the area was pretty much booked, we were hungry, i only drink sake, and he was treating :)."], "output": "[['place', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I planned a holiday dinner at Kurio and we ended up waiting two hours for the appetizers."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["This was not the same hostess I usually see there who happens to be very sweet and provides excellent service."], "output": "[['staff', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The place is packed, they don't take reservations and waited almost 2 hours."], "output": "[['place', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Each table has a pot of boiling water sunken into its surface, and you get platters of thin sliced meats, various vegetables, and rice and glass noodles."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Serving things like Chicken Kiev with a garlic mashed potato egg roll for $$ with the snooty attitude to match!"], "output": "[['food', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Blue Ribbon Sushi has far more than a cult following, packed daily from Noon till 3 AM, with hipsters, celebrities, Sashimi Lovers, and of course SOHO locals, it's breath taking menu, Superb Fare, Lengthy Sake List, and pro seating system have earned it a 5 STAR rating with The Sushi Times: 6 years running."], "output": "[['food', 'positive'], ['menu', 'neutral'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Park your trench coat at the coat check and be prepared for fine dining, expert / attentive table service and a delectable cuisine."], "output": "[['price', 'neutral'], ['food', 'positive'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the service is so-so; our waiter told us there was a table for us, then took us back to the entrance , we then waited another fifteen minutes- confusion seems to reign."], "output": "[['service', 'negative'], ['staff', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Especially the manager or host who kept walking by and giving us the evil eye to see the progress of our dinner so they could turn the table over to other customers."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Again, since I go out to dinner several times a week in NY, I am used to paying high prices and do not mind at all."], "output": "[['food', 'neutral'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Generally, the food was fine, but the table is too small to eat comfortably."], "output": "[['food', 'positive'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Food presented well and the service once we were seated was great but we had a long wait for our table (about half an hour) even though I had pre-booked."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["we told our waiter to make five selections for each of us, and he decided instead to charge us for each glass separately instead ($80 instead of $20)."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["OUr waiter was a little confused about how to serve champagne."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I also do not think waiters there are rude- yes there are not friendly and chatty, but do provide great service."], "output": "[['staff', 'negative'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Food is decent but portions so small that after 5 appetizers, 2 sides and three entrees, the three of us left still hungry!"], "output": "[['miscellaneous', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["When I requested a specific beer on the menu, the waiter said they were all out of that one and kept pushing the only available beer, which I didn't want."], "output": "[['menu', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Once dinner ended the party really started going inside they were playing great music."], "output": "[['food', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Their delivery of fresh hot pizza."], "output": "[['service', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["i went on a thursday evening and the restaurant was pretty empty the server got our drinks wrong 3 times!"], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Sushi pieces are smaller if u r a 'buffet' customer and choices are rather limited and there's really nothing special on the menu."], "output": "[['food', 'negative'], ['miscellaneous', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The bigger sin is the service --our waiter was late with our main dishes, late with the bill, which was totaled incorrectly (twice)."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the manager said that they were just starting with a preview menu."], "output": "[['staff', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["A huge Coca-Cola sign dominates the bar, and cute waiters whisk plates of 'cue across the dining room and to the sidewalk patio."], "output": "[['place', 'neutral'], ['staff', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We had a great tiem watching the shows and characters and ar food was just what we were looking for."], "output": "[['ambience', 'positive'], ['miscellaneous', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Went to Brasserie for restaurant week dinner and maybe it was the menu but the food was very bland and it was something that I could have eatten at home."], "output": "[['food', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I have never been treated more rudely than I was by the hostess and the manager of Public for brunch last Sunday; the hostess was arrogant, despicable, and mean to our party (reminder: she is a hostess in the service industry)."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Scene This storefront eatery is decked with colorful Mexican art and party kitsch, but it gets dim and moody enough in the evenings to suit a date."], "output": "[['miscellaneous', 'positive'], ['ambience', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Zero decor, this is not a date place--just a great place to get a quick, tasty and cheap meal."], "output": "[['ambience', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The place has a sort of trendy pseudo-asian decor that seems perfectly casual or romantic."], "output": "[['place', 'neutral'], ['ambience', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Besides the price, here are some other annoyances: bleaching the floors during the dinner and automatically charging you 20% gratuity on your credit card without your knowledge."], "output": "[['price', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Hostess continued to ask us if everything was okay, and then did nothing when we gave her specific actions (how about some water or coffee served in paper cups)."], "output": "[['staff', 'negative'], ['service', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food Chef-owner Tom Valenti's food makes just as much noise; he cooks in a masculine, big-flavored, meat-and-potatoes style, rich with terrines, mustards, eggs and bitter greens."], "output": "[['ambience', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The service always ruins your food if it's poor."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The staff didn't even tell us (college kids) about the prix-fixe special, but the pair of older adults sitting next to us took advantage."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Place was empty, waitress was rude, told us that even though there were drink specials at the bar (2 for 1 margaritas), we couldn't have them at our table and we couldn't go up to the bar to get drinks."], "output": "[['place', 'negative'], ['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After being treated like we were at Nobu by the hostess, our waitress brought us our check before we even asked for it and denied us a 2nd round of drinks because."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Don't let the ambiance of this place fool you, the food is far better than many pricey establishments."], "output": "[['ambience', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["However, our one and only complaint was when I received my drink I gave my coupon to our waiter, he returned minutes later to tell me that it could not be used in the dining room, only at the lounge or at the bar."], "output": "[['food', 'neutral'], ['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["For lunch, walk in slightly after 1pm to avoid long lines."], "output": "[['food', 'neutral'], ['miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Even when the place has been packed with tables (I saw a party of 12 in there last time), the waiters and bartenders are still nice."], "output": "[['place', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Long wait for our meal (approx 30 minutes), unusual slow service, waitresses (especially the preety one with black hair) louder thn clients, do not care much for customers."], "output": "[['food', 'neutral'], ['service', 'negative'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the hostess is rude as can be, the waiters can't stop to check in, the busboys are flinging stuff on your table, and that's true even when the restaurant is half empty!"], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We happen to walk by, read the menu posted outside they offered a nice selection ranging from citrus salmon, pan seared trout, chicken pot pie, sirlion steak, the fried calamari is out of this world they use a secret ingredient to their dipping sauce."], "output": "[['menu', 'neutral'], ['miscellaneous', 'positive'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Noisy atmosphere makes the place even more fun, though it may become hard to get in after 5PM on Friday- almost every table would be reserved."], "output": "[['ambience', 'negative'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Additionally, one of the waiters found it necessary to walk around the restaurant, telling people how to eat their food."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I have gotten warmer and much friendlier welcome and outstanding service at the other Thai restaurants in the Greenpoint area."], "output": "[['miscellaneous', 'positive'], ['service', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Lastly the waiters and bartender should learn to have argurments in private and not in front of customers."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food is not five star but the prices reflect that."], "output": "[['food', 'negative'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The price was right too--I spent under $30 for my entree and two drinks."], "output": "[['price', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Obviously we did not get right service and nobody said soory for that and other restaurant guests who came after us got quicker dish than us."], "output": "[['service', 'negative'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I won't even wait for an hour and a half when I don't have reservations, but the hostess and the pompous maitre d' just jerked me around and kept on promising me that I'd be the next to be seated."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["at the end of the meal the hostess came to us and rudely ask us to leave the table, we were astonished by her attitude."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Went to Chow Bar for dinner, I thought it was kind of pricey, but the food and the service was good - but it wasn't incredibly busy, so maybe they just had more free time to devote to us."], "output": "[['place', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["What I don't get is asking a high rolling, forgiving of bad service, drink guzzling table like mine to leave as soon as we finished out last sip of $12 martinis and left a 25% tip."], "output": "[['service', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I love the food here, and although it is pricey, the entree comes with rice, naan, dal, and salad, which makes it worthwhile."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["our waiter spilled an entire glass of water on my brother and didn't so much as acknowledge it, let alone apologize."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The staff is very kind and well trained, they're fast, they are always prompt to jump behind the bar and fix drinks, they know details of every item in the menu and make excelent recomendations."], "output": "[['staff', 'positive'], ['place', 'neutral'], ['food', 'neutral'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My friends and I had a great time - the atmosphere was exciting but didn't encroach on us while we had our meal and drinks (which is better, the kiwitini or the watermelon martini?)"], "output": "[['ambience', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["If you like an ecclectic crowd and an overall good time where you and your friends can get together whether it be to eat, drink or just play some good old pictionary (they provide crayons and a blank white sheet at every table), go to the Cargo!"], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["the food at pongal is average, the rava masala dosa is much better at madras mahal (a few doors down) and certainly the service at pongal is the worst among the indian restaurants along that block."], "output": "[['food', 'positive'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Instead, the chef made me a special creation off the menu, and wow."], "output": "[['staff', 'positive'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I followed my handsome waiter's suggestions for everything from my cranapple martini, BBQ duck tostada appetizer and rum-glazed pork tenerloin entree to the scandalously good brownie sundae."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["As expected, the wine list is as thoughtful as the menu the staff has earned my trust with their bullet-proof recommendations I have yet to be disappointed from their exhaustive list."], "output": "[['food', 'positive'], ['menu', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Much to my satisfaction, I was seated promptly without a reservation and soon after being seated was greeted by my server."], "output": "[['miscellaneous', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["before we could say anything, one waiter picked it up while another brought a knife to our table on a platter."], "output": "[['staff', 'negative'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["There was no price on the menu and the waitress recommended it."], "output": "[['price', 'neutral'], ['menu', 'neutral'], ['staff', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The ambiance and service is great but I wish I could say the same about the food."], "output": "[['ambience', 'positive'], ['service', 'positive'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Then we were led downstairs to the main room, and were seated at the huge communal dining room table."], "output": "[['service', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food is just ok, not at all worth having to put up with the disgusting staff, the manager/owner in particular."], "output": "[['food', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter never once asked how everything was, as I suspect he knew the kitchen was producing seriously average food."], "output": "[['staff', 'negative'], ['place', 'neutral'], ['food', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The prices did not reflect the quality of the meal."], "output": "[['price', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We were crammed next to the people who were seated to the right of us, who repeatedly took phone calls during dinner, while the rude wait staff did nothing despite the warning on the menu that cell phones were not to be used in the dining room."], "output": "[['food', 'neutral'], ['staff', 'negative'], ['menu', 'neutral'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food The daily-changing menu, scrawled on large dry-erase boards, offers a blend of haute cuisine and Texas roadhouse fare."], "output": "[['food', 'positive'], ['menu', 'neutral'], ['price', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Although we had to wait a few minutes for our table, the manager bought us a round of drinks and proceeded to take care of throughout the entire meal."], "output": "[['miscellaneous', 'neutral'], ['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["we walked in to the resturant, squeezed by our (to be) waiter (who ignored us and didnt step to the side), and straight up to the host (he was busy talking to the bar tender)."], "output": "[['staff', 'negative'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food When the counter guy asks, Would you like better fries with that?"], "output": "[['food', 'positive'], ['place', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The menu is informatively presented with facts about the ingredients, and is divided into Starting and Sharing plates, which allows one to sample a few items during the meal."], "output": "[['menu', 'positive'], ['ambience', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["My wife and I invited our friends to a late dinner and were having drinks afterwards when the manager instructed the waitress not to serve us any more drinks as it was bottle service."], "output": "[['food', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I am not sure if this was just an off night or what, our waiter forgot wine, brought us desert menus before dinner came, then brought us the wrong dinner."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Generous portions on the entrees."], "output": "[['miscellaneous', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We asked for the manager who told us that it was their first time serving brunch, to be patient and that our bill would be discounted."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The rude and unaccomodating hostess (who we later learned was the manager) repeatedly promised us the next table but never offered to buy us a drink while we waited."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Everyone around me was eating stuff that wasn't on the menu and looked tastier, but the waitress didn't bother to suggest any of these things, even when asked for suggestions."], "output": "[['menu', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waiter asked us several times after dinner whether we had paid our bill yet, and after we had, he came over to make sure that we hadn't just hidden it from him or something."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After asking the waiter for a few minutes to look over the menu, we had to call out several times over 15 minutes to get him to come back to our table."], "output": "[['staff', 'negative'], ['menu', 'neutral'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Not a destination restaurant, but if you're hungry for breakfast or lunch, big portions and good quality for the money."], "output": "[['food', 'neutral'], ['miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Good wines under $100 are included in the predominantly French list, but take some ferreting out to find."], "output": "[['food', 'positive'], ['miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["anyway, nice place for brunch for selection under $20 meals desserts were great (3 flavors for creme brulee!!"], "output": "[['place', 'positive'], ['food', 'positive'], ['miscellaneous', 'neutral'], ['ambience', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Downtown Dinner 2002 - Prixe fix: Appetizers were ok, waiter gave me poor suggestion."], "output": "[['food', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The Food Nothing makes for better bar snacks than this down-home Southern menu."], "output": "[['food', 'neutral'], ['place', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After spending about 2 hours in the restaurant our waiter decided to call it a night without even asking if we wanted dessert."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Half the menu is comprised of original creations while the other half consists of unique slants on orthodox cuisine such as the single super-sized gnocchi with cinammon."], "output": "[['menu', 'neutral'], ['food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Not only did we have to flag the waiter down every time for every course or request, but they spilled our drinks twice all over the table - and once was hot tea."], "output": "[['staff', 'negative'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Second, the value was great; after ordering a ton of food and several drinks, the bill still came to less than $40 a person (though I suspect that the nice manager might have given us a few freebees!"], "output": "[['miscellaneous', 'positive'], ['food', 'positive'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We arrived about 15 minutes late for a Friday 12:30 reservation, but the staff couldn't have been nicer."], "output": "[['miscellaneous', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["I have eaten here for nearly three years, with firends with family, the service is great attentive and informed, perfect for Thursdays, Fridays and Saturdays."], "output": "[['miscellaneous', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After reading the negative sushi reviews, my boyfriend and I opted for their Korean fare."], "output": "[['food', 'negative'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["After dinner I walked over to the cheese counter -after having been greeted by a rude server, I was shocked to see how dissapointing their cheese selection was: it is miniscule, many of the fresh chevre cheese were more than ready to be tossed, etc."], "output": "[['food', 'neutral'], ['miscellaneous', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The waitresses are at your table filling your water or oil before your last sip or dip."], "output": "[['staff', 'positive'], ['food', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The first time, the food was decent for lunch, but remember mediocre service."], "output": "[['food', 'neutral'], ['service', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["We walked out the door with only a drink in each of us and the bill was still over $100."], "output": "[['food', 'neutral'], ['price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["It took us 20 minutes to get a check, despite many attempts at meaningful eye contact with the wait staff."], "output": "[['price', 'neutral'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The pancakes were good, but don't have blueberry pancakes on the menu of you are not able to produce more than three tiny blueberries in each pancake."], "output": "[['food', 'negative'], ['menu', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["Our waiter disappeared entirely, our food, when we were finally able to order it, arrived without plates (we had to go and track down a busboy to get them), and when we were finished, we couldn't get the check, even after walking across the restaurant to request it."], "output": "[['staff', 'negative'], ['food', 'neutral'], ['miscellaneous', 'neutral'], ['price', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["90 for a porterhouse steak for 2 (ordered medium-rare, delivered well-done, dry and tasteless) and I'm not even full."], "output": "[['food', 'neutral'], ['service', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "} +{"task_type": "generation", "dataset": "mams", "input": ["The food was good but our waiters were pushy,rude and dumb."], "output": "[['food', 'positive'], ['staff', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": " 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']] "}