source
stringlengths 17
501k
| target
stringlengths 0
8.23k
| task_name
stringlengths 8
85
| task_source
stringclasses 4
values | template_type
stringclasses 4
values | template_idx
int64 0
17
| split
stringclasses 3
values |
|---|---|---|---|---|---|---|
Please answer the following question: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "GPS Nice app π
ππ»πππ°πΉπΊπ"
Answer:
|
3
|
app_reviews_convert_to_rating
|
P3
|
zs_noopt
| 9
|
train
|
Please answer the following question: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "Loved it Best learning app ever."
A:
|
5
|
app_reviews_convert_to_rating
|
P3
|
zs_opt
| 8
|
train
|
Please answer this: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "Nice Easy"
++++++++
Answer: 5
Please answer this: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "Ok!"
++++++++
Answer: 5
Please answer this: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "Great for mgt Emploee: No that is not what I said Mgr: Well I save every text I get."
++++++++
Answer:
|
5
|
app_reviews_convert_to_rating
|
P3
|
fs_opt
| 6
|
train
|
Answer the following question: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "hoooo"
Answer:
|
5
|
app_reviews_convert_to_rating
|
P3
|
zs_noopt
| 5
|
train
|
Please answer the following question: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "Add silent mode Clicking sound mute option should be add"
Answer:
|
3
|
app_reviews_convert_to_rating
|
P3
|
zs_opt
| 9
|
train
|
Answer the following question: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "Best"
Answer:
|
5
|
app_reviews_convert_to_rating
|
P3
|
zs_noopt
| 5
|
train
|
On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "No more running to the pc Love this app it does what I need it to do search repos for stuff I like to see or hear. Hope soon if I'm not mistaken an ability to use hand gestures instead of arrow keys would be really nice."
----
Answer: 5
On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "Loved it Good app with offline features"
----
Answer: 5
On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "Broken No longer works"
----
Answer:
|
1
|
app_reviews_convert_to_rating
|
P3
|
fs_opt
| 1
|
train
|
Please answer this: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "Perfect"
++++++++
Answer: 5
Problem: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "My Google account signs into Google"
A: 4
Problem: Given the question: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "Fiefth Shingz"
++++++++++++++++++++++++++++++++
The answer is:
5
input question: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "perfect app"???
output answer: 5
On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "Nice"
----
Answer: 5
Q: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "Very very good game"
A:
|
5
|
app_reviews_convert_to_rating
|
P3
|
fs_opt
| 1
|
train
|
input: Please answer the following: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "S7 Great"
++++++++++
output: 3
Please answer this: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "Nice app"
++++++++
Answer: 5
Problem: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "Good Haven't used it yet!π"
A: 5
Problem: Given the question: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "How to down files????"
++++++++++++++++++++++++++++++++
The answer is:
5
input question: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "This is not working No longer recognizes kdbx files. Can't open. Greyed out in file manager."???
output answer: 2
input question: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "Very bad Sorry"???
output answer:
|
1
|
app_reviews_convert_to_rating
|
P3
|
fs_opt
| 8
|
test
|
Problem: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "Good"
A: 5
Problem: Given the question: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "Bbbb Mmmm"
++++++++++++++++++++++++++++++++
The answer is:
5
input question: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "Ok"???
output answer: 3
On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "Fallings app Fsjkk"
----
Answer: 5
Q: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "Good Does everything needed good app"
A: 5
[Q]: On a scale of 1-5 (with 1 being least favorable and 5 being most favorable), how would you rate this review? "containerized debian on top of android. great and elegant solution that turns a phone into full-featured linux terminal."
****
[A]:
|
5
|
app_reviews_convert_to_rating
|
P3
|
fs_opt
| 3
|
validation
|
Instructions: Based on the given question and tppic, give an answer. The answer is available on on the internet. The questions are mostly centered around a single named entity.
Input: concept: Costa Rica question: what language do people speak in costa rica?
Output:
|
['Spanish Language']
|
task1601_webquestions_answer_generation
|
NIv2
|
zs_opt
| 3
|
train
|
Detailed Instructions: Based on the given question and tppic, give an answer. The answer is available on on the internet. The questions are mostly centered around a single named entity.
Problem:concept: Indonesia question: what language do they speak in indonesia?
Solution:
|
['Javanese Language', 'Malay Language', 'Sunda Language', 'English Language', 'Bali Language', 'Indonesian Language', 'Batak Language', 'Tobelo Language', 'Dutch Language', 'Madura Language']
|
task1601_webquestions_answer_generation
|
NIv2
|
zs_opt
| 8
|
train
|
Based on the given question and tppic, give an answer. The answer is available on on the internet. The questions are mostly centered around a single named entity.
One example: concept: Selena Gomez question: what city was selena gomez born in?
Solution is here: New York City
Explanation: The answer is correct based on the information available on the web about Selena Gomez.
Now, solve this: concept: France question: who is the leader of france 2012?
Solution:
|
['Nicolas Sarkozy']
|
task1601_webquestions_answer_generation
|
NIv2
|
fs_opt
| 6
|
train
|
Detailed Instructions: Based on the given question and tppic, give an answer. The answer is available on on the internet. The questions are mostly centered around a single named entity.
Problem:concept: Chris Colfer question: what movies has chris colfer been in?
Solution:
|
['8', 'Russel Fish: The Sausage and Eggs Incident', 'Glee Encore', 'Struck by Lightning', 'Glee: The 3D Concert Movie']
|
task1601_webquestions_answer_generation
|
NIv2
|
zs_opt
| 8
|
train
|
You will be given a definition of a task first, then some input of the task.
Based on the given question and tppic, give an answer. The answer is available on on the internet. The questions are mostly centered around a single named entity.
concept: Michigan question: who won the governor election in michigan?
Output:
|
['Rick Snyder']
|
task1601_webquestions_answer_generation
|
NIv2
|
zs_opt
| 1
|
train
|
Based on the given question and tppic, give an answer. The answer is available on on the internet. The questions are mostly centered around a single named entity.
Ex Input:
concept: Lola Bunny question: who plays lola bunny in the looney tunes show?
Ex Output:
['Britt McKillip', 'Kath Soucie']
Ex Input:
concept: John Steinbeck question: what is john steinbeck best known for?
Ex Output:
['Of Mice and Men']
Ex Input:
concept: Barack Obama question: what middle school did barack obama attend?
Ex Output:
|
['St. Francis of Assisi Catholic School']
|
task1601_webquestions_answer_generation
|
NIv2
|
fs_opt
| 1
|
train
|
TASK DEFINITION: Based on the given question and tppic, give an answer. The answer is available on on the internet. The questions are mostly centered around a single named entity.
PROBLEM: concept: Harley Quinn question: who should play harley quinn?
SOLUTION: ['Arleen Sorkin', 'Mia Sara', 'Hynden Walch']
PROBLEM: concept: Pittsburgh Steelers question: when was the last superbowl win for the steelers?
SOLUTION: ['2006 NFL season']
PROBLEM: concept: Howard Stern question: who played howard stern in private parts?
SOLUTION:
|
['Him/Herself']
|
task1601_webquestions_answer_generation
|
NIv2
|
fs_opt
| 8
|
train
|
Based on the given question and tppic, give an answer. The answer is available on on the internet. The questions are mostly centered around a single named entity.
Example: concept: Selena Gomez question: what city was selena gomez born in?
Example solution: New York City
Example explanation: The answer is correct based on the information available on the web about Selena Gomez.
Problem: concept: Iceland question: what language do people speak in iceland?
|
Solution: ['Icelandic Language']
|
task1601_webquestions_answer_generation
|
NIv2
|
fs_opt
| 5
|
train
|
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
Based on the given question and tppic, give an answer. The answer is available on on the internet. The questions are mostly centered around a single named entity.
concept: Selena Gomez question: what city was selena gomez born in?
Solution: New York City
Why? The answer is correct based on the information available on the web about Selena Gomez.
New input: concept: The Bahamas question: what type of government does the bahamas have?
Solution:
|
['Parliamentary system', 'Unitary state', 'Constitutional monarchy']
|
task1601_webquestions_answer_generation
|
NIv2
|
fs_opt
| 0
|
test
|
Based on the given question and tppic, give an answer. The answer is available on on the internet. The questions are mostly centered around a single named entity.
Example: concept: Selena Gomez question: what city was selena gomez born in?
Example solution: New York City
Example explanation: The answer is correct based on the information available on the web about Selena Gomez.
Problem: concept: Mary Todd Lincoln question: what religion was mary todd lincoln?
|
Solution: ['Presbyterianism', 'Baptists', 'Catholicism']
|
task1601_webquestions_answer_generation
|
NIv2
|
fs_opt
| 5
|
validation
|
Given the task definition and input, reply with output. In this task, you have to identify the named entities (NER) which are the ingredients required given its directions. Named entities are the names of the items without their quantity.
Place all dry ingredients in a large mixing bowl and stir together with a wire whisk., Add the remaining ingredients and beat on medium speed for 2 minutes., Pour into greased and floured cake pans, filling each pan a little over half full., Bake in a preheated 325-degree oven until cake tests done. Baking time varies depending on the size of pans used., For a chocolate cake, use a chocolate cake mix and substitue 3 whole eggs for the egg whites., To add liqueur flavors, substitute alcohol (champagne, Kahlua, etc.) for 1 cup of the water.
|
White Cake Mix, All-purpose, Sugar, Salt, Water, Vegetable Oil, Vanilla, Almond Extract, Sour Cream, Egg Whites
|
task571_recipe_nlg_ner_generation
|
NIv2
|
zs_opt
| 5
|
train
|
Given the task definition and input, reply with output. In this task, you have to identify the named entities (NER) which are the ingredients required given its directions. Named entities are the names of the items without their quantity.
Grill chicken breast. Prepare rice as directed. Add vegetables. Saut mushrooms and onions. Serve by placing chicken breasts over rice on plate. Mushrooms and onions over chicken. Cover with melted cheese. Serves 4.
|
chicken breast halves, Uncle Ben, white cheese, mixed vegetables, fresh mushrooms, onions
|
task571_recipe_nlg_ner_generation
|
NIv2
|
zs_opt
| 5
|
train
|
In this task, you have to identify the named entities (NER) which are the ingredients required given its directions. Named entities are the names of the items without their quantity.
Let me give you an example: Preheat oven to 375 degrees., Boil syrup, sugar and shortening over medium heat, stirring constantly., Remove from heat., Gradually stir in flour and nuts., Drop by teaspoonfuls about 3 inches apart on lightly greased cookie sheet., Bake 5 to 6 min., Remove from oven and let stand 5 min, before removing from sheet., May be rolled into cylindrical shape while still hot., If cooled too much, return to oven for a minute., Yield: 4 dozen cookies.
The answer to this example can be: flour, nuts, corn syrup, shortening, brown sugar
Here is why: This is a good example, as we see the NER is generated correctly from the directions.
OK. solve this:
Roll out sheet to 1/8-inch thick., Brush sheet with mustard; top with ham, cheese and top with remaining sheet., Fold ends together and with a fork, press sides., Brush egg yolk on top. Bake at 350Β° for 30 minutes on cookie sheet.
Answer:
|
deli, pastry sheets, mustard, Mozzarella, egg
|
task571_recipe_nlg_ner_generation
|
NIv2
|
fs_opt
| 8
|
train
|
Q: In this task, you have to identify the named entities (NER) which are the ingredients required given its directions. Named entities are the names of the items without their quantity.
In 12-inch nonstick skillet, heat Olive Oil over medium heat and cook garlic paste, stirring occasionally, 2 minutes or until slightly golden. Stir in Sauce. Bring to a boil over high heat. Reduce heat to low., , Season shrimp, if desired, with salt and pepper. Into skillet, stir in shrimp, olives and pepperoncini. Cook covered 3 minutes or until shrimp turn pink. Stir in parsley and toss with hot linguine.
A:
|
Olive Oil, garlic, Tomato, shrimp, green olives, pepperoncini, parsley, linguine
|
task571_recipe_nlg_ner_generation
|
NIv2
|
zs_opt
| 7
|
train
|
Given the task definition and input, reply with output. In this task, you have to identify the named entities (NER) which are the ingredients required given its directions. Named entities are the names of the items without their quantity.
In a large pot, melt the butter over moderately low heat. Add the onion; cook, stirring occasionally, until translucent, about 5 minutes., Add the garlic, broccoli stems, potatoes, broth, water, salt, and pepper. Bring to a boil. Reduce the heat and simmer until the vegetables are almost tender, about 10 minutes., In a food processor or blender, pulse the soup to a coarse puree. Return the soup to the pot and bring to a simmer. Add the broccoli florets and simmer until they are tender, about 5 minutes. Stir 1/4 cup of the grated Parmesan into the soup, and serve the soup topped with the remaining cheese., Variation: If you'd prefer a completely smooth soup, add the broccoli florets to the pot after the potatoes have cooked for five minutes, and continue simmering until all of the vegetables are tender, about five minutes more. Puree the soup until smooth. This would also make a great first course for six people., Wine Recommendation: Pinot grigio is the all-purpose Italian white. Its full body matches the creaminess of this soup, while its high acidity offers contrast. The relatively neutral taste of the wine allows the soup's subtle flavors to come through. No wonder pinot grigio is so popular.
|
butter, onion, garlic, broccoli, boiling potatoes, chicken broth, water, salt, fresh-ground black pepper, Parmesan
|
task571_recipe_nlg_ner_generation
|
NIv2
|
zs_opt
| 5
|
train
|
In this task, you have to identify the named entities (NER) which are the ingredients required given its directions. Named entities are the names of the items without their quantity.
--------
Question: Toss broccoli, raisins, onion, nuts, and bacon., In separate bowl, mix sugar, vinegar and mayonnaise., Pour mixture over broccoli and toss to coat., Refrigerate for at least 2 hours.
Answer: broccoli florets, raisins, red onion, walnuts, bacon, sugar, vinegar, mayonnaise
Question: Combine all items in large bowl and beat 4 minutes., Bake in greased and floured 9 x 13-inch pan at 350Β° for 35 to 40 minutes. Cool slightly., Pour banana glaze over top., Let mellow for a day or two., Makes very moist cake.
Answer: yellow cake mix, instant vanilla pudding, bananas, eggs, salt, water, vanilla, salad oil, pecans
Question: Coat a large nonstick skillet with cooking spray. Place over medium heat until hot. Add pork and onion; cook 10 minutes or until pork is browned and onion is crisp-tender, stirring often. Add chutney, wine, and lime juice. Cook over medium heat 6 minutes or until pork is tender. Spoon over bottom halves of rolls. Top with remaining roll halves. Serve warm.
Answer:
|
Vegetable cooking spray, pork tenderloin, purple onion, mango, Madeira wine, lime juice, onion rolls
|
task571_recipe_nlg_ner_generation
|
NIv2
|
fs_opt
| 7
|
train
|
In this task, you have to identify the named entities (NER) which are the ingredients required given its directions. Named entities are the names of the items without their quantity.
Q: Cream sugar and cream cheese together., Stir in Cool Whip. Add nuts, bananas, pineapple and strawberries; mix well. Refrigerate.
A:
|
cream cheese, sugar, banana slices, pecan pieces, pineapple, frozen strawberries
|
task571_recipe_nlg_ner_generation
|
NIv2
|
zs_opt
| 4
|
train
|
In this task, you have to identify the named entities (NER) which are the ingredients required given its directions. Named entities are the names of the items without their quantity.
[EX Q]: Preheat oven to 325F Line a 13x9 inch baking pan with foil., Brush foil with 1 tablespoon melted butter; set aside., In a large bowl, combine remaining melted butter and cocoa powder., Using an electric mixer set on medium speed, beat sugar, eggs and vanilla into the cocoa mixture until well combined., Stir flour and salt into cocoa mixture until thoroughly combined., Spread mixture into prepared pan., Bake brownies until a toothpick inserted in center comes out almost clean, 35-40 minutes., Transfer the pan to a wire rack to cool completely., Lift uncut bars from pan using foil and place on a flat work surface., Using the tree-shaped cookie cutter, cut out tree shapes, inverting the cutter every other time to minimize waste., Place melted chocolate into a reseable plastic bag; snip off 1 corner., Pipe melted chocolate in a zigzag design on top of trees; top with christmas sprinkles.
[EX A]: butter, butter, cocoa, sugar, eggs, vanilla, flour, salt, chocolate chips, sprinkles
[EX Q]: Heat oven to 425F., On a large rimmed baking sheet, gently toss the tomatoes, garlic, peppers and jalapeno with 3 tbsp olive oil, 3/4 tsp salt and 1/2 tsp pepper., Roast until the tomatoes begin to break down, 15 to 20 minutes., With five minutes remaining, heat the remaining tbsp oil in a nonstick skillet over medium heat., Season the tilapia with 1/2 tsp salt and 1/4 tsp pepper and cook until opaque throughout, 1 to 2 minutes per side., Toss the vegetables with the cilantro and serve over the seared fish.
[EX A]: cherry, garlic, orange peppers, jalapenos, olive oil, kosher salt, Black pepper, tilapia filets, fresh cilantro
[EX Q]: Mix all ingredints together., Place in a 9 x 13 pan., Bake at 350 for 1 hour.
[EX A]:
|
browns, cream of chicken soup, cream of mushroom soup, sour cream, onion, cheese
|
task571_recipe_nlg_ner_generation
|
NIv2
|
fs_opt
| 6
|
train
|
Detailed Instructions: In this task, you have to identify the named entities (NER) which are the ingredients required given its directions. Named entities are the names of the items without their quantity.
Problem:Heat 4 Tbsp., butter in heavy large saucepan over medium heat., Add in onion and garlic; saute/fry till light golden brown, about 5 min., Fold in bulgur., Add in 1/2 c. stock and cook till absorbed, stirring often, about 5 min., Add in 1/2 c. stock 2 more times, simmering after each addition and stirring often till liquid is absorbed., Fold in asparagus., Continue adding stock 1/2 c. at a time till bulgur is just tender and mix is creamy, simmering after each addition and stirring often till stock is absorbed, about 20 min., Add in peas and cook 3 min longer., Stir in 3/4 c. Parmesan, cream, tarragon and remaining 1 Tbsp., butter., Serve, passing additional grated Parmesan, if you like., This recipe yields 6 servings as a first-course., Comments: At the restaurant, this is made with spelt, a chewy grain which requires much longer cooking than does the more readily available bulgur called for here., Description: "(Risotto De Bulgour Aux Pois At Asperges)"
Solution:
|
butter, onion, garlic, bulgur, chicken, peas unthawed, freshly-grated Parmesan cheese, whipping cream, Parmesan cheese
|
task571_recipe_nlg_ner_generation
|
NIv2
|
zs_opt
| 8
|
test
|
Given the task definition and input, reply with output. In this task, you have to identify the named entities (NER) which are the ingredients required given its directions. Named entities are the names of the items without their quantity.
In a small frying pan, on medium low heat, toast the cumin, cloves, cardamom, peppercorns, allspice, fenugreek, and coriander for about 2 minutes, stirring constantly., Remove from the pan and cool for 5 minutes., Discard the stems from the chiles., In a spice grinder or with a mortar and pestle, finely grind together the toasted spices and the chiles., Mix in the remaining ingredients., Store Berbere refrigerated in a well sealed jar or a tightly closed plastic bag.
|
cumin seeds, cloves, cardamom seeds, black peppercorns, allspice, fenugreek seeds, coriander seeds, red chiles, ginger root, turmeric, salt, paprika, cinnamon, cloves ground
|
task571_recipe_nlg_ner_generation
|
NIv2
|
zs_opt
| 5
|
validation
|
Definition: In this task, you're given a pair of sentences, sentence 1 and sentence 2. Your job is to classify the genre of the sentences from the 10 options displayed. Indicate your answer by entering the number of the choice as 1-10.
Input: Sentence 1: Dissenting in the New York Times Book Review , Pico Iyer finds Cuba Libre The central moral question raised ... Sentence 2: The NYT book review did not read Cuba Libre. Choices: 1. FACE-TO-FACE, 2. GOVERNMENT, 3. LETTERS, 4. 9/11, 5. SLATE, 6. TELEPHONE, 7. TRAVEL, 8. VERBATIM, 9. OUP, 10. FICTION.
Output:
|
4
|
task198_mnli_domain_classification
|
NIv2
|
zs_opt
| 2
|
train
|
Q: In this task, you're given a pair of sentences, sentence 1 and sentence 2. Your job is to classify the genre of the sentences from the 10 options displayed. Indicate your answer by entering the number of the choice as 1-10.
Sentence 1: That's all." Tuppence rose. Sentence 2: Tuppence continued on speaking. Choices: 1. FACE-TO-FACE, 2. GOVERNMENT, 3. LETTERS, 4. 9/11, 5. SLATE, 6. TELEPHONE, 7. TRAVEL, 8. VERBATIM, 9. OUP, 10. FICTION.
A:
|
9
|
task198_mnli_domain_classification
|
NIv2
|
zs_opt
| 7
|
train
|
You will be given a definition of a task first, then some input of the task.
In this task, you're given a pair of sentences, sentence 1 and sentence 2. Your job is to classify the genre of the sentences from the 10 options displayed. Indicate your answer by entering the number of the choice as 1-10.
Sentence 1: And, a recent meta-analysis has shown little effect of age on the relative risk from PM exposure (Stieb et al. Sentence 2: Age has a massive effect on the risk from PM exposure. Choices: 1. FACE-TO-FACE, 2. GOVERNMENT, 3. LETTERS, 4. 9/11, 5. SLATE, 6. TELEPHONE, 7. TRAVEL, 8. VERBATIM, 9. OUP, 10. FICTION.
Output:
|
1
|
task198_mnli_domain_classification
|
NIv2
|
zs_opt
| 1
|
train
|
Instructions: In this task, you're given a pair of sentences, sentence 1 and sentence 2. Your job is to classify the genre of the sentences from the 10 options displayed. Indicate your answer by entering the number of the choice as 1-10.
Input: Sentence 1: we have had no snow to speak of to speak of Sentence 2: We did not get any snow. Choices: 1. FACE-TO-FACE, 2. GOVERNMENT, 3. LETTERS, 4. 9/11, 5. SLATE, 6. TELEPHONE, 7. TRAVEL, 8. VERBATIM, 9. OUP, 10. FICTION.
Output:
|
5
|
task198_mnli_domain_classification
|
NIv2
|
zs_opt
| 3
|
train
|
In this task, you're given a pair of sentences, sentence 1 and sentence 2. Your job is to classify the genre of the sentences from the 10 options displayed. Indicate your answer by entering the number of the choice as 1-10.
Example: Sentence 1: Next to the MGM Grand you will find M and M World. Sentence 2: The candy has many fans who love its attractions. Choices: 1. FACE-TO-FACE, 2. GOVERNMENT, 3. LETTERS, 4. 9/11, 5. SLATE, 6. TELEPHONE, 7. TRAVEL, 8. VERBATIM, 9. OUP, 10. FICTION.
Example solution: 1
Example explanation: The places are specifically pointed out and referred to as attractions.
Problem: Sentence 1: well yeah i think they they like a routine of sorts Sentence 2: They would rather go by a schedule. Choices: 1. FACE-TO-FACE, 2. GOVERNMENT, 3. LETTERS, 4. 9/11, 5. SLATE, 6. TELEPHONE, 7. TRAVEL, 8. VERBATIM, 9. OUP, 10. FICTION.
|
Solution: 5
|
task198_mnli_domain_classification
|
NIv2
|
fs_opt
| 5
|
train
|
In this task, you're given a pair of sentences, sentence 1 and sentence 2. Your job is to classify the genre of the sentences from the 10 options displayed. Indicate your answer by entering the number of the choice as 1-10.
Q: Sentence 1: Employers wishing to avoid paying workers compensation could deny coverage until the worker was no longer in the country, or discontinue payments after the worker had returned home. Sentence 2: Employers who want to avoid workers comp can deny coverage until a worker leaves the country. Choices: 1. FACE-TO-FACE, 2. GOVERNMENT, 3. LETTERS, 4. 9/11, 5. SLATE, 6. TELEPHONE, 7. TRAVEL, 8. VERBATIM, 9. OUP, 10. FICTION.
A: 1
****
Q: Sentence 1: to me yeah to yeah to me yeah well Sentence 2: No, not to me. Never! Choices: 1. FACE-TO-FACE, 2. GOVERNMENT, 3. LETTERS, 4. 9/11, 5. SLATE, 6. TELEPHONE, 7. TRAVEL, 8. VERBATIM, 9. OUP, 10. FICTION.
A: 5
****
Q: Sentence 1: i mean a day Sentence 2: I mean the whole twenty four hours. Choices: 1. FACE-TO-FACE, 2. GOVERNMENT, 3. LETTERS, 4. 9/11, 5. SLATE, 6. TELEPHONE, 7. TRAVEL, 8. VERBATIM, 9. OUP, 10. FICTION.
A:
|
5
****
|
task198_mnli_domain_classification
|
NIv2
|
fs_opt
| 4
|
train
|
Instructions: In this task, you're given a pair of sentences, sentence 1 and sentence 2. Your job is to classify the genre of the sentences from the 10 options displayed. Indicate your answer by entering the number of the choice as 1-10.
Input: Sentence 1: The Commission stated that a date stamp on a telephone would indicate to users that a telephone is hearing aid compatible if it were imported or manufactured after August 16, 1989, when all new telephones were required to be hearing aid compatible. Sentence 2: The Commission said a date stamp would tell users the telephone works with hearing aids as long as it was a new phone. Choices: 1. FACE-TO-FACE, 2. GOVERNMENT, 3. LETTERS, 4. 9/11, 5. SLATE, 6. TELEPHONE, 7. TRAVEL, 8. VERBATIM, 9. OUP, 10. FICTION.
Output:
|
1
|
task198_mnli_domain_classification
|
NIv2
|
zs_opt
| 3
|
train
|
Given the task definition and input, reply with output. In this task, you're given a pair of sentences, sentence 1 and sentence 2. Your job is to classify the genre of the sentences from the 10 options displayed. Indicate your answer by entering the number of the choice as 1-10.
Sentence 1: Buchanan pities the Lone Eagle, who he says suffered for the rest of his life--and beyond for uttering three short paragraphs. Sentence 2: The Lone Eagle was very healthy. Choices: 1. FACE-TO-FACE, 2. GOVERNMENT, 3. LETTERS, 4. 9/11, 5. SLATE, 6. TELEPHONE, 7. TRAVEL, 8. VERBATIM, 9. OUP, 10. FICTION.
|
4
|
task198_mnli_domain_classification
|
NIv2
|
zs_opt
| 5
|
train
|
In this task, you're given a pair of sentences, sentence 1 and sentence 2. Your job is to classify the genre of the sentences from the 10 options displayed. Indicate your answer by entering the number of the choice as 1-10.
Example Input: Sentence 1: like i said i like it i like the heat i like the i jump out of the swimming pool and i go into the hot tub Sentence 2: The change in temperature is exhilarating. Choices: 1. FACE-TO-FACE, 2. GOVERNMENT, 3. LETTERS, 4. 9/11, 5. SLATE, 6. TELEPHONE, 7. TRAVEL, 8. VERBATIM, 9. OUP, 10. FICTION.
Example Output: 5
Example Input: Sentence 1: The nurse's face was framed in copper-red hair. Sentence 2: The nurse's red hair matched her red lipstick. Choices: 1. FACE-TO-FACE, 2. GOVERNMENT, 3. LETTERS, 4. 9/11, 5. SLATE, 6. TELEPHONE, 7. TRAVEL, 8. VERBATIM, 9. OUP, 10. FICTION.
Example Output: 9
Example Input: Sentence 1: Escaping unscathed from the Black Death of 1348 and subsequent plagues, it built up a sound economic base and maintained a strong army with plentiful manpower. Sentence 2: The Black Death of 1348 caused its collapse. Choices: 1. FACE-TO-FACE, 2. GOVERNMENT, 3. LETTERS, 4. 9/11, 5. SLATE, 6. TELEPHONE, 7. TRAVEL, 8. VERBATIM, 9. OUP, 10. FICTION.
Example Output:
|
6
|
task198_mnli_domain_classification
|
NIv2
|
fs_opt
| 3
|
test
|
In this task, you're given a pair of sentences, sentence 1 and sentence 2. Your job is to classify the genre of the sentences from the 10 options displayed. Indicate your answer by entering the number of the choice as 1-10.
One example: Sentence 1: Next to the MGM Grand you will find M and M World. Sentence 2: The candy has many fans who love its attractions. Choices: 1. FACE-TO-FACE, 2. GOVERNMENT, 3. LETTERS, 4. 9/11, 5. SLATE, 6. TELEPHONE, 7. TRAVEL, 8. VERBATIM, 9. OUP, 10. FICTION.
Solution is here: 1
Explanation: The places are specifically pointed out and referred to as attractions.
Now, solve this: Sentence 1: One of the first impressions you'll get at the airport in Delhi or Mumbai (Bombay) is the diversity of ethnic types. Sentence 2: One of many first impressions you'll get whilst at the airport in say, Dehli or Mumbai is the vast variety of ethnic groups. Choices: 1. FACE-TO-FACE, 2. GOVERNMENT, 3. LETTERS, 4. 9/11, 5. SLATE, 6. TELEPHONE, 7. TRAVEL, 8. VERBATIM, 9. OUP, 10. FICTION.
Solution:
|
6
|
task198_mnli_domain_classification
|
NIv2
|
fs_opt
| 6
|
validation
|
You are given an original reference as well as a system generated reference. Your task is to judge the naturaleness of the system generated reference. If the utterance could have been produced by a native speaker output 1, else output 0.
Ex Input:
System Reference: mangia tutti ristorante is a good dinner place that allows kids near financial district.
Original Reference: there is a nice restaurant called mangia tutti ristorante near the financial district that allows kid -s and is good for dinner.
Ex Output:
0
Ex Input:
System Reference: there is a sea food restaurant called alamo square seafood grill.
Original Reference: the alamo square seafood grill servers sea food.
Ex Output:
1
Ex Input:
System Reference: what type of food would you like to eat?
Original Reference: what type of food are you looking for?.
Ex Output:
|
1
|
task1186_nne_hrngo_classification
|
NIv2
|
fs_opt
| 1
|
train
|
Teacher:You are given an original reference as well as a system generated reference. Your task is to judge the naturaleness of the system generated reference. If the utterance could have been produced by a native speaker output 1, else output 0.
Teacher: Now, understand the problem? Solve this instance: System Reference: what price range are you comfortable with?
Original Reference: do you have a price range preference?.
Student:
|
1
|
task1186_nne_hrngo_classification
|
NIv2
|
zs_opt
| 6
|
train
|
Teacher: You are given an original reference as well as a system generated reference. Your task is to judge the naturaleness of the system generated reference. If the utterance could have been produced by a native speaker output 1, else output 0.
Teacher: Now, understand the problem? If you are still confused, see the following example:
System Reference: x is a reasonably priced fast food restaurant down by river cheap.
Original Reference: x is a cheap fastfood restaurant located near the riverside.
Solution: 1
Reason: The system reference could have been uttered by a native speaker.
Now, solve this instance: System Reference: there is a hotel called in the buena vista motor inn and in the area of fort mason.
Original Reference: near fort mason is the buena vista motor inn.
Student:
|
0
|
task1186_nne_hrngo_classification
|
NIv2
|
fs_opt
| 2
|
train
|
Detailed Instructions: You are given an original reference as well as a system generated reference. Your task is to judge the naturaleness of the system generated reference. If the utterance could have been produced by a native speaker output 1, else output 0.
Q: System Reference: the name of the restaurant is angkor borei restaurant.
Original Reference: angkor borei restaurant is a nice restaurant.
A:
|
1
|
task1186_nne_hrngo_classification
|
NIv2
|
zs_opt
| 9
|
train
|
You will be given a definition of a task first, then some input of the task.
You are given an original reference as well as a system generated reference. Your task is to judge the naturaleness of the system generated reference. If the utterance could have been produced by a native speaker output 1, else output 0.
System Reference: where is it near?
Original Reference: which particular location you want to be close to?.
Output:
|
1
|
task1186_nne_hrngo_classification
|
NIv2
|
zs_opt
| 1
|
train
|
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
You are given an original reference as well as a system generated reference. Your task is to judge the naturaleness of the system generated reference. If the utterance could have been produced by a native speaker output 1, else output 0.
System Reference: x is a reasonably priced fast food restaurant down by river cheap.
Original Reference: x is a cheap fastfood restaurant located near the riverside.
Solution: 1
Why? The system reference could have been uttered by a native speaker.
New input: System Reference: no hotel in north beach that does not allow dogs.
Original Reference: there are no hotel -s in the north beach area that allow dogs.
Solution:
|
0
|
task1186_nne_hrngo_classification
|
NIv2
|
fs_opt
| 0
|
train
|
You are given an original reference as well as a system generated reference. Your task is to judge the naturaleness of the system generated reference. If the utterance could have been produced by a native speaker output 1, else output 0.
[EX Q]: System Reference: what area are you looking for?
Original Reference: what part of town do you want to dine in?.
[EX A]: 0
[EX Q]: System Reference: chez maman, is a good restaurant that serves creperies food, especially for dinner.
Original Reference: chez maman serves creperies and is good for dinner.
[EX A]: 1
[EX Q]: System Reference: there is a hotel called in the inn at the presidio and in the area of presidio.
Original Reference: there is the inn at the presidio in the presidio area.
[EX A]:
|
0
|
task1186_nne_hrngo_classification
|
NIv2
|
fs_opt
| 6
|
train
|
You are given an original reference as well as a system generated reference. Your task is to judge the naturaleness of the system generated reference. If the utterance could have been produced by a native speaker output 1, else output 0.
System Reference: bund shanghai restaurant 's address is 640 jackson street.
Original Reference: bund shanghai restaurant is located at 640 jackson street.
|
1
|
task1186_nne_hrngo_classification
|
NIv2
|
zs_opt
| 0
|
train
|
You will be given a definition of a task first, then some input of the task.
You are given an original reference as well as a system generated reference. Your task is to judge the naturaleness of the system generated reference. If the utterance could have been produced by a native speaker output 1, else output 0.
System Reference: there are 89 result for a restaurant with a good dinner that allows kids.
Original Reference: there are 89 other restaurant -s that are good for dinner and allow kid -s.
Output:
|
1
|
task1186_nne_hrngo_classification
|
NIv2
|
zs_opt
| 1
|
test
|
Teacher:You are given an original reference as well as a system generated reference. Your task is to judge the naturaleness of the system generated reference. If the utterance could have been produced by a native speaker output 1, else output 0.
Teacher: Now, understand the problem? Solve this instance: System Reference: there is a ethnic food or russian restaurant called stroganoff restaurant.
Original Reference: stroganoff restaurant serves ethnic food or russian.
Student:
|
1
|
task1186_nne_hrngo_classification
|
NIv2
|
zs_opt
| 6
|
validation
|
Detailed Instructions: You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Italian.
Problem:ΧΧ ΧΧ ΧΧ Χ ΧΧΧΧΧΧ ΧΧ’Χ©ΧΧͺ ΧΧΧͺΧΧ©?
Solution:
|
Che possiamo fare alla zanzara?
|
task1111_ted_translation_he_it
|
NIv2
|
zs_opt
| 8
|
train
|
Detailed Instructions: You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Italian.
Q: ΧΧΧ ΧΧΧ©Χ ΧΧΧΧΧ.
A:
|
Γ un obiettivo impressionante.
|
task1111_ted_translation_he_it
|
NIv2
|
zs_opt
| 9
|
train
|
You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Italian.
--------
Question: ΧΧ 'ΧΧ ΧΧ§ΧΧΧΧ, ΧΧΧΧ ΧΧΧΧΧ©Χ¨, ΧΧΧ¨Χ ΧΧΧ¨Χ ΧΧΧΧ© Χ©ΧΧΧ ΧΧΧΧΧ Χ©ΧΧ‘Χ¨ΧΧΧ Χ©ΧΧΧ ΧΧΧ€Χ₯ ΧΧ¨Χ©Χͺ ΧΧΧΧ¨ΧΧ£.
Answer: E Jill e Kevin, la coppia felice, sono tornati dalla luna di miele e hanno scoperto che il loro video era diventato popolare.
Question: ΧΧ¨ΧΧ‘ ΧΧΧΧ§: ΧΧ ΧΧ ΧΧΧͺΧ ΧΧΧ ΧΧ Χ©ΧΧ ΧΧ.
Answer: Chris Milk: La mia fonte di gioia all'epoca.
Question: ΧΧΧ ΧΧ ΧΧΧ ΧΧΧΧ ΧΧͺΧͺ ΧΧͺ ΧΧ’ΧΧΧ, ΧΧΧΧΧͺΧ ΧΧ ΧΧͺΧ ΧΧΧΧͺ ΧΧΧΧ ΧΧ’Χ ΧΧΧ Χͺ.
Answer:
|
Lui non avrebbe concesso la golf car, e argomentΓ² il suo dissenso in modo interessante.
|
task1111_ted_translation_he_it
|
NIv2
|
fs_opt
| 7
|
train
|
Q: You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Italian.
ΧΧΧ ΧΧ Χ‘ΧΧ ΧΧ€Χ©ΧΧΧͺ Χ©Χ Χ¨ΧΧ ΧΧ¨ΧΧ¨ ΧΧΧΧΧ, ΧΧ ΧΧΧ‘ΧΧ Χ©Χ Χ¨ΧΧ Χ’ΧΧΧ§?
A:
|
Questo Γ¨ quel tipo di semplice che appare ovvio, o il tipo che appare profondo?
|
task1111_ted_translation_he_it
|
NIv2
|
zs_opt
| 7
|
train
|
You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Italian.
Ex Input:
ΧΧΧΧΧ ΧΧΧ, ΧΧΧΧ ΧΧΧΧ ΧΧΧΧΧ§ ΧΧΧͺΧ ΧͺΧ ΧΧΧ ΧΧΧ ΧΧΧ ΧΧΧΧΧΧ ΧΧ€Χ Χ 3.5 ΧΧΧΧΧΧ¨Χ Χ©Χ ΧΧ.
Ex Output:
A quest'altitudine, questo lago Γ¨ sottoposto alle stesse condizioni che c'erano su Marte 3,5 miliardi di anni fa.
Ex Input:
ΧΧ ΧΧΧ©ΧΧ’ΧΧͺ Χ©Χ Χ§ΧΧΧ¦Χͺ ΧΧΧ§ΧΧ¨Χͺ?
Ex Output:
Qual Γ¨ il significato dei controlli?
Ex Input:
ΧΧ©ΧΧ Χ Χ’ΧΧΧ Χ’Χ Χ¨ΧΧΧΧ, Χ©ΧΧΧ ΧΧΧΧΧ§ΧΧ ΧΧΧΧ, ΧΧ’ΧΧͺΧΧ Χ§Χ¨ΧΧΧΧͺ ΧΧ Χ ΧΧΧΧ¨ ΧΧ, "" ΧΧ ΧͺΧ’Χ§ΧΧ ΧΧΧ¨ ΧΧ Χ©ΧΧͺΧ‘Χ¨ΧΧ ΧΧΧ¨ ΧΧΧΧ¨.
Ex Output:
|
Quando lavoro con Rahman che Γ¨ un grande musicista, gli dico spesso, "" Non seguire ciΓ² che giΓ dice la sceneggiatura.
|
task1111_ted_translation_he_it
|
NIv2
|
fs_opt
| 1
|
train
|
You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Italian.
[Q]: ΧΧΧΧ¨ 'Χ ΧΧΧΧ Χ¦Χ¨ΧΧΧΧ ΧΧ©ΧΧΧͺ ΧΧͺΧΧΧ.
[A]: Loro ci devono nuotare in mezzo.
[Q]: ΧΧΧ Χ ΧΧΧ ΧΧΧ‘ΧΧΧ ΧΧ Χ’Χ Χ’Χ¨Χ ΧΧΧ Χ’Χ Χ©ΧΧΧ ΧΧΧΧΧ ΧΧ ΧΧ¦ΧΧΧ Χ ΧΧΧ€ΧΧΧͺ ΧΧͺ ΧΧ€Χ©ΧΧ’Χ ΧΧΧΧΧ¨Χͺ, Χ ΧΧΧ ΧΧ’Χ©ΧΧͺ ΧΧ©ΧΧ ΧΧ ΧΧ’Χ ΧΧΧ, ΧΧΧ’ΧͺΧ Χ.
[A]: E se concordiamo sia su un valore che su un modo di misurare se siamo stati bravi a ridurre il numero di recidivi, allora possiamo fare qualcosa che riteniamo piuttosto interessante.
[Q]: ΧΧ ΧΧΧ Χ¦ΧΧΧ¨ Χ ΧΧ£ Χ’Χ ΧΧΧΧΧΧͺ, ΧΧ¦Χ ΧΧΧΧ©ΧΧͺ Χ©ΧΧͺΧΧͺ ΧΧΧ. ΧΧΧͺΧ ΧΧ©Χ ΧΧ’ΧΧ¨ΧΧ ΧΧΧΧ§ ΧΧ§ΧΧΧ ΧΧͺΧΧͺΧΧ, ΧΧ’Χ ΧΧΧΧ’Χ ΧΧΧΧΧ¨, ΧΧΧͺΧ ΧΧΧΧͺ Χ©Χ ΧΧΧ ΧΧΧΧͺΧΧΧΧΧ ΧΧ§ΧΧΧ‘, ΧΧΧΧ ΧΧΧ¨, "" ΧΧ ΧΧ? "" ΧΧΧ Χ- ΧΧ£ ΧΧΧ ΧΧΧ¨ ΧΧ Χ’Χ©Χ ΧΧΧͺ, ΧΧ¦ΧΧ’ΧͺΧ ΧΧΧΧ¨ΧͺΧ "ΧΧ ΧΧ§ΧΧΧ ΧΧ Χ©Χ ΧΧΧ¦ΧΧΧ"
[A]:
|
Era un panorama con figure, semi vestite, che bevevano vino. C'era una donna nuda nel primo piano in basso, e una sulla collina sullo sfondo, c'era una figura del dio mitologico Bacco, e disse: "" Cos'Γ¨ questo? "" Ed io β nessun altro lo fece, per cui alzai la mano e dissi: "" E 'un Baccanale di Tiziano "".
|
task1111_ted_translation_he_it
|
NIv2
|
fs_opt
| 5
|
train
|
Instructions: You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Italian.
Input: ΧΧ© ΧΧ Χ Χ‘Χ€Χ¨ΧΧ, ΧΧΧ ΧΧ Χ ΧΧΧΧ, ΧΧΧΧ Χ¨ΧΧΧ, ΧΧΧΧͺ ΧΧΧͺΧΧ ΧΧͺ, ΧΧ¨ΧΧΧΧͺ ΧΧ¨ΧΧ.
Output:
|
Abbiamo libri, buffet e onde radio, future spose e giri sulle montagne russe.
|
task1111_ted_translation_he_it
|
NIv2
|
zs_opt
| 3
|
train
|
You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Italian.
Input: Consider Input: ΧΧ Χ ΧΧΧ©Χ Χ©ΧΧΧ Χ¦Χ¨ΧΧ ΧΧΧΧΧͺ ΧΧΧΧ’, ΧΧ ΧΧΧ ΧΧΧ€Χ©Χ¨ ΧΧͺ ΧΧΧ©Χ€ΧΧ Χ©ΧΧ.
Output: Penso che dovrebbe stare sul tronco, perchΓ© ha reso possibile la mia famiglia.
Input: Consider Input: ΧΧΧ©ΧΧ ΧΧ¨ΧΧΧ© ΧΧΧΧΧΧ, ΧΧΧ©ΧΧ ΧΧΧΧͺ ΧΧ§ΧΧ§ ΧΧΧ?
Output: Nessuno si sente minacciato? Nesuno ne ha davvero bisogno?
Input: Consider Input: ΧΧΧ Χ ΧΧΧ© Χ ΧΧ Χ‘ΧͺΧ ΧΧΧ
|
Output: E mi sono lasciato prendere.
|
task1111_ted_translation_he_it
|
NIv2
|
fs_opt
| 2
|
train
|
Instructions: You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Italian.
Input: ΧΧ¨Χ’ΧΧΧ Χ©Χ ΧΧ‘ΧΧ¨ΧΧΧΧ ΧΧ’Χ‘Χ§ΧΧ ΧΧ§ΧΧ¨Χ ΧΧ©Χ Χ Χ’Χ Χ§ΧΧ ΧΧΧ ΧΧΧ§ΧΧΧΧΧΧ: ΧΧ¨ΧΧ‘ ΧΧ ΧΧ¨Χ‘ΧΧ, ΧΧΧΧΧ‘Χ Χ©Χ BCG, ΧΧΧΧΧ§Χ Χ€ΧΧ¨ΧΧ¨, Χ€Χ¨ΧΧ€Χ‘ΧΧ¨ ΧΧΧΧͺ ΧΧ‘Χ€Χ¨ ΧΧ’Χ‘Χ§ΧΧ Χ©Χ ΧΧΧ¨ΧΧΧΧ¨Χ.
Output:
|
L'idea di strategia nel business deve le sue origini a due giganti del pensiero: Bruce Henderson, il fondatore del Boston Consulting Group, e Michael Porter, professore alla Harvard Business School.
|
task1111_ted_translation_he_it
|
NIv2
|
zs_opt
| 3
|
test
|
Q: You are given a sentence in Hebrew. Your job is to translate the Hebrew sentence into Italian.
ΧΧ ΧΧ Χ©ΧΧΧ Χ©ΧΧ ΧΧΧͺΧΧΧ ΧΧΧͺΧ¨ β ΧΧΧ Χ©ΧΧΧ¨Χ ΧΧΧͺΧ¨ ΧΧΧΧΧΧ¨ΧΧͺ β Χ¨ΧΧΧ Χ€ΧΧΧͺ, ΧΧ©ΧΧΧ Χ©ΧΧ ΧΧΧͺΧΧΧ Χ€ΧΧΧͺ β ΧΧΧ Χ©ΧΧΧ’Χ ΧΧΧ ΧΧ¦ΧΧΧΧ ΧΧΧΧΧΧ¨ ΧΧΧΧΧ¨ΧΧͺ β Χ¨ΧΧΧ ΧΧΧͺΧ¨.
A:
|
Non era che le persone piΓΉ religiose, coloro che ricordavano meglio i 10 Comandamenti, abbiano imbrogliato meno, e i meno religiosi, quelli che quasi non ne ricordavano neanche uno, abbiano invece truffato di piΓΉ.
|
task1111_ted_translation_he_it
|
NIv2
|
zs_opt
| 7
|
validation
|
In this task, you are given a text from tweets and a boolean question whether this tweet has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no".
[Q]: Tweet: I'm bored... and ready for lunch... I'm lonely... Question: is it a negative tweet?
[A]: yes
[Q]: Tweet: @thetelevixen well that's no good I want to watch L&O UK but have same problem. I want to see some Jamie Bamber!! Question: is it a negative tweet?
[A]: no
[Q]: Tweet: Work is gonna drag so much this morning.. Can't wait for hangs with James tonight Question: is it a negative tweet?
[A]:
|
no
|
task196_sentiment140_answer_generation
|
NIv2
|
fs_opt
| 5
|
train
|
In this task, you are given a text from tweets and a boolean question whether this tweet has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no".
Tweet: @Sampalm yes that's true omg why u wake up so early everyday here it's 2:42pm and i woke up at 12 pm Question: is it a negative tweet?
|
no
|
task196_sentiment140_answer_generation
|
NIv2
|
zs_opt
| 0
|
train
|
Definition: In this task, you are given a text from tweets and a boolean question whether this tweet has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no".
Input: Tweet: Watching Sonny with a chance Question: is it a positive tweet?
Output:
|
yes
|
task196_sentiment140_answer_generation
|
NIv2
|
zs_opt
| 2
|
train
|
In this task, you are given a text from tweets and a boolean question whether this tweet has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no".
Q: Tweet: Want to go home! I'm missing So You Think You Can Dance! Question: is it a positive tweet?
A: no
****
Q: Tweet: @Bobb12587 : ouch! ...my leg Question: is it a positive tweet?
A: no
****
Q: Tweet: Had an amazing time alone in my house for 3 days! A lot of icons comming ur way ppl! Question: is it a negative tweet?
A:
|
no
****
|
task196_sentiment140_answer_generation
|
NIv2
|
fs_opt
| 4
|
train
|
In this task, you are given a text from tweets and a boolean question whether this tweet has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no".
Tweet: I take no satisfaction in seeing Luongo feeling so badly. Very sad interview by Luo. Question: is it a negative tweet?
|
yes
|
task196_sentiment140_answer_generation
|
NIv2
|
zs_opt
| 0
|
train
|
Teacher:In this task, you are given a text from tweets and a boolean question whether this tweet has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no".
Teacher: Now, understand the problem? Solve this instance: Tweet: @jimbiosis Timmy says if I keep asking him silly questions he won't be my bestest friend. Question: is it a negative tweet?
Student:
|
yes
|
task196_sentiment140_answer_generation
|
NIv2
|
zs_opt
| 6
|
train
|
Given the task definition and input, reply with output. In this task, you are given a text from tweets and a boolean question whether this tweet has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no".
Tweet: Going to do some hardcore studying now. 29 terms to memorise for globals! + stuff about Imperialism, WWI, and WWII for the essay part. Question: is it a negative tweet?
|
yes
|
task196_sentiment140_answer_generation
|
NIv2
|
zs_opt
| 5
|
train
|
In this task, you are given a text from tweets and a boolean question whether this tweet has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no".
Input: Consider Input: Tweet: @AnditisLiz the c-murda youtube vid got removed Question: is it a negative tweet?
Output: yes
Input: Consider Input: Tweet: @ddlovato [Link] - awwww!! fun! it's like winter in the middle of summer! (sorta) lol Question: is it a positive tweet?
Output: yes
Input: Consider Input: Tweet: Today was our last day of school and everybody cried! It was SSSOOOO sad! Question: is it a positive tweet?
|
Output: no
|
task196_sentiment140_answer_generation
|
NIv2
|
fs_opt
| 2
|
train
|
In this task, you are given a text from tweets and a boolean question whether this tweet has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no".
Example input: Tweet: @justinchuan Awww! I was thinking about you lot up there! Glad you enjoyed it Question: is it a positive tweet?
Example output: yes
Example explanation: There is an expression of happiness in this tweet text, hence, we can say it's positive. So answer is 'yes'.
Q: Tweet: @twimtwussell yes we do! Oh well, it keeps it interesting!lol You have a great weekend too! Question: is it a negative tweet?
A:
|
no
|
task196_sentiment140_answer_generation
|
NIv2
|
fs_opt
| 3
|
test
|
In this task, you are given a text from tweets and a boolean question whether this tweet has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no".
Example input: Tweet: @justinchuan Awww! I was thinking about you lot up there! Glad you enjoyed it Question: is it a positive tweet?
Example output: yes
Example explanation: There is an expression of happiness in this tweet text, hence, we can say it's positive. So answer is 'yes'.
Q: Tweet: Heading out to Monday's in the Yard with some of my favorite people ever....well minus one but he knows he is on my mind Question: is it a positive tweet?
A:
|
yes
|
task196_sentiment140_answer_generation
|
NIv2
|
fs_opt
| 3
|
validation
|
Choices: [I] Yes. [II] No.
Q: Do you think the right answer to the question "what do most molds get their organic compounds from?" is "particles in the air", given that molds get organic compound from dead organisms?
A:
|
[I]
|
qasc_is_correct_2
|
P3
|
zs_opt
| 6
|
train
|
Do you think the right answer to the question "plants and snakes live _." is "important habitats", given that plants live just about everywhere snakes do?
OPT: (I). Yes; (II). No;
Answer:
|
(I).
|
qasc_is_correct_2
|
P3
|
zs_opt
| 1
|
train
|
Do you think the right answer to the question "intelligence is primarily encoded in what?" is "rNA", given that intelligence is primarily encoded in DNA?
OPTIONS:
- Yes
- No
Answer: No
Do you think the right answer to the question "what are highly probable in the evolution of a group of bipedal dinosaurs?" is "heat energy", given that feathers are highly probable in the evolution of a group of bipedal dinosaurs?
OPTIONS:
- Yes
- No
Answer: No
Do you think the right answer to the question "protonemas develop into what?" is "ferns", given that flowers produce spores from a protonema?
OPTIONS:
- Yes
- No
Answer:
|
No
|
qasc_is_correct_2
|
P3
|
fs_opt
| 1
|
train
|
Do you think the right answer to the question "what requires investment, seed mass, size and dispersal?" is "species", given that plants require investment, seed mass, size and dispersal. ?
i. Yes.
ii. No.
Answer:
|
i.
|
qasc_is_correct_2
|
P3
|
zs_opt
| 2
|
train
|
Do you think the right answer to the question "magnetism can cause objects to do what to each other?" is "kill them", given that magnetism can cause objects to push each other away?
Answer:
|
No
|
qasc_is_correct_2
|
P3
|
zs_noopt
| 1
|
train
|
Problem: OPTIONS:
- Yes
- No
Q: Do you think the right answer to the question "the runaway greenhouse effect present on Venus makes what unlikely?" is "bloom time", given that venus is unlikely to be able to sustain life because of a runaway greenhouse effect?
Answer: No
Problem: OPTIONS:
- Yes
- No
Q: Do you think the right answer to the question "what collects tiny grains that are the male gametes of plants?" is "viruses", given that bees collect tiny grains that are the male gametes of plants?
Answer: Yes
Problem: OPTIONS:
- Yes
- No
Q: Do you think the right answer to the question "what kind of animal is classified as having a vertebrae?" is "invertebrate", given that vertebrate chordates have a vertebrae?
Answer:
|
No
|
qasc_is_correct_2
|
P3
|
fs_opt
| 8
|
train
|
Q: Do you think the right answer to the question "what do living things require?" is "water", given that living things all require food. ? | OPTIONS:
- Yes
- No
A: No
Q: Do you think the right answer to the question "what redirects light in a camera?" is "microscope", given that a camera needs a mirror to help redirect light? | OPTIONS:
- Yes
- No
A: No
Q: Do you think the right answer to the question "what causes rocks to weather?" is "force", given that weathering of rocks is caused by water? | OPTIONS:
- Yes
- No
A: No
Q: Do you think the right answer to the question "viruses are so small that they can be seen only with a device developed where?" is "sunlight", given that viruses are so small that they can be seen only with a device developed in germany? | OPTIONS:
- Yes
- No
|
A: No
|
qasc_is_correct_2
|
P3
|
fs_opt
| 2
|
train
|
Q: Do you think the right answer to the question "what has lower temperatures?" is "fur seals", given that the mountains have lower temperatures? | OPTIONS:
- Yes
- No
A: No
Q: Do you think the right answer to the question "what grows towards a light source?" is "bacteria", given that legumes grow towards a light source? | OPTIONS:
- Yes
- No
A: No
Q: Do you think the right answer to the question "getting scraped with what can give oneself an infection?" is "a knife with sanitized dirt", given that scraping oneself on an infected needle may cause infection? | OPTIONS:
- Yes
- No
A: No
Q: Do you think the right answer to the question "what removes waste from blood?" is "leptospirosis", given that excretion removes waste from blood? | OPTIONS:
- Yes
- No
|
A: No
|
qasc_is_correct_2
|
P3
|
fs_opt
| 2
|
train
|
Q: Do you think the right answer to the question "what can cause debris?" is "erosion", given that hammers cause debris?
A:
|
No
|
qasc_is_correct_2
|
P3
|
zs_noopt
| 6
|
test
|
Q: Do you think the right answer to the question "vegetative life can live anywhere on earth and also share what characteristics?" is "sub-units of species", given that vegetative live just about everywhere on earth and are innovative and adaptive?
Options: (1). Yes. (2). No.
A:
|
(2).
|
qasc_is_correct_2
|
P3
|
zs_opt
| 3
|
validation
|
Detailed Instructions: In this task you are given a tweet. You must judge whether the tweet is ironic or not. We define two type of irony for this task ("polarity","situational"). Situational irony happens when a situation fails to meet some expectations. polarity irony happens when irony is achieved by inverting the intended sentence. Label the instances as "ironic" or "not" based on your judgment. Note that URLs in the text have been replaced with [Link].
Problem:#phillhughes #63 #out we will miss u always respect for u [Link]
Solution:
|
not
|
task386_semeval_2018_task3_irony_detection
|
NIv2
|
zs_opt
| 8
|
train
|
In this task you are given a tweet. You must judge whether the tweet is ironic or not. We define two type of irony for this task ("polarity","situational"). Situational irony happens when a situation fails to meet some expectations. polarity irony happens when irony is achieved by inverting the intended sentence. Label the instances as "ironic" or "not" based on your judgment. Note that URLs in the text have been replaced with [Link].
Example input: 3 episodes left I'm dying over here
Example output: not
Example explanation: this tweet doesn't contain irony
Q: @the_angry_ranga @UberFacts For the masses. I love it.
A:
|
not
|
task386_semeval_2018_task3_irony_detection
|
NIv2
|
fs_opt
| 3
|
train
|
In this task you are given a tweet. You must judge whether the tweet is ironic or not. We define two type of irony for this task ("polarity","situational"). Situational irony happens when a situation fails to meet some expectations. polarity irony happens when irony is achieved by inverting the intended sentence. Label the instances as "ironic" or "not" based on your judgment. Note that URLs in the text have been replaced with [Link].
--------
Question: Ostentatious "a showy display designed to impress". Thats the word I immediately think of when I see a woman feeding her child! #Idiot
Answer: ironic
Question: @DarkNetNews @Bipartisanism But it's not a time capsule! It' current in time
Answer: not
Question: hula hoops, hot chocolate and law revision. my breaks in work are filled with glamour and fun.
Answer:
|
ironic
|
task386_semeval_2018_task3_irony_detection
|
NIv2
|
fs_opt
| 7
|
train
|
Detailed Instructions: In this task you are given a tweet. You must judge whether the tweet is ironic or not. We define two type of irony for this task ("polarity","situational"). Situational irony happens when a situation fails to meet some expectations. polarity irony happens when irony is achieved by inverting the intended sentence. Label the instances as "ironic" or "not" based on your judgment. Note that URLs in the text have been replaced with [Link].
See one example below:
Problem: 3 episodes left I'm dying over here
Solution: not
Explanation: this tweet doesn't contain irony
Problem: Please instagram all your xmas presents I'm dying to see them #nobodycares
Solution:
|
ironic
|
task386_semeval_2018_task3_irony_detection
|
NIv2
|
fs_opt
| 4
|
train
|
Instructions: In this task you are given a tweet. You must judge whether the tweet is ironic or not. We define two type of irony for this task ("polarity","situational"). Situational irony happens when a situation fails to meet some expectations. polarity irony happens when irony is achieved by inverting the intended sentence. Label the instances as "ironic" or "not" based on your judgment. Note that URLs in the text have been replaced with [Link].
Input: I'm glad H & M has employed enough staff today. #nohelp #terrible
Output:
|
ironic
|
task386_semeval_2018_task3_irony_detection
|
NIv2
|
zs_opt
| 3
|
train
|
Teacher:In this task you are given a tweet. You must judge whether the tweet is ironic or not. We define two type of irony for this task ("polarity","situational"). Situational irony happens when a situation fails to meet some expectations. polarity irony happens when irony is achieved by inverting the intended sentence. Label the instances as "ironic" or "not" based on your judgment. Note that URLs in the text have been replaced with [Link].
Teacher: Now, understand the problem? Solve this instance: Cramming 200+ psych pages into my brain even though we learnt that cramming isn't effective
Student:
|
ironic
|
task386_semeval_2018_task3_irony_detection
|
NIv2
|
zs_opt
| 6
|
train
|
In this task you are given a tweet. You must judge whether the tweet is ironic or not. We define two type of irony for this task ("polarity","situational"). Situational irony happens when a situation fails to meet some expectations. polarity irony happens when irony is achieved by inverting the intended sentence. Label the instances as "ironic" or "not" based on your judgment. Note that URLs in the text have been replaced with [Link].
Let me give you an example: 3 episodes left I'm dying over here
The answer to this example can be: not
Here is why: this tweet doesn't contain irony
OK. solve this:
@nfullers98 Georgia's nativity play in the morning too..
Answer:
|
not
|
task386_semeval_2018_task3_irony_detection
|
NIv2
|
fs_opt
| 8
|
train
|
In this task you are given a tweet. You must judge whether the tweet is ironic or not. We define two type of irony for this task ("polarity","situational"). Situational irony happens when a situation fails to meet some expectations. polarity irony happens when irony is achieved by inverting the intended sentence. Label the instances as "ironic" or "not" based on your judgment. Note that URLs in the text have been replaced with [Link].
[Q]: And my christmas shopping is done.
[A]: not
[Q]: Isn't the point to learn how to craft our own reality? What am I missing here? Should we not be different? #wat?[Link]
[A]: not
[Q]: Extending trade and not telling the people about the extended trade. Best idea ever!
[A]:
|
ironic
|
task386_semeval_2018_task3_irony_detection
|
NIv2
|
fs_opt
| 5
|
train
|
Definition: In this task you are given a tweet. You must judge whether the tweet is ironic or not. We define two type of irony for this task ("polarity","situational"). Situational irony happens when a situation fails to meet some expectations. polarity irony happens when irony is achieved by inverting the intended sentence. Label the instances as "ironic" or "not" based on your judgment. Note that URLs in the text have been replaced with [Link].
Input: Today stats: 5 followers, 8 unfollowers and followed 2 people via [Link]
Output:
|
not
|
task386_semeval_2018_task3_irony_detection
|
NIv2
|
zs_opt
| 2
|
test
|
In this task you are given a tweet. You must judge whether the tweet is ironic or not. We define two type of irony for this task ("polarity","situational"). Situational irony happens when a situation fails to meet some expectations. polarity irony happens when irony is achieved by inverting the intended sentence. Label the instances as "ironic" or "not" based on your judgment. Note that URLs in the text have been replaced with [Link].
Don't forget the true meaning of Christmas:person_with_folded_hands:
not
That was one long walk :ok_hand_sign::ok_hand_sign::ok_hand_sign: #GoMe [Link]
not
Lawyer on train to other lawyer talking about ceiling ad- "who would even read that? No one's going to notice that thing..."
|
ironic
|
task386_semeval_2018_task3_irony_detection
|
NIv2
|
fs_opt
| 0
|
validation
|
Given the task definition and input, reply with output. You are given an original reference as well as a system reference. Your task is to judge the informativeness of the system reference. If the utterance provides all the useful information from the meaning representation output 1, else output 0.
System Reference: sanjalisco is near mission.
Original Reference: sanjalisco is near mission.
|
0
|
task1284_hrngo_informativeness_classification
|
NIv2
|
zs_opt
| 5
|
train
|
Definition: You are given an original reference as well as a system reference. Your task is to judge the informativeness of the system reference. If the utterance provides all the useful information from the meaning representation output 1, else output 0.
Input: System Reference: what area are you looking for a hotel in?
Original Reference: what area are you looking to stay?.
Output:
|
0
|
task1284_hrngo_informativeness_classification
|
NIv2
|
zs_opt
| 2
|
train
|
Definition: You are given an original reference as well as a system reference. Your task is to judge the informativeness of the system reference. If the utterance provides all the useful information from the meaning representation output 1, else output 0.
Input: System Reference: the address of original us restaurant is 515 columbus ave and the phone number is 4153975200.
Original Reference: original us restaurant is at 515 columbus avenue and the phone number is 4153975200.
Output:
|
1
|
task1284_hrngo_informativeness_classification
|
NIv2
|
zs_opt
| 2
|
train
|
Teacher:You are given an original reference as well as a system reference. Your task is to judge the informativeness of the system reference. If the utterance provides all the useful information from the meaning representation output 1, else output 0.
Teacher: Now, understand the problem? Solve this instance: System Reference: the phone number for red door cafe is 4152828283.
Original Reference: red door cafe number is 4152828283.
Student:
|
1
|
task1284_hrngo_informativeness_classification
|
NIv2
|
zs_opt
| 6
|
train
|
You are given an original reference as well as a system reference. Your task is to judge the informativeness of the system reference. If the utterance provides all the useful information from the meaning representation output 1, else output 0.
Example: System Reference: x is a reasonably priced fast food restaurant down by river cheap.
Original Reference: x is a cheap fastfood restaurant located near the riverside.
Example solution: 1
Example explanation: The system reference provides all the useful information.
Problem: System Reference: there are 2 restaurants which serve brunch.
Original Reference: there are 2 restaurant -s which serve brunch.
|
Solution: 1
|
task1284_hrngo_informativeness_classification
|
NIv2
|
fs_opt
| 5
|
train
|
You are given an original reference as well as a system reference. Your task is to judge the informativeness of the system reference. If the utterance provides all the useful information from the meaning representation output 1, else output 0.
Example Input: System Reference: may i ask near where?
Original Reference: are you looking for a hotel nearby?.
Example Output: 0
Example Input: System Reference: red door cafe address is 1608 bush street, and i do not know their food type.
Original Reference: the address of red door cafe is 1608 bush street. i do not know the type of food.
Example Output: 1
Example Input: System Reference: the inn on castro is in the castro area.
Original Reference: inn on castro is a hotel i found in the castro.
Example Output:
|
0
|
task1284_hrngo_informativeness_classification
|
NIv2
|
fs_opt
| 3
|
train
|
You will be given a definition of a task first, then some input of the task.
You are given an original reference as well as a system reference. Your task is to judge the informativeness of the system reference. If the utterance provides all the useful information from the meaning representation output 1, else output 0.
System Reference: pad thai restaurant allows kids, and is good for dinner.
Original Reference: pad thai restaurant is an excellent restaurant that welcome child -s and serves dinner.
Output:
|
1
|
task1284_hrngo_informativeness_classification
|
NIv2
|
zs_opt
| 1
|
train
|
You are given an original reference as well as a system reference. Your task is to judge the informativeness of the system reference. If the utterance provides all the useful information from the meaning representation output 1, else output 0.
Q: System Reference: may i ask near where?
Original Reference: what venue do you want to be near.
A: 0
****
Q: System Reference: x is a restaurant in the centre of town located near x and x.
Original Reference: x is a restaurant in the city centre, located near x and x .
A: 1
****
Q: System Reference: there are 239 restaurants in any price range.
Original Reference: there are 239 restaurant -s of any price range.
A:
|
1
****
|
task1284_hrngo_informativeness_classification
|
NIv2
|
fs_opt
| 4
|
train
|
instruction:
You are given an original reference as well as a system reference. Your task is to judge the informativeness of the system reference. If the utterance provides all the useful information from the meaning representation output 1, else output 0.
question:
System Reference: x is a french restaurant in the riverside area near x.
Original Reference: x is a restaurant by the riverside, near x providing french food. .
answer:
1
question:
System Reference: 77 restaurants do not allow kids in the moderate range.
Original Reference: there are 77 restaurant -s that have a moderate price range and do not allow kid -s.
answer:
0
question:
System Reference: the name of the restaurant is hakkasan.
Original Reference: the name of the restaurant is hakkasan.
answer:
|
1
|
task1284_hrngo_informativeness_classification
|
NIv2
|
fs_opt
| 9
|
test
|
You are given an original reference as well as a system reference. Your task is to judge the informativeness of the system reference. If the utterance provides all the useful information from the meaning representation output 1, else output 0.
Example: System Reference: x is a reasonably priced fast food restaurant down by river cheap.
Original Reference: x is a cheap fastfood restaurant located near the riverside.
Example solution: 1
Example explanation: The system reference provides all the useful information.
Problem: System Reference: what price range are you comfortable with?
Original Reference: are you looking for a certain price range?.
|
Solution: 0
|
task1284_hrngo_informativeness_classification
|
NIv2
|
fs_opt
| 5
|
validation
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.