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 |
|---|---|---|---|---|---|---|
Detailed Instructions: In this task, you are given two facts, and a multiple-choice question. Based on the given facts, answer the question with index of the correct option (e.g, "A").
Problem:Fact1: Most protists have motility., Fact2: Protists Protists are single-celled organisms., Question: What is one thing most single-celled organisms have in common? (A) Energy (B) glucose (C) bacteria (D) motility (E) Energy. (F) heat energy (G) resistance (H) warmth
Solution:
|
D
|
task1297_qasc_question_answering
|
NIv2
|
zs_opt
| 8
|
train
|
Detailed Instructions: In this task, you are given two facts, and a multiple-choice question. Based on the given facts, answer the question with index of the correct option (e.g, "A").
See one example below:
Problem: Fact1: a plant requires sunlight to grow, Fact2: Plants to avoid are fast-growing vines that can take over an area in no time., Question: What requires sunlight in order to take over an area? (A) spores (B) fish (C) plants (D) humans (E) pods (F) Oak (G) opossums (H) coral
Solution: C
Explanation: This is a good example. Based on the facts plants require sunlight in order to take over an area.
Problem: Fact1: when a hemisphere is tilted towards the sun , that hemisphere receives more direct sunlight, Fact2: Direct sunlight causes higher temperatures., Question: A hemisphere tilted toward the sun is likely to have what? (A) higher taxes (B) colors of the spectrum (C) fewer automobiles (D) wavelengths and photons (E) higher temperatures (F) rays or beams (G) electromagnetic energy (H) higher mountains
Solution:
|
E
|
task1297_qasc_question_answering
|
NIv2
|
fs_opt
| 4
|
train
|
Teacher:In this task, you are given two facts, and a multiple-choice question. Based on the given facts, answer the question with index of the correct option (e.g, "A").
Teacher: Now, understand the problem? Solve this instance: Fact1: Reproduction is the process by which living things give rise to offspring., Fact2: Sex equals reproduction., Question: What is the process by which living things give rise to offspring? (A) sex (B) diploid (C) ovum (D) bird (E) ovary (F) eggs (G) gametes (H) DNA
Student:
|
A
|
task1297_qasc_question_answering
|
NIv2
|
zs_opt
| 6
|
train
|
Detailed Instructions: In this task, you are given two facts, and a multiple-choice question. Based on the given facts, answer the question with index of the correct option (e.g, "A").
See one example below:
Problem: Fact1: a plant requires sunlight to grow, Fact2: Plants to avoid are fast-growing vines that can take over an area in no time., Question: What requires sunlight in order to take over an area? (A) spores (B) fish (C) plants (D) humans (E) pods (F) Oak (G) opossums (H) coral
Solution: C
Explanation: This is a good example. Based on the facts plants require sunlight in order to take over an area.
Problem: Fact1: Mammals have a layer of fat under the skin to help insulate the body., Fact2: An extra layer of fat also helps protect the polar bear from the cold., Question: What does a polar bear have to insulate its body? (A) white (B) Cold blood (C) Less fat (D) Warm blood (E) environment (F) Bodily water (G) Extra fat (H) Animal fur
Solution:
|
G
|
task1297_qasc_question_answering
|
NIv2
|
fs_opt
| 4
|
train
|
You will be given a definition of a task first, then some input of the task.
In this task, you are given two facts, and a multiple-choice question. Based on the given facts, answer the question with index of the correct option (e.g, "A").
Fact1: a mutation in the sex cells of a parent can cause a new trait to appear in the parent 's offspring, Fact2: Sometimes animal offspring look very different from their parents., Question: A mutation in what of a parent can cause children to look very different from their parents? (A) chromosomes (B) sex cells (C) fur and fat (D) coded genes (E) hormones (F) sperm (G) epidermal (H) Enzymes
Output:
|
B
|
task1297_qasc_question_answering
|
NIv2
|
zs_opt
| 1
|
train
|
Definition: In this task, you are given two facts, and a multiple-choice question. Based on the given facts, answer the question with index of the correct option (e.g, "A").
Input: Fact1: being burried under soil and mud changes vegetation into peat through extreme heat and pressure in a swamp over a long period of time, Fact2: Fossils are typically preserved when they are buried under many layers of sand and mud., Question: being preserved under many layers changes vegetation into peat through extreme what? (A) Physical weathering (B) Wet weather (C) heat and mud (D) Time and energy (E) scarce resources (F) heat and pressure (G) heat and vegetation (H) sand and pressure
Output:
|
F
|
task1297_qasc_question_answering
|
NIv2
|
zs_opt
| 2
|
train
|
Given the task definition, example input & output, solve the new input case.
In this task, you are given two facts, and a multiple-choice question. Based on the given facts, answer the question with index of the correct option (e.g, "A").
Example: Fact1: a plant requires sunlight to grow, Fact2: Plants to avoid are fast-growing vines that can take over an area in no time., Question: What requires sunlight in order to take over an area? (A) spores (B) fish (C) plants (D) humans (E) pods (F) Oak (G) opossums (H) coral
Output: C
This is a good example. Based on the facts plants require sunlight in order to take over an area.
New input case for you: Fact1: astronauts require preserved food for extended flights, Fact2: Preservatives are added to extend the shelf life., Question: What prolongs the storage life of food in space? (A) hydrogen and oxygen (B) preservatives (C) Dehydration (D) heating liquids (E) Fuel cells (F) heat energy (G) hard outer covering (H) layers of fat
Output:
|
B
|
task1297_qasc_question_answering
|
NIv2
|
fs_opt
| 1
|
train
|
In this task, you are given two facts, and a multiple-choice question. Based on the given facts, answer the question with index of the correct option (e.g, "A").
[Q]: Fact1: Populations of viruses do not grow through cell division because they are not cells., Fact2: Viruses are the cause of many diseases., Question: What aren't diseases caused by? (A) ovaries (B) bacteria (C) A drug. (D) humans (E) cells (F) infection (G) virus (H) cats
[A]: E
[Q]: Fact1: Mutation creates new genetic variation in a gene pool., Fact2: Mutations Mutations are random changes in the genetic information of an organism., Question: What happens when there are random changes in the genetic information of an organism? (A) New genetic variation (B) Cancer (C) cause people to become sick. (D) deadly and devastating (E) Identical twins (F) Random diseases (G) death and devastation (H) a tree falling
[A]: A
[Q]: Fact1: cell division often causes growth, Fact2: Cell division produces daughter cells of equal size., Question: Producing daughter cells of equal size often causes what? (A) pregnancy (B) eggs (C) growth (D) migrate (E) gene flow (F) disease (G) cycles (H) sperm
[A]:
|
C
|
task1297_qasc_question_answering
|
NIv2
|
fs_opt
| 5
|
train
|
In this task, you are given two facts, and a multiple-choice question. Based on the given facts, answer the question with index of the correct option (e.g, "A").
Q: Fact1: cold fronts cause thunderstorms as they pass by, Fact2: All thunderstorms produce lightning., Question: Cold fronts cause what? (A) lightning (B) Dehydration (C) erosion (D) mountains (E) sunlight (F) rainfall (G) sunsets (H) flooding
A:
|
A
|
task1297_qasc_question_answering
|
NIv2
|
zs_opt
| 4
|
test
|
In this task, you are given two facts, and a multiple-choice question. Based on the given facts, answer the question with index of the correct option (e.g, "A").
One example: Fact1: a plant requires sunlight to grow, Fact2: Plants to avoid are fast-growing vines that can take over an area in no time., Question: What requires sunlight in order to take over an area? (A) spores (B) fish (C) plants (D) humans (E) pods (F) Oak (G) opossums (H) coral
Solution is here: C
Explanation: This is a good example. Based on the facts plants require sunlight in order to take over an area.
Now, solve this: Fact1: a light bulb is used for seeing in the dark, Fact2: Conventional light bulbs generate light by heating a filament., Question: What is helpful for seeing in the dark? (A) an electron microscope (B) an electron lens (C) microscope (D) closing the blinds (E) blackouts (F) closing your eyes (G) focusing a lens (H) heating a filament
Solution:
|
H
|
task1297_qasc_question_answering
|
NIv2
|
fs_opt
| 6
|
validation
|
Please answer the following question: Here's a short story: Harry noticed that he got a much less smooth ride when travelling with his bicycle over sand than when travelling over pavement. Riding his bicycle over _____ generates less heat (A) sand (B) pavement. What is the most sensical answer between "sand" and "pavement"?
A:
|
pavement
|
quarel_heres_a_story
|
P3
|
zs_noopt
| 8
|
train
|
Please answer the following question: Here's a short story: Tom's paper plane heated up less when he flew it through the air compared to when he slid it over the table. He learned that the _____ had less friction (A) air (B) table. What is the most sensical answer between "air" and "table"?
A:
|
air
|
quarel_heres_a_story
|
P3
|
zs_noopt
| 8
|
train
|
Ques:Here's a short story: Neptune is one of the largest planets in the solar system. Which object has stronger gravity? (A) Mercury (B) Neptune. What is the most sensical answer between "Neptune" and "Mercury"?
Ans:Mercury
-----
Ques:Here's a short story: Even though she was accident prone, Emma thankfully never managed to break her glasses. After a couple of close calls, she was relieved that her expensive new glasses were _____ than her previous cheaper pairs. (A) less flexible (B) more flexible. What is the most sensical answer between "costlier glasses" and "cheaper glasses"?
Ans:cheaper glasses
-----
Ques:Here's a short story: Pushing a safety pin into thin paper is easier then pushing it into thick paper. Which paper will allow the safety pin to plunge into it at a faster rate of speed? (A) thick paper (B) thin paper. What is the most sensical answer between "thin paper" and "thick paper"?
Ans:thick paper
-----
Ques:Here's a short story: Jameson is walking along the road that borders the beach. Above him is a streetlight, while in the distance, the blinking light of a buoy can be seen. The streetlight is the more vibrant of the two because (A) He is directly under it (B) He is many yards away from it. What is the most sensical answer between "streetlight" and "light of a buoy"?
Ans:
|
streetlight
-----
|
quarel_heres_a_story
|
P3
|
fs_opt
| 9
|
train
|
Here's a short story: When the race car engine started up in the driveway it was very loud but as it pulled away and got farther away it became (A) louder (B) quieter.. What is the most sensical answer between "Engine far away" and "Engine nearby"?
Engine nearby
------
Here's a short story: Harold pulled his dogcart through a gravel path before travelling on a paved road while going to the store. The paved road was much less rough then the gravel path, so he wondered whether the _____ had less friction (A) gravel path (B) paved road. What is the most sensical answer between "paved road" and "gravel path"?
gravel path
------
Here's a short story: The class is outside for P.E., half the children have chosen to walk their 4 laps, while the other half run the same distance. Which half will likely sweat more? (A) Students who walk (B) Students who run. What is the most sensical answer between "students who run" and "students who walk"?
students who walk
------
Here's a short story: I skater zipped quickly across the ice rink floor but much slower on the tile because it had (A) more resistance (B) less resistance. What is the most sensical answer between "tile" and "ice rink floor"?
|
tile
------
|
quarel_heres_a_story
|
P3
|
fs_opt
| 5
|
train
|
Ques:Here's a short story: Jeri noticed that the pool cue ball moves faster on the felt of the table than on the carpeted game room floor. The cue ball moves faster on the felt surface because the felt has (A) less resistance (B) more resistance. What is the most sensical answer between "felt" and "carpet"?
Ans:felt
-----
Ques:Here's a short story: Juan is injured in a car accident, which necessitates a hospital stay where he is unable to maintain the strength in his arm. Juan notices that his throwing arm feels extremely frail compared to the level of strength it had when he was healthy. If Juan decides to throw a ball with his friend, when will his throw travel less distance? (A) When Juan's arm is healthy (B) When Juan's arm is weak after the hospital stay.. What is the most sensical answer between "Juan after a hospital stay" and "Juan when healthy"?
Ans:Juan when healthy
-----
Ques:Here's a short story: Taylor pushes her shopping cart over a tile floor then over a door mat. The shopping cart moves more slowly over the door mat than it does the tile floor as a result of there being more friction on the (A) door mat (B) tile floor.. What is the most sensical answer between "door mat" and "tile floor"?
Ans:door mat
-----
Ques:Here's a short story: The monkey was much stronger than the man so it was able to throw a ball (A) farther (B) less far. What is the most sensical answer between "Monkey" and "Man"?
Ans:
|
Monkey
-----
|
quarel_heres_a_story
|
P3
|
fs_opt
| 9
|
train
|
(Question)
Here's a short story: John's whiffle ball warms up more when he rolls it over desert compared to when he rolls it over his driveway. The surface of the _____ is more smooth (A) desert (B) driveway. What is the most sensical answer between "desert" and "driveway"?
(Answer)
driveway
(Question)
Here's a short story: A man punches a tire and a wood board for a demonstration. The board if very stiff. Which object do you think is more likely to break? (A) Tire (B) Wood Board. What is the most sensical answer between "Wood Board" and "Tire"?
(Answer)
Tire
(Question)
Here's a short story: Terry is in much better shape than he was when he was in high school. Terry has played baseball since high school. Terry throws the baseball (A) further than in high school (B) less far than in high school. What is the most sensical answer between "in better shape now" and "in high school"?
(Answer)
|
in better shape now
|
quarel_heres_a_story
|
P3
|
fs_opt
| 6
|
train
|
Q: Here's a short story: Gary is trying to bend different things. He tries to bend a rubber mat and a wooden pencil. Which breaks first? (A) rubber mat (B) wooden pencil. What is the most sensical answer between "wooden pencil" and "rubber mat"?
A: rubber mat
Q: Here's a short story: Ben is playing with a remote control car. It goes up a ramp very easily. When it lands on the grass, he has trouble getting the car to maintain speed. This is because the surface of the _____ is rougher. (A) wood ramp (B) grass. What is the most sensical answer between "wood ramp" and "grass"?
A: grass
Q: Here's a short story: Bill and Dan both throw a rock. Dan throws it much farther than Bill meaning Dan is (A) very buff (B) not buff. What is the most sensical answer between "Dan" and "Bill"?
A: Dan
Q: Here's a short story: Tommy found that his new hoverboard was faster on the _____ because there was less resistance. (A) sidewalk (B) gravel road. What is the most sensical answer between "sidewalk" and "gravel road"?
|
A: sidewalk
|
quarel_heres_a_story
|
P3
|
fs_opt
| 2
|
train
|
Answer the following question: Here's a short story: A child slips more easily on ice than on a sidewalk. This is because there is less friction on the (A) ice (B) sidewalk.. What is the most sensical answer between "ice" and "sidewalk"?
Answer:
|
ice
|
quarel_heres_a_story
|
P3
|
zs_opt
| 5
|
train
|
Here's a short story: The unicycle was able to pick up more speed on the asphalt versus the beach sand because (A) the asphalt has lower resistance (B) the asphalt has higher resistance. What is the most sensical answer between "asphalt" and "beach sand"?
The answer to this question is:
|
asphalt
|
quarel_heres_a_story
|
P3
|
zs_noopt
| 7
|
test
|
Here's a short story: A boomerang thrown into a windy sky heats up quite a bit, but one thrown into a calm sky stays about the same temperature. Which surface puts the least amount of friction on the boomerang? (A) windy sky (B) calm sky. What is the most sensical answer between "windy sky" and "calm sky"?
calm sky
Here's a short story: Bannon tossed the basketball on the pavement. He also tossed it in the sand. Bannon noticed that in the sand the basketball moved at a more sluggish speed than it did on the pavement. To Bannon it appeared that less friction on the the basketball happened on the (A) pavement (B) sand.. What is the most sensical answer between "sand" and "pavement"?
sand
Q: Here's a short story: A person that is walking will take _____ than a person that is running (A) more time to make a trip (B) less time to make a trip. What is the most sensical answer between "Running" and "Walking"?
A: Running
Question: Here's a short story: William notices that when he pets his bearded dragon, it's skin is much rougher than he notices when he pets his bunny rabbit. The surface of the pet that has less friction is the (A) bearded dragon (B) bunny rabbit. What is the most sensical answer between "bearded dragon" and "bunny rabbit"?
Answer: bunny rabbit
*Question*
Here's a short story: As Judy is walking into the cave with her flashlight and Kate is standing at the entrance watching her go, the light from the flashlight will (A) get brighter as she walks away (B) get dimmer as she walks away.. What is the most sensical answer between "flashlight far" and "flashlight close"?
**Answer**
flashlight close
Here's a short story: Jessie walked to the store, while Jim drove to it. Who would reach to the destination the fastest: (A) Jessie because he was walking(B) Jim because he was driving. What is the most sensical answer between "person in car" and "person walking"?
|
person walking
|
quarel_heres_a_story
|
P3
|
fs_opt
| 0
|
validation
|
Given the task definition, example input & output, solve the new input case.
In this task, based on the given context word, you are asked to create a pair of sentences each containing a blank (_) and their corresponding answer. The sentence pair should look similar, and should be about two related but different objects; for example "trophy" and "suitcase". Additionally, the two sentences must be different in terms of trigger words (e.g., "small" and "big") which express contrasting properties about the two objects. The answer must not be associated with the trigger word; instead, it should depend on the context present in twin sentences. Also, the answers should not be ambiguous. For each sentence, there should be an agreed upon answer to fill in the blank. Your generations should NOT contain potentially explicit, offensive, or adult content. Do not use animals and proper nouns (e.g., New York, Macbook, Jeff Bezos, McDonald's, ...) as your objects. Avoid repeating the same style or phrase in twin sentences. E.g., a contrasting sentence can always be created using simple negation i.e. by adding not, never, etc. Instead, try to increase diversity. Both twin sentences must contain at least 15 and at most 30 words. Twin sentences must have at least 70% overlapping words. You must utilize the given context word while writing the twin sentences. Each of the twin sentences must contain only one blank. Make sure that ObjectX and Y have the same number e.g. when ObjectX is singular, ObjectY must be singular, too. The two objects (ObjectX & ObjectY) should be used ONCE in each sentence. Here is a list of contrastive words that may be used as trigger words. You should create more such trigger words and use them in your twin sentences.
| Attribute | triggerword | contrastive triggerword |
| age | old | new |
| altitude | low | high |
| area | small | vast |
| brightness | dark | light |
| clarity | obscure | clear |
| cleanness | dirty | clean |
| complexity | simple | complex |
| cost | cheap | expensive |
| density | sparse | dense |
| depth | shallow | deep |
| distance | near | far |
| electric conductivity | low | high |
| flexibility | rigid | flexible |
| granularity | fine | coarse |
| hardness | soft | hard |
| length | short | long |
| magnitude | small | large |
| mass | small | large |
| odor | weak | strong |
| pressure | low | high |
| resistance | low | high |
| shape | round | sharp |
| shape | flat | spiky |
| size | small | large |
| sound | quiet | loud |
| sound pitch | low | high |
| speed | slow | fast |
| stability | unstable | stable |
| strength | weak | strong |
| temperature | low | high |
| texture | smooth | rough |
| thermal conductivity | low | high |
| thickness | thin | thick |
| volume | small | large |
| weight | light | heavy |
| width | narrow | wide |
| location | in | out |
| location | up | down |
| location | above | below |
| location | on | off |
| location | to | from |
Example: Context word: fit.
Output: Sentence 1: The trophy doesn't fit into the brown suitcase because _ is too large.
Answer1: trophy.
Sentence 2: The trophy doesn't fit into the brown suitcase because _ is too small.
Answer2: suitcase.
Here, the two objects are "trophy" and "suitcase". The trigger words are "large" and "small". Everything else (apart from the trigger words) are the same in the two sentences. The two sentences have different answers, which are the two objects ("trophy" and "suitcase").
New input case for you: Context Word: organ.
Output:
|
Sentence 1: The music sounded better coming from the organ than the piano because the _ was old and needed tuning.
Answer1: piano.
Sentence 2: The music sounded better coming from the organ than the piano because the _ was big and impressive.
Answer2: organ.
|
task029_winogrande_full_object
|
NIv2
|
fs_opt
| 1
|
train
|
Detailed Instructions: In this task, based on the given context word, you are asked to create a pair of sentences each containing a blank (_) and their corresponding answer. The sentence pair should look similar, and should be about two related but different objects; for example "trophy" and "suitcase". Additionally, the two sentences must be different in terms of trigger words (e.g., "small" and "big") which express contrasting properties about the two objects. The answer must not be associated with the trigger word; instead, it should depend on the context present in twin sentences. Also, the answers should not be ambiguous. For each sentence, there should be an agreed upon answer to fill in the blank. Your generations should NOT contain potentially explicit, offensive, or adult content. Do not use animals and proper nouns (e.g., New York, Macbook, Jeff Bezos, McDonald's, ...) as your objects. Avoid repeating the same style or phrase in twin sentences. E.g., a contrasting sentence can always be created using simple negation i.e. by adding not, never, etc. Instead, try to increase diversity. Both twin sentences must contain at least 15 and at most 30 words. Twin sentences must have at least 70% overlapping words. You must utilize the given context word while writing the twin sentences. Each of the twin sentences must contain only one blank. Make sure that ObjectX and Y have the same number e.g. when ObjectX is singular, ObjectY must be singular, too. The two objects (ObjectX & ObjectY) should be used ONCE in each sentence. Here is a list of contrastive words that may be used as trigger words. You should create more such trigger words and use them in your twin sentences.
| Attribute | triggerword | contrastive triggerword |
| age | old | new |
| altitude | low | high |
| area | small | vast |
| brightness | dark | light |
| clarity | obscure | clear |
| cleanness | dirty | clean |
| complexity | simple | complex |
| cost | cheap | expensive |
| density | sparse | dense |
| depth | shallow | deep |
| distance | near | far |
| electric conductivity | low | high |
| flexibility | rigid | flexible |
| granularity | fine | coarse |
| hardness | soft | hard |
| length | short | long |
| magnitude | small | large |
| mass | small | large |
| odor | weak | strong |
| pressure | low | high |
| resistance | low | high |
| shape | round | sharp |
| shape | flat | spiky |
| size | small | large |
| sound | quiet | loud |
| sound pitch | low | high |
| speed | slow | fast |
| stability | unstable | stable |
| strength | weak | strong |
| temperature | low | high |
| texture | smooth | rough |
| thermal conductivity | low | high |
| thickness | thin | thick |
| volume | small | large |
| weight | light | heavy |
| width | narrow | wide |
| location | in | out |
| location | up | down |
| location | above | below |
| location | on | off |
| location | to | from |
Q: Context Word: instrument.
A:
|
Sentence 1: I've never been able to tell the difference between instruments like cello and a violin. I think the _ is just a larger version.
Answer1: cello.
Sentence 2: I've never been able to tell the difference between instruments like cello and a violin. I think the _ is just a smaller version.
Answer2: violin.
|
task029_winogrande_full_object
|
NIv2
|
zs_opt
| 9
|
train
|
Teacher: In this task, based on the given context word, you are asked to create a pair of sentences each containing a blank (_) and their corresponding answer. The sentence pair should look similar, and should be about two related but different objects; for example "trophy" and "suitcase". Additionally, the two sentences must be different in terms of trigger words (e.g., "small" and "big") which express contrasting properties about the two objects. The answer must not be associated with the trigger word; instead, it should depend on the context present in twin sentences. Also, the answers should not be ambiguous. For each sentence, there should be an agreed upon answer to fill in the blank. Your generations should NOT contain potentially explicit, offensive, or adult content. Do not use animals and proper nouns (e.g., New York, Macbook, Jeff Bezos, McDonald's, ...) as your objects. Avoid repeating the same style or phrase in twin sentences. E.g., a contrasting sentence can always be created using simple negation i.e. by adding not, never, etc. Instead, try to increase diversity. Both twin sentences must contain at least 15 and at most 30 words. Twin sentences must have at least 70% overlapping words. You must utilize the given context word while writing the twin sentences. Each of the twin sentences must contain only one blank. Make sure that ObjectX and Y have the same number e.g. when ObjectX is singular, ObjectY must be singular, too. The two objects (ObjectX & ObjectY) should be used ONCE in each sentence. Here is a list of contrastive words that may be used as trigger words. You should create more such trigger words and use them in your twin sentences.
| Attribute | triggerword | contrastive triggerword |
| age | old | new |
| altitude | low | high |
| area | small | vast |
| brightness | dark | light |
| clarity | obscure | clear |
| cleanness | dirty | clean |
| complexity | simple | complex |
| cost | cheap | expensive |
| density | sparse | dense |
| depth | shallow | deep |
| distance | near | far |
| electric conductivity | low | high |
| flexibility | rigid | flexible |
| granularity | fine | coarse |
| hardness | soft | hard |
| length | short | long |
| magnitude | small | large |
| mass | small | large |
| odor | weak | strong |
| pressure | low | high |
| resistance | low | high |
| shape | round | sharp |
| shape | flat | spiky |
| size | small | large |
| sound | quiet | loud |
| sound pitch | low | high |
| speed | slow | fast |
| stability | unstable | stable |
| strength | weak | strong |
| temperature | low | high |
| texture | smooth | rough |
| thermal conductivity | low | high |
| thickness | thin | thick |
| volume | small | large |
| weight | light | heavy |
| width | narrow | wide |
| location | in | out |
| location | up | down |
| location | above | below |
| location | on | off |
| location | to | from |
Teacher: Now, understand the problem? If you are still confused, see the following example:
Context word: fit.
Solution: Sentence 1: The trophy doesn't fit into the brown suitcase because _ is too large.
Answer1: trophy.
Sentence 2: The trophy doesn't fit into the brown suitcase because _ is too small.
Answer2: suitcase.
Reason: Here, the two objects are "trophy" and "suitcase". The trigger words are "large" and "small". Everything else (apart from the trigger words) are the same in the two sentences. The two sentences have different answers, which are the two objects ("trophy" and "suitcase").
Now, solve this instance: Context Word: atm.
Student:
|
Sentence 1: Don needed to go to the atm to get money out, but the _ was not working.
Answer1: atm.
Sentence 2: Don needed to go to the atm to get money out, because the _ was gone.
Answer2: money.
|
task029_winogrande_full_object
|
NIv2
|
fs_opt
| 2
|
train
|
Instructions: In this task, based on the given context word, you are asked to create a pair of sentences each containing a blank (_) and their corresponding answer. The sentence pair should look similar, and should be about two related but different objects; for example "trophy" and "suitcase". Additionally, the two sentences must be different in terms of trigger words (e.g., "small" and "big") which express contrasting properties about the two objects. The answer must not be associated with the trigger word; instead, it should depend on the context present in twin sentences. Also, the answers should not be ambiguous. For each sentence, there should be an agreed upon answer to fill in the blank. Your generations should NOT contain potentially explicit, offensive, or adult content. Do not use animals and proper nouns (e.g., New York, Macbook, Jeff Bezos, McDonald's, ...) as your objects. Avoid repeating the same style or phrase in twin sentences. E.g., a contrasting sentence can always be created using simple negation i.e. by adding not, never, etc. Instead, try to increase diversity. Both twin sentences must contain at least 15 and at most 30 words. Twin sentences must have at least 70% overlapping words. You must utilize the given context word while writing the twin sentences. Each of the twin sentences must contain only one blank. Make sure that ObjectX and Y have the same number e.g. when ObjectX is singular, ObjectY must be singular, too. The two objects (ObjectX & ObjectY) should be used ONCE in each sentence. Here is a list of contrastive words that may be used as trigger words. You should create more such trigger words and use them in your twin sentences.
| Attribute | triggerword | contrastive triggerword |
| age | old | new |
| altitude | low | high |
| area | small | vast |
| brightness | dark | light |
| clarity | obscure | clear |
| cleanness | dirty | clean |
| complexity | simple | complex |
| cost | cheap | expensive |
| density | sparse | dense |
| depth | shallow | deep |
| distance | near | far |
| electric conductivity | low | high |
| flexibility | rigid | flexible |
| granularity | fine | coarse |
| hardness | soft | hard |
| length | short | long |
| magnitude | small | large |
| mass | small | large |
| odor | weak | strong |
| pressure | low | high |
| resistance | low | high |
| shape | round | sharp |
| shape | flat | spiky |
| size | small | large |
| sound | quiet | loud |
| sound pitch | low | high |
| speed | slow | fast |
| stability | unstable | stable |
| strength | weak | strong |
| temperature | low | high |
| texture | smooth | rough |
| thermal conductivity | low | high |
| thickness | thin | thick |
| volume | small | large |
| weight | light | heavy |
| width | narrow | wide |
| location | in | out |
| location | up | down |
| location | above | below |
| location | on | off |
| location | to | from |
Input: Context Word: positively.
Output:
|
Sentence 1: She was trying to think more positively so she dusted off a self-help book and picked up a journal. The _ was old.
Answer1: book.
Sentence 2: She was trying to think more positively so she dusted off a self-help book and picked up a journal. The _ was new.
Answer2: journal.
|
task029_winogrande_full_object
|
NIv2
|
zs_opt
| 3
|
train
|
Detailed Instructions: In this task, based on the given context word, you are asked to create a pair of sentences each containing a blank (_) and their corresponding answer. The sentence pair should look similar, and should be about two related but different objects; for example "trophy" and "suitcase". Additionally, the two sentences must be different in terms of trigger words (e.g., "small" and "big") which express contrasting properties about the two objects. The answer must not be associated with the trigger word; instead, it should depend on the context present in twin sentences. Also, the answers should not be ambiguous. For each sentence, there should be an agreed upon answer to fill in the blank. Your generations should NOT contain potentially explicit, offensive, or adult content. Do not use animals and proper nouns (e.g., New York, Macbook, Jeff Bezos, McDonald's, ...) as your objects. Avoid repeating the same style or phrase in twin sentences. E.g., a contrasting sentence can always be created using simple negation i.e. by adding not, never, etc. Instead, try to increase diversity. Both twin sentences must contain at least 15 and at most 30 words. Twin sentences must have at least 70% overlapping words. You must utilize the given context word while writing the twin sentences. Each of the twin sentences must contain only one blank. Make sure that ObjectX and Y have the same number e.g. when ObjectX is singular, ObjectY must be singular, too. The two objects (ObjectX & ObjectY) should be used ONCE in each sentence. Here is a list of contrastive words that may be used as trigger words. You should create more such trigger words and use them in your twin sentences.
| Attribute | triggerword | contrastive triggerword |
| age | old | new |
| altitude | low | high |
| area | small | vast |
| brightness | dark | light |
| clarity | obscure | clear |
| cleanness | dirty | clean |
| complexity | simple | complex |
| cost | cheap | expensive |
| density | sparse | dense |
| depth | shallow | deep |
| distance | near | far |
| electric conductivity | low | high |
| flexibility | rigid | flexible |
| granularity | fine | coarse |
| hardness | soft | hard |
| length | short | long |
| magnitude | small | large |
| mass | small | large |
| odor | weak | strong |
| pressure | low | high |
| resistance | low | high |
| shape | round | sharp |
| shape | flat | spiky |
| size | small | large |
| sound | quiet | loud |
| sound pitch | low | high |
| speed | slow | fast |
| stability | unstable | stable |
| strength | weak | strong |
| temperature | low | high |
| texture | smooth | rough |
| thermal conductivity | low | high |
| thickness | thin | thick |
| volume | small | large |
| weight | light | heavy |
| width | narrow | wide |
| location | in | out |
| location | up | down |
| location | above | below |
| location | on | off |
| location | to | from |
Problem:Context Word: blog.
Solution:
|
Sentence 1: Amelia and Clare's blog included both essays and listicles. Because Amelia was a more lighthearted writer, she wrote the _ .
Answer1: listicles.
Sentence 2: Amelia and Clare's blog included both essays and listicles. Because Clare was a more serious writer, she wrote the _ .
Answer2: essays.
|
task029_winogrande_full_object
|
NIv2
|
zs_opt
| 8
|
train
|
Given the task definition and input, reply with output. In this task, based on the given context word, you are asked to create a pair of sentences each containing a blank (_) and their corresponding answer. The sentence pair should look similar, and should be about two related but different objects; for example "trophy" and "suitcase". Additionally, the two sentences must be different in terms of trigger words (e.g., "small" and "big") which express contrasting properties about the two objects. The answer must not be associated with the trigger word; instead, it should depend on the context present in twin sentences. Also, the answers should not be ambiguous. For each sentence, there should be an agreed upon answer to fill in the blank. Your generations should NOT contain potentially explicit, offensive, or adult content. Do not use animals and proper nouns (e.g., New York, Macbook, Jeff Bezos, McDonald's, ...) as your objects. Avoid repeating the same style or phrase in twin sentences. E.g., a contrasting sentence can always be created using simple negation i.e. by adding not, never, etc. Instead, try to increase diversity. Both twin sentences must contain at least 15 and at most 30 words. Twin sentences must have at least 70% overlapping words. You must utilize the given context word while writing the twin sentences. Each of the twin sentences must contain only one blank. Make sure that ObjectX and Y have the same number e.g. when ObjectX is singular, ObjectY must be singular, too. The two objects (ObjectX & ObjectY) should be used ONCE in each sentence. Here is a list of contrastive words that may be used as trigger words. You should create more such trigger words and use them in your twin sentences.
| Attribute | triggerword | contrastive triggerword |
| age | old | new |
| altitude | low | high |
| area | small | vast |
| brightness | dark | light |
| clarity | obscure | clear |
| cleanness | dirty | clean |
| complexity | simple | complex |
| cost | cheap | expensive |
| density | sparse | dense |
| depth | shallow | deep |
| distance | near | far |
| electric conductivity | low | high |
| flexibility | rigid | flexible |
| granularity | fine | coarse |
| hardness | soft | hard |
| length | short | long |
| magnitude | small | large |
| mass | small | large |
| odor | weak | strong |
| pressure | low | high |
| resistance | low | high |
| shape | round | sharp |
| shape | flat | spiky |
| size | small | large |
| sound | quiet | loud |
| sound pitch | low | high |
| speed | slow | fast |
| stability | unstable | stable |
| strength | weak | strong |
| temperature | low | high |
| texture | smooth | rough |
| thermal conductivity | low | high |
| thickness | thin | thick |
| volume | small | large |
| weight | light | heavy |
| width | narrow | wide |
| location | in | out |
| location | up | down |
| location | above | below |
| location | on | off |
| location | to | from |
Context Word: toddler.
|
Sentence 1: Mary walked her toddler to preschool, and on the way they found a twig and a newspaper. The _ was on the sidewalk.
Answer1: twig.
Sentence 2: Mary walked her toddler to preschool, and on the way they found a twig and a newspaper. The _ was on a table.
Answer2: newspaper.
|
task029_winogrande_full_object
|
NIv2
|
zs_opt
| 5
|
train
|
Instructions: In this task, based on the given context word, you are asked to create a pair of sentences each containing a blank (_) and their corresponding answer. The sentence pair should look similar, and should be about two related but different objects; for example "trophy" and "suitcase". Additionally, the two sentences must be different in terms of trigger words (e.g., "small" and "big") which express contrasting properties about the two objects. The answer must not be associated with the trigger word; instead, it should depend on the context present in twin sentences. Also, the answers should not be ambiguous. For each sentence, there should be an agreed upon answer to fill in the blank. Your generations should NOT contain potentially explicit, offensive, or adult content. Do not use animals and proper nouns (e.g., New York, Macbook, Jeff Bezos, McDonald's, ...) as your objects. Avoid repeating the same style or phrase in twin sentences. E.g., a contrasting sentence can always be created using simple negation i.e. by adding not, never, etc. Instead, try to increase diversity. Both twin sentences must contain at least 15 and at most 30 words. Twin sentences must have at least 70% overlapping words. You must utilize the given context word while writing the twin sentences. Each of the twin sentences must contain only one blank. Make sure that ObjectX and Y have the same number e.g. when ObjectX is singular, ObjectY must be singular, too. The two objects (ObjectX & ObjectY) should be used ONCE in each sentence. Here is a list of contrastive words that may be used as trigger words. You should create more such trigger words and use them in your twin sentences.
| Attribute | triggerword | contrastive triggerword |
| age | old | new |
| altitude | low | high |
| area | small | vast |
| brightness | dark | light |
| clarity | obscure | clear |
| cleanness | dirty | clean |
| complexity | simple | complex |
| cost | cheap | expensive |
| density | sparse | dense |
| depth | shallow | deep |
| distance | near | far |
| electric conductivity | low | high |
| flexibility | rigid | flexible |
| granularity | fine | coarse |
| hardness | soft | hard |
| length | short | long |
| magnitude | small | large |
| mass | small | large |
| odor | weak | strong |
| pressure | low | high |
| resistance | low | high |
| shape | round | sharp |
| shape | flat | spiky |
| size | small | large |
| sound | quiet | loud |
| sound pitch | low | high |
| speed | slow | fast |
| stability | unstable | stable |
| strength | weak | strong |
| temperature | low | high |
| texture | smooth | rough |
| thermal conductivity | low | high |
| thickness | thin | thick |
| volume | small | large |
| weight | light | heavy |
| width | narrow | wide |
| location | in | out |
| location | up | down |
| location | above | below |
| location | on | off |
| location | to | from |
Input: Context Word: chlorine.
Output:
|
Sentence 1: Jenna added chlorine gradually to her pool, because she wanted to make sure that the _ was making it cleaner.
Answer1: chlorine.
Sentence 2: Jenna added chlorine gradually to her pool, because she wanted to make sure that the _ was not salty.
Answer2: pool.
|
task029_winogrande_full_object
|
NIv2
|
zs_opt
| 3
|
train
|
Q: In this task, based on the given context word, you are asked to create a pair of sentences each containing a blank (_) and their corresponding answer. The sentence pair should look similar, and should be about two related but different objects; for example "trophy" and "suitcase". Additionally, the two sentences must be different in terms of trigger words (e.g., "small" and "big") which express contrasting properties about the two objects. The answer must not be associated with the trigger word; instead, it should depend on the context present in twin sentences. Also, the answers should not be ambiguous. For each sentence, there should be an agreed upon answer to fill in the blank. Your generations should NOT contain potentially explicit, offensive, or adult content. Do not use animals and proper nouns (e.g., New York, Macbook, Jeff Bezos, McDonald's, ...) as your objects. Avoid repeating the same style or phrase in twin sentences. E.g., a contrasting sentence can always be created using simple negation i.e. by adding not, never, etc. Instead, try to increase diversity. Both twin sentences must contain at least 15 and at most 30 words. Twin sentences must have at least 70% overlapping words. You must utilize the given context word while writing the twin sentences. Each of the twin sentences must contain only one blank. Make sure that ObjectX and Y have the same number e.g. when ObjectX is singular, ObjectY must be singular, too. The two objects (ObjectX & ObjectY) should be used ONCE in each sentence. Here is a list of contrastive words that may be used as trigger words. You should create more such trigger words and use them in your twin sentences.
| Attribute | triggerword | contrastive triggerword |
| age | old | new |
| altitude | low | high |
| area | small | vast |
| brightness | dark | light |
| clarity | obscure | clear |
| cleanness | dirty | clean |
| complexity | simple | complex |
| cost | cheap | expensive |
| density | sparse | dense |
| depth | shallow | deep |
| distance | near | far |
| electric conductivity | low | high |
| flexibility | rigid | flexible |
| granularity | fine | coarse |
| hardness | soft | hard |
| length | short | long |
| magnitude | small | large |
| mass | small | large |
| odor | weak | strong |
| pressure | low | high |
| resistance | low | high |
| shape | round | sharp |
| shape | flat | spiky |
| size | small | large |
| sound | quiet | loud |
| sound pitch | low | high |
| speed | slow | fast |
| stability | unstable | stable |
| strength | weak | strong |
| temperature | low | high |
| texture | smooth | rough |
| thermal conductivity | low | high |
| thickness | thin | thick |
| volume | small | large |
| weight | light | heavy |
| width | narrow | wide |
| location | in | out |
| location | up | down |
| location | above | below |
| location | on | off |
| location | to | from |
Context Word: transition.
A:
|
Sentence 1: When he wanted to transition a firefighter, they told him he was too short and weak. The _ issue was harder to resolve.
Answer1: short.
Sentence 2: When he wanted to transition a firefighter, they told him he was too short and weak. The _ issue was easier to resolve.
Answer2: weak.
|
task029_winogrande_full_object
|
NIv2
|
zs_opt
| 7
|
train
|
Teacher: In this task, based on the given context word, you are asked to create a pair of sentences each containing a blank (_) and their corresponding answer. The sentence pair should look similar, and should be about two related but different objects; for example "trophy" and "suitcase". Additionally, the two sentences must be different in terms of trigger words (e.g., "small" and "big") which express contrasting properties about the two objects. The answer must not be associated with the trigger word; instead, it should depend on the context present in twin sentences. Also, the answers should not be ambiguous. For each sentence, there should be an agreed upon answer to fill in the blank. Your generations should NOT contain potentially explicit, offensive, or adult content. Do not use animals and proper nouns (e.g., New York, Macbook, Jeff Bezos, McDonald's, ...) as your objects. Avoid repeating the same style or phrase in twin sentences. E.g., a contrasting sentence can always be created using simple negation i.e. by adding not, never, etc. Instead, try to increase diversity. Both twin sentences must contain at least 15 and at most 30 words. Twin sentences must have at least 70% overlapping words. You must utilize the given context word while writing the twin sentences. Each of the twin sentences must contain only one blank. Make sure that ObjectX and Y have the same number e.g. when ObjectX is singular, ObjectY must be singular, too. The two objects (ObjectX & ObjectY) should be used ONCE in each sentence. Here is a list of contrastive words that may be used as trigger words. You should create more such trigger words and use them in your twin sentences.
| Attribute | triggerword | contrastive triggerword |
| age | old | new |
| altitude | low | high |
| area | small | vast |
| brightness | dark | light |
| clarity | obscure | clear |
| cleanness | dirty | clean |
| complexity | simple | complex |
| cost | cheap | expensive |
| density | sparse | dense |
| depth | shallow | deep |
| distance | near | far |
| electric conductivity | low | high |
| flexibility | rigid | flexible |
| granularity | fine | coarse |
| hardness | soft | hard |
| length | short | long |
| magnitude | small | large |
| mass | small | large |
| odor | weak | strong |
| pressure | low | high |
| resistance | low | high |
| shape | round | sharp |
| shape | flat | spiky |
| size | small | large |
| sound | quiet | loud |
| sound pitch | low | high |
| speed | slow | fast |
| stability | unstable | stable |
| strength | weak | strong |
| temperature | low | high |
| texture | smooth | rough |
| thermal conductivity | low | high |
| thickness | thin | thick |
| volume | small | large |
| weight | light | heavy |
| width | narrow | wide |
| location | in | out |
| location | up | down |
| location | above | below |
| location | on | off |
| location | to | from |
Teacher: Now, understand the problem? If you are still confused, see the following example:
Context word: fit.
Solution: Sentence 1: The trophy doesn't fit into the brown suitcase because _ is too large.
Answer1: trophy.
Sentence 2: The trophy doesn't fit into the brown suitcase because _ is too small.
Answer2: suitcase.
Reason: Here, the two objects are "trophy" and "suitcase". The trigger words are "large" and "small". Everything else (apart from the trigger words) are the same in the two sentences. The two sentences have different answers, which are the two objects ("trophy" and "suitcase").
Now, solve this instance: Context Word: undermining.
Student:
|
Sentence 1: The boss was undermining his career but could not affect his salary, as the _ was vulnerable to his manipulations.
Answer1: career.
Sentence 2: The boss was undermining his career but could not affect his salary, as the _ was protected from his manipulations.
Answer2: salary.
|
task029_winogrande_full_object
|
NIv2
|
fs_opt
| 2
|
test
|
Teacher: In this task, based on the given context word, you are asked to create a pair of sentences each containing a blank (_) and their corresponding answer. The sentence pair should look similar, and should be about two related but different objects; for example "trophy" and "suitcase". Additionally, the two sentences must be different in terms of trigger words (e.g., "small" and "big") which express contrasting properties about the two objects. The answer must not be associated with the trigger word; instead, it should depend on the context present in twin sentences. Also, the answers should not be ambiguous. For each sentence, there should be an agreed upon answer to fill in the blank. Your generations should NOT contain potentially explicit, offensive, or adult content. Do not use animals and proper nouns (e.g., New York, Macbook, Jeff Bezos, McDonald's, ...) as your objects. Avoid repeating the same style or phrase in twin sentences. E.g., a contrasting sentence can always be created using simple negation i.e. by adding not, never, etc. Instead, try to increase diversity. Both twin sentences must contain at least 15 and at most 30 words. Twin sentences must have at least 70% overlapping words. You must utilize the given context word while writing the twin sentences. Each of the twin sentences must contain only one blank. Make sure that ObjectX and Y have the same number e.g. when ObjectX is singular, ObjectY must be singular, too. The two objects (ObjectX & ObjectY) should be used ONCE in each sentence. Here is a list of contrastive words that may be used as trigger words. You should create more such trigger words and use them in your twin sentences.
| Attribute | triggerword | contrastive triggerword |
| age | old | new |
| altitude | low | high |
| area | small | vast |
| brightness | dark | light |
| clarity | obscure | clear |
| cleanness | dirty | clean |
| complexity | simple | complex |
| cost | cheap | expensive |
| density | sparse | dense |
| depth | shallow | deep |
| distance | near | far |
| electric conductivity | low | high |
| flexibility | rigid | flexible |
| granularity | fine | coarse |
| hardness | soft | hard |
| length | short | long |
| magnitude | small | large |
| mass | small | large |
| odor | weak | strong |
| pressure | low | high |
| resistance | low | high |
| shape | round | sharp |
| shape | flat | spiky |
| size | small | large |
| sound | quiet | loud |
| sound pitch | low | high |
| speed | slow | fast |
| stability | unstable | stable |
| strength | weak | strong |
| temperature | low | high |
| texture | smooth | rough |
| thermal conductivity | low | high |
| thickness | thin | thick |
| volume | small | large |
| weight | light | heavy |
| width | narrow | wide |
| location | in | out |
| location | up | down |
| location | above | below |
| location | on | off |
| location | to | from |
Teacher: Now, understand the problem? If you are still confused, see the following example:
Context word: fit.
Solution: Sentence 1: The trophy doesn't fit into the brown suitcase because _ is too large.
Answer1: trophy.
Sentence 2: The trophy doesn't fit into the brown suitcase because _ is too small.
Answer2: suitcase.
Reason: Here, the two objects are "trophy" and "suitcase". The trigger words are "large" and "small". Everything else (apart from the trigger words) are the same in the two sentences. The two sentences have different answers, which are the two objects ("trophy" and "suitcase").
Now, solve this instance: Context Word: Clean.
Student:
|
Sentence 1: Jane wanted to clean the hall with the vacuum cleaner attached with a cable but the _ is too short.
Answer1: cable.
Sentence 2: Jane wanted to clean the hall with the vacuum cleaner attached with a cable but the _ is too wide.
Answer2: hall.
|
task029_winogrande_full_object
|
NIv2
|
fs_opt
| 2
|
validation
|
Given the task definition and input, reply with output. You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Galician.
7枚の鏡が設置され望遠鏡が完成するのは 2020年代の中頃になるでしょう
|
E o telescopio enteiro estará rematado a mediados da próxima década, cos sete espellos.
|
task1095_ted_translation_ja_gl
|
NIv2
|
zs_opt
| 5
|
train
|
You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Galician.
[Q]: ドアの下に口を置くと質問をするという意味になります
[A]: Unha boca dentro dunha porta: preguntar
[Q]: もはや今までに見た事もないような核戦争が起こらない限りこの状況は止まらないでしょう
[A]: Non hai nada, agás unha guerra nuclear de grandes proporcións nunca vista, que poida deter este crecemento.
[Q]: 子供が生き残ることこそが人口の増加を止める唯一の方法なのです
[A]:
|
Só mediante a supervivencia infantil poderemos parar o crecemento da poboación.
|
task1095_ted_translation_ja_gl
|
NIv2
|
fs_opt
| 5
|
train
|
You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Galician.
Ex Input:
スピルバーグの映画では共謀した恐竜が人々を襲い始めます
Ex Output:
Claro, iso é o que acontece na película de Steven Spielberg. Dinosauros que conspiran e perseguen xente.
Ex Input:
これが現在の様子ですしかしこれが1950年代の様子です同じ場所で同じ船で同じ港の同じボードです
Ex Output:
Ben, agora iso é así, pero na década de 1950 xa era así: o mesmo barco no mesmo lugar, no mesmo panel do mesmo peirao.
Ex Input:
希望を持つ理由がちゃんとありますから
Ex Output:
|
Penso que hai motivos para a esperanza.
|
task1095_ted_translation_ja_gl
|
NIv2
|
fs_opt
| 1
|
train
|
You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Galician.
小さな７歳のピカソの夢は粉々に砕かれました
Os meus soños do pequeno Picasso de sete anos esmagados.
これを見ると70億人いると分かります「エア層」や「物干し層」の人「電球層」や「焚き火層」の人
Mirade isto, vedes os sete mil millóns de persoas aí enriba: a xente do ar, xente do lavado, a xente das bombillas, e a xente do lume.
貧乏だとしか聞いてなかったのでそれ以外のことと彼らを結びつけるのが
|
Todo o que escoitara deles era o pobres que eran, así que érame imposible miralos
|
task1095_ted_translation_ja_gl
|
NIv2
|
fs_opt
| 0
|
train
|
Given the task definition, example input & output, solve the new input case.
You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Galician.
Example: 処方箋を支払う為の保険は ？
Output: Terán seguro para pagar a receita?
The Japanese sentence is correctly translated into Galician, because the meaning is preserved.
New input case for you: この細胞片から細胞を育てようとしたのです
Output:
|
Quixemos cultivar células obtidas deses anacos de tecido.
|
task1095_ted_translation_ja_gl
|
NIv2
|
fs_opt
| 1
|
train
|
You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Galician.
[Q]: 毛細血管の小さな房
[A]: Observade esta pequena mata de capilares.
[Q]: 小さな７歳のピカソの夢は粉々に砕かれました
[A]: Os meus soños do pequeno Picasso de sete anos esmagados.
[Q]: 人生に「イエス」と言うのです
[A]:
|
Si á vida.
|
task1095_ted_translation_ja_gl
|
NIv2
|
fs_opt
| 5
|
train
|
You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Galician.
Q: 我々の工場機器の資本コストは非常に低く
A:
|
Temos costes capitais moi baixos no noso equipo de planta.
|
task1095_ted_translation_ja_gl
|
NIv2
|
zs_opt
| 4
|
train
|
You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Galician.
Input: Consider Input: だから私たちは一人残らず後世の子どもたちにとっての祖父母になるというわけです
Output: Así que esencialmente, todos nos convertemos en avós para as xeracións de nenos que veñen tras de nós.
Input: Consider Input: 上についているレーザーセンサを使っています
Output: Funciona cun sensor láser montado na parte de arriba de Rezero.
Input: Consider Input: 息子は赤私は緑
|
Output: O meu fillo está a deixar tinta vermella, eu estou a deixar tinta verde.
|
task1095_ted_translation_ja_gl
|
NIv2
|
fs_opt
| 2
|
train
|
Q: You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Galician.
（ 笑 ） 屋根を覆うとある女性がジョークを言いました「神様が見つけてくれるわ」
A:
|
(Risas) Cando os tellados estaban cubertos, unha muller dixo de broma: "Agora Deus pode verme."
|
task1095_ted_translation_ja_gl
|
NIv2
|
zs_opt
| 7
|
test
|
You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Galician.
Example: 処方箋を支払う為の保険は ？
Example solution: Terán seguro para pagar a receita?
Example explanation: The Japanese sentence is correctly translated into Galician, because the meaning is preserved.
Problem: このグラフには、 4種類の要素と教え方の質との関連性が表示されています。
|
Solution: Este gráfico amosa catro factores e indica en que medida inflúen na calidade do ensino.
|
task1095_ted_translation_ja_gl
|
NIv2
|
fs_opt
| 5
|
validation
|
You will be given a definition of a task first, then some input of the task.
In this task, you are given a tuple, comprising Head and Tail, separated with <sep>. The Head and the Tail events are short phrases possibly involving participants. The names of specific people have been replaced by generic words (e.g., PersonX, PersonY, PersonZ). PersonX is always the subject of the event. You have to determine whether, as a result of the Head, PersonY or others will want what is mentioned in the Tail or not. In this task, wanting is a postcondition desire on the part of PersonY and others, respectively. For example, as a result of PersonX giving PersonY gifts, PersonY may want to open the gift. Classify your answers into "Yes" and "No". The phrase may also contain "___", a placeholder that can be an object, a person, and/or an action.
Head: PersonX makes PersonY comment<sep>Tail: to explain
Output:
|
Yes
|
task1198_atomic_classification_owant
|
NIv2
|
zs_opt
| 1
|
train
|
In this task, you are given a tuple, comprising Head and Tail, separated with <sep>. The Head and the Tail events are short phrases possibly involving participants. The names of specific people have been replaced by generic words (e.g., PersonX, PersonY, PersonZ). PersonX is always the subject of the event. You have to determine whether, as a result of the Head, PersonY or others will want what is mentioned in the Tail or not. In this task, wanting is a postcondition desire on the part of PersonY and others, respectively. For example, as a result of PersonX giving PersonY gifts, PersonY may want to open the gift. Classify your answers into "Yes" and "No". The phrase may also contain "___", a placeholder that can be an object, a person, and/or an action.
Ex Input:
Head: PersonX agrees to the challenge<sep>Tail: be offered a challenge
Ex Output:
No
Ex Input:
Head: PersonX mentions in PersonY chapter<sep>Tail: publish the piece
Ex Output:
Yes
Ex Input:
Head: PersonX accepts the offer<sep>Tail: provide a service
Ex Output:
|
No
|
task1198_atomic_classification_owant
|
NIv2
|
fs_opt
| 1
|
train
|
Detailed Instructions: In this task, you are given a tuple, comprising Head and Tail, separated with <sep>. The Head and the Tail events are short phrases possibly involving participants. The names of specific people have been replaced by generic words (e.g., PersonX, PersonY, PersonZ). PersonX is always the subject of the event. You have to determine whether, as a result of the Head, PersonY or others will want what is mentioned in the Tail or not. In this task, wanting is a postcondition desire on the part of PersonY and others, respectively. For example, as a result of PersonX giving PersonY gifts, PersonY may want to open the gift. Classify your answers into "Yes" and "No". The phrase may also contain "___", a placeholder that can be an object, a person, and/or an action.
Q: Head: PersonX cuts PersonY's ___ according<sep>Tail: to have his thing cutted
A:
|
Yes
|
task1198_atomic_classification_owant
|
NIv2
|
zs_opt
| 9
|
train
|
In this task, you are given a tuple, comprising Head and Tail, separated with <sep>. The Head and the Tail events are short phrases possibly involving participants. The names of specific people have been replaced by generic words (e.g., PersonX, PersonY, PersonZ). PersonX is always the subject of the event. You have to determine whether, as a result of the Head, PersonY or others will want what is mentioned in the Tail or not. In this task, wanting is a postcondition desire on the part of PersonY and others, respectively. For example, as a result of PersonX giving PersonY gifts, PersonY may want to open the gift. Classify your answers into "Yes" and "No". The phrase may also contain "___", a placeholder that can be an object, a person, and/or an action.
One example: Head: PersonX holds PersonY's head<sep>Tail: to be messaged
Solution is here: Yes
Explanation: This is a good example. As a result of the Head, PersonY will want to be messaged.
Now, solve this: Head: PersonX becomes flat<sep>Tail: sneaky
Solution:
|
No
|
task1198_atomic_classification_owant
|
NIv2
|
fs_opt
| 6
|
train
|
In this task, you are given a tuple, comprising Head and Tail, separated with <sep>. The Head and the Tail events are short phrases possibly involving participants. The names of specific people have been replaced by generic words (e.g., PersonX, PersonY, PersonZ). PersonX is always the subject of the event. You have to determine whether, as a result of the Head, PersonY or others will want what is mentioned in the Tail or not. In this task, wanting is a postcondition desire on the part of PersonY and others, respectively. For example, as a result of PersonX giving PersonY gifts, PersonY may want to open the gift. Classify your answers into "Yes" and "No". The phrase may also contain "___", a placeholder that can be an object, a person, and/or an action.
[Q]: Head: PersonX holds PersonY tighter<sep>Tail: theft
[A]: Yes
[Q]: Head: PersonX is a professional photographer<sep>Tail: to receive great service from PersonX
[A]: Yes
[Q]: Head: PersonX eats crow<sep>Tail: to apologize to PersonX
[A]:
|
Yes
|
task1198_atomic_classification_owant
|
NIv2
|
fs_opt
| 5
|
train
|
In this task, you are given a tuple, comprising Head and Tail, separated with <sep>. The Head and the Tail events are short phrases possibly involving participants. The names of specific people have been replaced by generic words (e.g., PersonX, PersonY, PersonZ). PersonX is always the subject of the event. You have to determine whether, as a result of the Head, PersonY or others will want what is mentioned in the Tail or not. In this task, wanting is a postcondition desire on the part of PersonY and others, respectively. For example, as a result of PersonX giving PersonY gifts, PersonY may want to open the gift. Classify your answers into "Yes" and "No". The phrase may also contain "___", a placeholder that can be an object, a person, and/or an action.
Head: PersonX becomes PersonY's wife<sep>Tail: Person y movies in with person x.
|
No
|
task1198_atomic_classification_owant
|
NIv2
|
zs_opt
| 0
|
train
|
Detailed Instructions: In this task, you are given a tuple, comprising Head and Tail, separated with <sep>. The Head and the Tail events are short phrases possibly involving participants. The names of specific people have been replaced by generic words (e.g., PersonX, PersonY, PersonZ). PersonX is always the subject of the event. You have to determine whether, as a result of the Head, PersonY or others will want what is mentioned in the Tail or not. In this task, wanting is a postcondition desire on the part of PersonY and others, respectively. For example, as a result of PersonX giving PersonY gifts, PersonY may want to open the gift. Classify your answers into "Yes" and "No". The phrase may also contain "___", a placeholder that can be an object, a person, and/or an action.
Problem:Head: PersonX affects PersonY's interests<sep>Tail: steals a job
Solution:
|
No
|
task1198_atomic_classification_owant
|
NIv2
|
zs_opt
| 8
|
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.
In this task, you are given a tuple, comprising Head and Tail, separated with <sep>. The Head and the Tail events are short phrases possibly involving participants. The names of specific people have been replaced by generic words (e.g., PersonX, PersonY, PersonZ). PersonX is always the subject of the event. You have to determine whether, as a result of the Head, PersonY or others will want what is mentioned in the Tail or not. In this task, wanting is a postcondition desire on the part of PersonY and others, respectively. For example, as a result of PersonX giving PersonY gifts, PersonY may want to open the gift. Classify your answers into "Yes" and "No". The phrase may also contain "___", a placeholder that can be an object, a person, and/or an action.
Head: PersonX holds PersonY's head<sep>Tail: to be messaged
Solution: Yes
Why? This is a good example. As a result of the Head, PersonY will want to be messaged.
New input: Head: PersonX asks PersonY's teacher<sep>Tail: show homework
Solution:
|
Yes
|
task1198_atomic_classification_owant
|
NIv2
|
fs_opt
| 0
|
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.
In this task, you are given a tuple, comprising Head and Tail, separated with <sep>. The Head and the Tail events are short phrases possibly involving participants. The names of specific people have been replaced by generic words (e.g., PersonX, PersonY, PersonZ). PersonX is always the subject of the event. You have to determine whether, as a result of the Head, PersonY or others will want what is mentioned in the Tail or not. In this task, wanting is a postcondition desire on the part of PersonY and others, respectively. For example, as a result of PersonX giving PersonY gifts, PersonY may want to open the gift. Classify your answers into "Yes" and "No". The phrase may also contain "___", a placeholder that can be an object, a person, and/or an action.
Head: PersonX holds PersonY's head<sep>Tail: to be messaged
Solution: Yes
Why? This is a good example. As a result of the Head, PersonY will want to be messaged.
New input: Head: PersonX checks every ___<sep>Tail: none
Solution:
|
Yes
|
task1198_atomic_classification_owant
|
NIv2
|
fs_opt
| 0
|
test
|
Given the task definition, example input & output, solve the new input case.
In this task, you are given a tuple, comprising Head and Tail, separated with <sep>. The Head and the Tail events are short phrases possibly involving participants. The names of specific people have been replaced by generic words (e.g., PersonX, PersonY, PersonZ). PersonX is always the subject of the event. You have to determine whether, as a result of the Head, PersonY or others will want what is mentioned in the Tail or not. In this task, wanting is a postcondition desire on the part of PersonY and others, respectively. For example, as a result of PersonX giving PersonY gifts, PersonY may want to open the gift. Classify your answers into "Yes" and "No". The phrase may also contain "___", a placeholder that can be an object, a person, and/or an action.
Example: Head: PersonX holds PersonY's head<sep>Tail: to be messaged
Output: Yes
This is a good example. As a result of the Head, PersonY will want to be messaged.
New input case for you: Head: PersonX catches PersonY's eyes<sep>Tail: to avoid PersonX
Output:
|
Yes
|
task1198_atomic_classification_owant
|
NIv2
|
fs_opt
| 1
|
validation
|
You will be given a definition of a task first, then some input of the task.
Given a sentence in Japanese, provide an equivalent paraphrased translation in French that retains the same meaning both through the translation and the paraphrase.
特殊な感覚鎖繊維は筋肉に含まれる核器官です。
Output:
|
Une fibre de chaîne sensorielle spécialisée est un organe nucléaire contenu dans un muscle.
|
task815_pawsx_japanese_french_translation
|
NIv2
|
zs_opt
| 1
|
train
|
Given a sentence in Japanese, provide an equivalent paraphrased translation in French that retains the same meaning both through the translation and the paraphrase.
ドラマティックスピーキングおよびパブリックアート部門は、もともとT. Earl Pardoeが率いていました。
|
Le département des arts dramatiques et publics était à l'origine dirigé par T. Earl Pardoe.
|
task815_pawsx_japanese_french_translation
|
NIv2
|
zs_opt
| 0
|
train
|
Q: Given a sentence in Japanese, provide an equivalent paraphrased translation in French that retains the same meaning both through the translation and the paraphrase.
ニューヨークでレナードとグリフィスの間の会議の後、グリフィスはロサンゼルスに飛んで、エピソードを撮影しました。
A:
|
Après des conférences entre Leonard et Griffith à New York, Griffith s'est envolé pour Los Angeles et a filmé l'épisode.
|
task815_pawsx_japanese_french_translation
|
NIv2
|
zs_opt
| 7
|
train
|
You will be given a definition of a task first, then some input of the task.
Given a sentence in Japanese, provide an equivalent paraphrased translation in French that retains the same meaning both through the translation and the paraphrase.
1956年の夏に、マイクバーネットはシリーズの同じ年の終わりまでフランクラブジョイの役割を引き継ぎました。
Output:
|
À l'été 1956, Mike Barnett a repris le rôle de Frank Lovejoy jusqu'à la fin de la série la même année.
|
task815_pawsx_japanese_french_translation
|
NIv2
|
zs_opt
| 1
|
train
|
Given a sentence in Japanese, provide an equivalent paraphrased translation in French that retains the same meaning both through the translation and the paraphrase.
--------
Question: 彼らの関係の間に、ペアはロサンゼルスに住んでいました、シーモアは彼女の仕事のためにロンドンとロサンゼルスでもっと時間を費やしました。
Answer: Tout au long de sa relation, le couple a vécu à Los Angeles, bien que Seymour ait passé plus de temps à Londres et à Los Angeles pour leur travail.
Question: これはイギリスのロンドンで奉仕してきた地方自治体組織のさまざまな長のリストです。
Answer: Voici une liste des différents responsables des organisations gouvernementales locales qui ont servi Londres, en Angleterre.
Question: 独立したルイス学者であるKathryn Lindskoogは、Hooperの奨学金は信頼できないと彼は誤った発言をし、ルイスに鍛造された作品を起因させたと主張した。
Answer:
|
Kathryn Lindskoog, une universitaire indépendante de Lewis, a fait valoir que les recherches de Hooper n'étaient pas fiables et qu'il avait fait de fausses déclarations et attribué de faux travaux.
|
task815_pawsx_japanese_french_translation
|
NIv2
|
fs_opt
| 7
|
train
|
Detailed Instructions: Given a sentence in Japanese, provide an equivalent paraphrased translation in French that retains the same meaning both through the translation and the paraphrase.
Problem:Andrea Bocelliは彼女のリハーサルパフォーマンスを「とてもいい」と言い、David Fosterは彼女の声を素晴らしいと言っています。
Solution:
|
Andrea Andrea Bocelli a qualifié son exemple de performance de «très sympa» et David Foster a qualifié sa voix de spectaculaire.
|
task815_pawsx_japanese_french_translation
|
NIv2
|
zs_opt
| 8
|
train
|
Given the task definition, example input & output, solve the new input case.
Given a sentence in Japanese, provide an equivalent paraphrased translation in French that retains the same meaning both through the translation and the paraphrase.
Example: 1975 - 76年のNBAシーズンは、全米バスケットボール協会の30番目のシーズンでした。
Output: La saison 1975-1976 de la National Basketball Association était la 30e saison de la NBA.
This is a correct and accurate translation from Japanese to French because the translated paraphrase retains the main message that between the years 1975-1976, the 30th NBA season occurred.
New input case for you: Mineral Hillsの村とStambaughの町は、2000年7月1日からIron Riverの町と統合されました。
Output:
|
À compter du 1er juillet 2000, le village de Mineral Hills et la ville de Stambaugh ont été regroupés avec la ville d’Iron River.
|
task815_pawsx_japanese_french_translation
|
NIv2
|
fs_opt
| 1
|
train
|
Q: Given a sentence in Japanese, provide an equivalent paraphrased translation in French that retains the same meaning both through the translation and the paraphrase.
Seb Janiakは、フランス出身の写真家であり、ポーランド出身のビデオディレクターです。
A:
|
Seb Janiak est le photographe et réalisateur français d'origine polonaise.
|
task815_pawsx_japanese_french_translation
|
NIv2
|
zs_opt
| 7
|
train
|
Given a sentence in Japanese, provide an equivalent paraphrased translation in French that retains the same meaning both through the translation and the paraphrase.
One example is below.
Q: 1975 - 76年のNBAシーズンは、全米バスケットボール協会の30番目のシーズンでした。
A: La saison 1975-1976 de la National Basketball Association était la 30e saison de la NBA.
Rationale: This is a correct and accurate translation from Japanese to French because the translated paraphrase retains the main message that between the years 1975-1976, the 30th NBA season occurred.
Q: 1406年に彼はDivascuridesのJuliana Aniciaコーデックス、リバウンドと目次を加えました、そして、ビザンチンギリシャのMinuskel scholiaは広範囲に回復しました。
A:
|
En 1406, il fit ajouter le Juliana Anicia Codex de Dioscurides, un rebond, une table des matières et une minuscule scholia restaurée en grec byzantin extensif.
|
task815_pawsx_japanese_french_translation
|
NIv2
|
fs_opt
| 9
|
test
|
Instructions: Given a sentence in Japanese, provide an equivalent paraphrased translation in French that retains the same meaning both through the translation and the paraphrase.
Input: Hector Crawfordは、3DBマネージャで管理者のCurteis Crawfordの兄弟であり、またDorothy Crawfordの兄弟でした。
Output:
|
Hector Crawford était le frère du directeur et administrateur de 3DB, Curteis Crawford, ainsi que le frère de Dorothy Crawford.
|
task815_pawsx_japanese_french_translation
|
NIv2
|
zs_opt
| 3
|
validation
|
In this task, you are given an abstract of article. Your task is to generate title for this article. Preferred titles are under thirty words.
Input: Consider Input: Patients with asthma, a major public health problem, are at high risk for serious disease from influenza virus infection, but the pathogenic mechanisms by which influenza A causes airway disease and asthma are not fully known. We show here in a mouse model that influenza infection acutely induced airway hyper-reactivity (AHR), a cardinal feature of asthma, independently of T helper type 2 (TH2) cells and adaptive immunity. Instead, influenza infection induced AHR through a previously unknown pathway that required the interleukin 13 (IL-13)–IL-33 axis and cells of the non-T cell, non-B cell innate lymphoid type called 'natural helper cells'. Infection with influenza A virus, which activates the NLRP3 inflammasome, resulted in much more production of IL-33 by alveolar macrophages, which in turn activated natural helper cells producing substantial IL-13.
Output: Innate lymphoid cells mediate influenza-induced airway hyper-reactivity independently of adaptive immunity
Input: Consider Input: OBJECTIVE To assess whether sex differences exist in the angiographic severity, management and outcomes of acute coronary syndromes (ACS).
METHODS The study comprised 7638 women and 19 117 men with ACS who underwent coronary angiography and were included in GRACE (Global Registry of Acute Coronary Events) from 1999-2006. Normal vessels/mild disease was defined as <50% stenosis in all epicardial vessels; advanced disease was defined as >or=one vessel with >or=50% stenosis.
RESULTS Women were older than men and had higher rates of cardiovascular risk factors. Men and women presented equally with chest pain; however, jaw pain and nausea were more frequent among women. Women were more likely to have normal/mild disease (12% vs 6%, p<0.001) and less likely to have left-main and three-vessel disease (27% vs 32%, p<0.001) or undergo percutaneous coronary intervention (65% vs 68%, p<0.001). Women and men with normal and mild disease were treated less aggressively than those with advanced disease. Women with advanced disease had a higher risk of death (4% vs 3%, p<0.01). After adjustment for age and extent of disease, women were more likely to have adverse outcomes (death, myocardial infarction, stroke and rehospitalisation) at six months compared to men (odds ratio 1.24, 95% confidence interval 1.14 to 1.34); however, sex differences in mortality were no longer statistically significant.
CONCLUSIONS Women with ACS were more likely to have cardiovascular disease risk factors and atypical symptoms such as nausea compared with men, but were more likely to have normal/mild angiographic coronary artery disease. Further study regarding sex differences related to disease severity is warranted.
Output: Sex-related differences in the presentation, treatment and outcomes among patients with acute coronary syndromes: the Global Registry of Acute Coronary Events.
Input: Consider Input: The simple yet powerful technique of induced pluripotency may eventually supply a wide range of differentiated cells for cell therapy and drug development. However, making the appropriate cells via induced pluripotent stem cells (iPSCs) requires reprogramming of somatic cells and subsequent redifferentiation. Given how arduous and lengthy this process can be, we sought to determine whether it might be possible to convert somatic cells into lineage-specific stem/progenitor cells of another germ layer in one step, bypassing the intermediate pluripotent stage. Here we show that transient induction of the four reprogramming factors (Oct4, Sox2, Klf4, and c-Myc) can efficiently transdifferentiate fibroblasts into functional neural stem/progenitor cells (NPCs) with appropriate signaling inputs. Compared with induced neurons (or iN cells, which are directly converted from fibroblasts), transdifferentiated NPCs have the distinct advantage of being expandable in vitro and retaining the ability to give rise to multiple neuronal subtypes and glial cells. Our results provide a unique paradigm for iPSC-factor-based reprogramming by demonstrating that it can be readily modified to serve as a general platform for transdifferentiation.
|
Output: Direct reprogramming of mouse fibroblasts to neural progenitors.
|
task1586_scifact_title_generation
|
NIv2
|
fs_opt
| 2
|
train
|
Given the task definition and input, reply with output. In this task, you are given an abstract of article. Your task is to generate title for this article. Preferred titles are under thirty words.
Classical C2H2 zinc finger proteins are among the most abundant transcription factors found in eukaryotes, and the mechanisms through which they recognize their target genes have been extensively investigated. In general, a tandem array of three fingers separated by characteristic TGERP links is required for sequence-specific DNA recognition. Nevertheless, a significant number of zinc finger proteins do not contain a hallmark three-finger array of this type, raising the question of whether and how they contact DNA. We have examined the multi-finger protein ZNF217, which contains eight classical zinc fingers. ZNF217 is implicated as an oncogene and in repressing the E-cadherin gene. We show that two of its zinc fingers, 6 and 7, can mediate contacts with DNA. We examine its putative recognition site in the E-cadherin promoter and demonstrate that this is a suboptimal site. NMR analysis and mutagenesis is used to define the DNA binding surface of ZNF217, and we examine the specificity of the DNA binding activity using fluorescence anisotropy titrations. Finally, sequence analysis reveals that a variety of multi-finger proteins also contain two-finger units, and our data support the idea that these may constitute a distinct subclass of DNA recognition motif.
|
The multi-zinc finger protein ZNF217 contacts DNA through a two-finger domain.
|
task1586_scifact_title_generation
|
NIv2
|
zs_opt
| 5
|
train
|
In this task, you are given an abstract of article. Your task is to generate title for this article. Preferred titles are under thirty words.
Skeletal muscle overload induces the expression of angiogenic factors such as vascular endothelial growth factor (VEGF) and matrix metalloproteinase (MMP)-2, leading to new capillary growth. We found that the overload-induced increase in angiogenesis, as well as increases in VEGF, MMP-2 and MT1-MMP transcripts were abrogated in muscle VEGF KO mice, highlighting the critical role of myocyte-derived VEGF in controlling this process. The upstream mediators that contribute to overload-induced expression of VEGF have yet to be ascertained. We found that muscle overload increased angiotensinogen expression, a precursor of angiotensin (Ang) II, and that Ang II signaling played an important role in basal VEGF production in C2C12 cells. Furthermore, matrix-bound VEGF released from myoblasts induced the activation of endothelial cells, as evidenced by elevated endothelial cell phospho-p38 levels. We also found that exogenous Ang II elevates VEGF expression, as well as MMP-2 transcript levels in C2C12 myotubes. Interestingly, these responses also were observed in skeletal muscle endothelial cells in response to Ang II treatment, indicating that these cells also can respond directly to the stimulus. The involvement of Ang II in muscle overload-induced angiogenesis was assessed. We found that blockade of AT1R-dependent Ang II signaling using losartan did not attenuate capillary growth. Surprisingly, increased levels of VEGF protein were detected in overloaded muscle from losartan-treated rats. Similarly, we observed elevated VEGF production in cultured endothelial cells treated with losartan alone or in combination with Ang II. These studies conclusively establish the requirement for muscle derived VEGF in overload-induced angiogenesis and highlight a role for Ang II in basal VEGF production in skeletal muscle. However, while Ang II signaling is activated following overload and plays a role in muscle VEGF production, inhibition of this pathway is not sufficient to halt overload-induced angiogenesis, indicating that AT1-independent signals maintain VEGF production in losartan-treated muscle.
|
Angiotensin II Evokes Angiogenic Signals within Skeletal Muscle through Co-ordinated Effects on Skeletal Myocytes and Endothelial Cells
|
task1586_scifact_title_generation
|
NIv2
|
zs_opt
| 0
|
train
|
Q: In this task, you are given an abstract of article. Your task is to generate title for this article. Preferred titles are under thirty words.
IRGM, a human immunity-related GTPase, confers autophagic defence against intracellular pathogens by an unknown mechanism. Here, we report an unexpected mode of IRGM action. IRGM demonstrated differential affinity for the mitochondrial lipid cardiolipin, translocated to mitochondria, affected mitochondrial fission and induced autophagy. Mitochondrial fission was necessary for autophagic control of intracellular mycobacteria by IRGM. IRGM influenced mitochondrial membrane polarization and cell death. Overexpression of IRGMd, but not IRGMb splice isoforms, caused mitochondrial depolarization and autophagy-independent, but Bax/Bak-dependent, cell death. By acting on mitochondria, IRGM confers autophagic protection or cell death, explaining IRGM action both in defence against tuberculosis and in the damaging inflammation caused by Crohn's disease.
A:
|
Human IRGM Regulates Autophagy and Its Cell-Autonomous Immunity Functions Through Mitochondria
|
task1586_scifact_title_generation
|
NIv2
|
zs_opt
| 7
|
train
|
Instructions: In this task, you are given an abstract of article. Your task is to generate title for this article. Preferred titles are under thirty words.
Input: The multifunctional signaling protein p75 neurotrophin receptor (p75(NTR)) is a central regulator and major contributor to the highly invasive nature of malignant gliomas. Here, we show that neurotrophin-dependent regulated intramembrane proteolysis (RIP) of p75(NTR) is required for p75(NTR)-mediated glioma invasion, and identify a previously unnamed process for targeted glioma therapy. Expression of cleavage-resistant chimeras of p75(NTR) or treatment of animals bearing p75(NTR)-positive intracranial tumors with clinically applicable gamma-secretase inhibitors resulted in dramatically decreased glioma invasion and prolonged survival. Importantly, proteolytic processing of p75(NTR) was observed in p75(NTR)-positive patient tumor specimens and brain tumor initiating cells. This work highlights the importance of p75(NTR) as a therapeutic target, suggesting that gamma-secretase inhibitors may have direct clinical application for the treatment of malignant glioma.
Output:
|
Gamma-Secretase Represents a Therapeutic Target for the Treatment of Invasive Glioma Mediated by the p75 Neurotrophin Receptor
|
task1586_scifact_title_generation
|
NIv2
|
zs_opt
| 3
|
train
|
Teacher: In this task, you are given an abstract of article. Your task is to generate title for this article. Preferred titles are under thirty words.
Teacher: Now, understand the problem? If you are still confused, see the following example:
Alterations of the architecture of cerebral white matter in the developing human brain can affect cortical development and result in functional disabilities. A line scan diffusion-weighted magnetic resonance imaging (MRI) sequence with diffusion tensor analysis was applied to measure the apparent diffusion coefficient, to calculate relative anisotropy, and to delineate three-dimensional fiber architecture in cerebral white matter in preterm (n = 17) and full-term infants (n = 7). To assess effects of prematurity on cerebral white matter development, early gestation preterm infants (n = 10) were studied a second time at term. In the central white matter the mean apparent diffusion coefficient at 28 wk was high, 1.8 microm2/ms, and decreased toward term to 1.2 microm2/ms. In the posterior limb of the internal capsule, the mean apparent diffusion coefficients at both times were similar (1.2 versus 1.1 microm2/ms). Relative anisotropy was higher the closer birth was to term with greater absolute values in the internal capsule than in the central white matter. Preterm infants at term showed higher mean diffusion coefficients in the central white matter (1.4 +/- 0.24 versus 1.15 +/- 0.09 microm2/ms, p = 0.016) and lower relative anisotropy in both areas compared with full-term infants (white matter, 10.9 +/- 0.6 versus 22.9 +/- 3.0%, p = 0.001; internal capsule, 24.0 +/- 4.44 versus 33.1 +/- 0.6% p = 0.006). Nonmyelinated fibers in the corpus callosum were visible by diffusion tensor MRI as early as 28 wk; full-term and preterm infants at term showed marked differences in white matter fiber organization. The data indicate that quantitative assessment of water diffusion by diffusion tensor MRI provides insight into microstructural development in cerebral white matter in living infants.
Solution: Microstructural development of human newborn cerebral white matter assessed in vivo by diffusion tensor magnetic resonance imaging.
Reason: This title is appropriate for the given abstract because the focus of this abstract is cerebral white matter assesment.
Now, solve this instance: During ageing thymic function declines and is unable to meet the demand for peripheral T helper (Th) cell replenishment. Therefore, population maintenance of naive Th cells must be at least partly peripherally based. Such peripheral postthymic expansion of recent thymic emigrants (RTEs) during ageing consequently should lead to loss or dilution of T cell receptor excision circles (TRECs) from a subset of naive T cells. We have identified two subsets of naive Th cells in human adult peripheral blood characterized by a striking unequal content of TRECs, indicating different peripheral proliferative histories. TRECs are highly enriched in peripheral naive CD45RA+ Th cells coexpressing CD31 compared with peripheral naive CD45RA+ Th cells lacking CD31 expression, in which TRECs can hardly be detected. Furthermore we show that CD31−CD45RA+ Th cells account for increasing percentages of the naive peripheral Th cell pool during ageing but retain phenotypic and functional features of naive Th cells. As CD31 is lost upon T cell receptor (TCR) engagement in vitro, we hypothesize that TCR triggering is a prerequisite for homeostatically driven peripheral postthymic expansion of human naive RTEs. We describe here the identification of peripherally expanded naive Th cells in human adult blood characterized by the loss of CD31 expression and a highly reduced TREC content.
Student:
|
Two Subsets of Naive T Helper Cells with Distinct T Cell Receptor Excision Circle Content in Human Adult Peripheral Blood
|
task1586_scifact_title_generation
|
NIv2
|
fs_opt
| 2
|
train
|
In this task, you are given an abstract of article. Your task is to generate title for this article. Preferred titles are under thirty words.
Cilia are sensory organelles that protrude from cell surfaces to monitor the surrounding environment. In addition to its role as sensory receiver, the cilium also releases extracellular vesicles (EVs). The release of sub-micron sized EVs is a conserved form of intercellular communication used by all three kingdoms of life. These extracellular organelles play important roles in both short and long range signaling between donor and target cells and may coordinate systemic responses within an organism in normal and diseased states. EV shedding from ciliated cells and EV–cilia interactions are evolutionarily conserved phenomena, yet remarkably little is known about the relationship between the cilia and EVs and the fundamental biology of EVs. Studies in the model organisms Chlamydomonas and Caenorhabditis elegans have begun to shed light on ciliary EVs. Chlamydomonas EVs are shed from tips of flagella and are bioactive. Caenorhabditis elegans EVs are shed and released by ciliated sensory neurons in an intraflagellar transport-dependent manner. Caenorhabditis elegans EVs play a role in modulating animal-to-animal communication, and this EV bioactivity is dependent on EV cargo content. Some ciliary pathologies, or ciliopathies, are associated with abnormal EV shedding or with abnormal cilia–EV interactions. Until the 21st century, both cilia and EVs were ignored as vestigial or cellular junk. As research interest in these two organelles continues to gain momentum, we envision a new field of cell biology emerging. Here, we propose that the cilium is a dedicated organelle for EV biogenesis and EV reception. We will also discuss possible mechanisms by which EVs exert bioactivity and explain how what is learned in model organisms regarding EV biogenesis and function may provide insight to human ciliopathies.
|
Ciliary Extracellular Vesicles: Txt Msg Organelles
|
task1586_scifact_title_generation
|
NIv2
|
zs_opt
| 0
|
train
|
Given the task definition and input, reply with output. In this task, you are given an abstract of article. Your task is to generate title for this article. Preferred titles are under thirty words.
Despite its key role in determining the stability and intensity of malaria transmission, the infectiousness of human populations to mosquitoes has rarely been estimated. Field-based analyses of malaria transmission have frequently relied on the prevalence of asexual parasites or gametocytes as proxies for infectiousness. We now summarize empirical data on human infectiousness from Africa and Papua New Guinea. Over a wide range of transmission intensities there is little relationship between the infectiousness of human populations to vector mosquitoes and mosquito-to-human transmission intensity. We compare these data with the predictions of a stochastic simulation model of Plasmodium falciparum epidemiology. This model predicted little variation in the infectiousness of the human population for entomologic inoculation rates (EIRs) greater than approximately 10 infectious bites per year, demonstrating that the lack of relationship between the EIR and the infectious reservoir can be explained without invoking any effects of acquired transmission-blocking immunity. The near absence of field data from areas with an EIR < 10 per year precluded validation of the model predictions for low EIR values. These results suggest that interventions reducing mosquito-to-human transmission will have little or no effect on human infectiousness at the levels of transmission found in most rural areas of sub-Saharan Africa. Unless very large reductions in transmission can be achieved, measures to prevent mosquito-to-human transmission need to be complemented with interventions that reduce the density or infectiousness of blood stage parasites.
|
Infectiousness of malaria-endemic human populations to vectors.
|
task1586_scifact_title_generation
|
NIv2
|
zs_opt
| 5
|
train
|
Detailed Instructions: In this task, you are given an abstract of article. Your task is to generate title for this article. Preferred titles are under thirty words.
Problem:Young patients with an ischaemic stroke or transient ischaemic attack (TIA) often have no vascular risk factors. Hyperhomocysteinaemia is an established risk factor for stroke in elderly patients but it is uncertain whether it is also important for the prognosis of young ischaemic stroke and TIA patients. We examined the possible effect of the plasma homocysteine level on the risk of recurrent vascular events in patients between 18 and 45 years of age. The study population consisted of 161 consecutive patients with a recent cerebral infarction or TIA. Data on the primary event and the homocysteine level were collected retrospectively from hospital records. General practitioners and patients were contacted by telephone to record vascular events and the type of medication used during the follow–up period. Vascular events included cerebral infarction, TIA, pulmonary embolism, venous thrombosis, myocardial infarction and peripheral arterial disease. A Kaplan- Meier curve showed a dose effect relationship between event-free survival time and tertiles of the homocysteine level (Log rank statistic 5.91; p = 0.05). The Cox hazard ratio, after adjustment for homocysteine lowering treatment, was 1.7 (95 % CI, 1.1 to 2.8) for any vascular outcome event, 1.9 (95% CI, 1.1 to 3.0) for arterial outcome events and 1.8 (95 % CI, 1.1 to 2.9) for cerebral outcome events. In spite of our small number of outcome events we found a significant association at the 95% confidence level between homocysteine level and the risk of recurrent vascular events in young patients with an ischaemic stroke or TIA. The association is of the same magnitude as in elderly people.
Solution:
|
Plasma homocysteine is a risk factor for recurrent vascular events in young patients with an ischaemic stroke or TIA
|
task1586_scifact_title_generation
|
NIv2
|
zs_opt
| 8
|
test
|
You will be given a definition of a task first, then some input of the task.
In this task, you are given an abstract of article. Your task is to generate title for this article. Preferred titles are under thirty words.
3'-Ends of almost all eukaryotic mRNAs are generated by endonucleolytic cleavage and addition of a poly(A) tail. In mammalian cells, the reaction depends on the sequence AAUAAA upstream of the cleavage site, a degenerate GU-rich sequence element downstream of the cleavage site and stimulatory sequences upstream of AAUAAA. Six factors have been identified that carry out the two reactions. With a single exception, they have been purified to homogeneity and cDNAs for 11 subunits have been cloned. Some of the cooperative RNA-protein and protein-protein interactions within the processing complex have been analyzed, but many details, including the identity of the endonuclease, remain unknown. Several examples of regulated polyadenylation are being analyzed at the molecular level. In the yeast Saccharomyces cerevisiae, sequences directing cleavage and polyadenylation are more degenerate than in metazoans, and a downstream element has not been identified. The list of processing factors may be complete now with approximately a dozen polypeptides, but their functions in the reaction are largely unknown. 3'-Processing is known to be coupled to transcription. This connection is thought to involve interactions of processing factors with the mRNA cap as well as with RNA polymerase II.
Output:
|
3'-End processing of pre-mRNA in eukaryotes.
|
task1586_scifact_title_generation
|
NIv2
|
zs_opt
| 1
|
validation
|
In this task, you are given a review of a movie and a boolean question whether this review 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: Review: Not really spoilers in my opinion, but I wanted to cover myself, nevertheless. As the executive producer, Morgan Freeman wants the audience to ignore the numerous absurdities of his character in 10 Items Or Less, a movie with an intentional indie-feel, and just be absorbed in the mentor/be-all-that-you-can-be theme. He plays a alternate universe, semi-washed up version of the real Morgan Freeman, who is chauffeured in an old Econovan by a kid all the way into Carson, CA from Brentwood to research his next movie role. Why Carson, is a mystery to So. Cal residents. He could have saved the trip and gone anywhere in the San Fernando Valley and found the same elements. Paz Vega is pretty to watch, a cross between Salma Hayek and Penelope Cruz, playing a disgruntled grocery checker at a large but slow local market that apparently is the ultimate source for Moragn Freeman's research. His character is only known as "Him" to allude to how actors are regarded when encountered in real life by average people-"Psst, that's 'him,' etc. Unfortunately, I was too distracted that Him had all kinds of worldly wisdom and advice but had no reliable return back to his home in Brentwood, carried no cash or debit card, or had the wisdom to keep a cell phone with him. If one has such a high opinion of their self that they believe they possess an answer to everything like Him does, then I gotta see cash and a Blackberry which displays intelligence and good survival instincts to preserve that big ego which Him definitely has. Nothing really happens in this movie. I don't believe that either of the main character's were substantially changed by their encounter with each other. It flirts with the idea of adultery, but then that thought fizzles. This to me was similar to Steve Martin's Shopgirl, without the sexual affair. It was self-indulgent for Freeman and unconvincing to the audience. Question: is it a negative review?
A: yes
****
Q: Review: When you go at an open air cinema under the Greek summer night you usually don't care what the movie is! Edison started really good with some good effort from the singers-who-want-to-be actors and a once again great Morgan Freeman but... (In a movie there is usually a good start to catch audience,done, a bit boring yet story filling middle of the movie that is more about characters and less about action ,done, and the third part is something really good so that you can remember the movie...) when you see 30 elite police officers (packed with weapons that can demolish a building) shoot at a guy behind a car, fail to hit him even once while he kills all (but 3) and then the guy takes out a flame thrower (to kill the rest 3) ,you realise that the Greek summer sky filled with stars is way too good to be distracted by a movie like this! Question: is it a negative review?
A: yes
****
Q: Review: The acting, other reviews notwithstanding, was remarkably well-done. Brad Pitt handles the role of an annoying, obnoxious Austrian climber quite well. Other acting is fine. The story could have been riveting, but somehow, it misses - one never really understands or cares for the characters shown, and so the story, which could have been quite dramatic, fails to draw in this audience.Beautiful scenery and cinematography, a remarkably dramatic true story, important events that shaped the world that we live in - but I could not, try as I might, involve myself in this story. As an unabashed Brad Pitt fan (I consider him one of the top 5 actors of his generation), I expected to *love* this flick - and yet, it left me cold.It could be a failing within myself, but I tend to point toward the creative end of this movie - direction, scriptwriting, production, editing - somehow, they lost me. It's a shame, because it could have been wonderful.Good acting, dramatic story, beautifully shot - it should have been magnificent. It wasn't. Probably worth watching, just to make your own mind up on it - but don't expect too much, and perhaps you won't be as disappointed as I was. Mostly, it bored me. Question: is it a negative review?
A:
|
yes
****
|
task285_imdb_answer_generation
|
NIv2
|
fs_opt
| 4
|
train
|
In this task, you are given a review of a movie and a boolean question whether this review 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: Review: For a movie that gets no respect there sure are a lot of memorable quotes listed for this gem. Imagine a movie where Joe Piscopo is actually funny! Maureen Stapleton is a scene stealer. The Moroni character is an absolute scream. Watch for Alan The Skipper Hale jr. as a police Sgt. Question: is it a positive review?
Example solution: yes
Example explanation: There is an expression of appreciation in this movie review, hence we can say it's positive. So generated label is 'yes'.
Problem: Review: I love a good sappy love story (and I'm a guy) but when I rented "Love Story" I prayed for the end to come as quickly and painlessly as possible and just the opposite for Ali McGraw's character.Ali McGraw as Jenny alienated and irritated the heck out of me within the first 15 minutes. When we learn that she has been diagnosed with a life threatening illness I couldn't help but wonder if her death would be such a terrible loss for poor Oliver or if anyone watching this film would even care. If she didn't die her grating personality would probably have pushed Oliver over the edge and eventually landed them in divorce court.People love this movie but it's one of the worst of the 70's. Question: is it a positive review?
|
Solution: no
|
task285_imdb_answer_generation
|
NIv2
|
fs_opt
| 5
|
train
|
You will be given a definition of a task first, then some input of the task.
In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no".
Review: ...And that's why hard to rate. From the adult point of view (hmm, student point of view:)). i must say i fell nearly asleep here. Sure, there is some laughing scene (all the credit takes here Eddie), but that can't save the disney type of script and whole movie, that's why2 out of 10 Question: is it a positive review?
Output:
|
no
|
task285_imdb_answer_generation
|
NIv2
|
zs_opt
| 1
|
train
|
Teacher:In this task, you are given a review of a movie and a boolean question whether this review 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: Review: Now, many would think to stay away from this movie just because of the title. If you do not have the stomach for gory movies, then what are you doing reading this review? Anyhow, I borrowed the video from a friend of mine and fell in love with this movie immediately. This movie is chock full of wonderful gore, plus the usual other ingredients that make up a b-movie add up to one hell of a viewing experience! If you're a lover of good quality experiences, then by all means, watch this great flick! Question: is it a negative review?
Student:
|
no
|
task285_imdb_answer_generation
|
NIv2
|
zs_opt
| 6
|
train
|
You will be given a definition of a task first, then some input of the task.
In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no".
Review: Just another film that exploits gratuitous frontal male nudity; awful acting, plus, the lovemaking scenes are the most un-sexy I've ever seen (and this is not about me not linking the idea of two young men making love, since I'm gay).Again, as in Mil nubes de paz, Julian Hernandez directed an incredibly pretentious film with a story that makes enough argument for a short film of about five minutes but manages to make a 2 hour film with it... And this time, there isn't even the issue of racism and commodification in the Mexican gay community to talk about! God gracious have mercy on us! Question: is it a negative review?
Output:
|
yes
|
task285_imdb_answer_generation
|
NIv2
|
zs_opt
| 1
|
train
|
In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no".
Ex Input:
Review: Sure, he became rapidly uneven after this film, but from "Knife In the Water" up till "The Tenant", Roman Polanski could always be counted on to deliver something fascinating and unique. Despite many running themes (alienation, paranoia), no two of his films are really alike. The story of this is somewhat similar to his own "Repulsion" from ten years earlier, but the tone is completely different. "The Tenant" manages to balance darker than dark absurdity (I'm a bit hesitant on calling it humor, even though the protagonists bizarre behavior and dialog was occasionally funny) with some truly suspenseful paranoia. Polanski was always a master at building unease, and moments in this film are almost unbearably creepy. The overall weirdness of the film is also a plus.In addition to Polanski's exquisite as usual direction, the rest of the cast and crew offer great contributions. Polanski the actor is often overshadowed by Polanski the director, but his performance here truly captures his characters awkwardness and sense of being an outcast. The themes of social discrimination make this film more than just strangeness for the sake of being strange. The rest of the cast offers strong performances also, especially Isabelle Adjani's sympathetic turn, and Melyvn Douglas and Shelley Winters' appropriately annoying ones. "The Tenant" is often underrated because of how ready people are to heap praise on both "Repulsion" and "Rosemary's Baby", but its just as brilliant as either of those classics. (9/10) Question: is it a negative review?
Ex Output:
no
Ex Input:
Review: It looks to me as if the creators of "The Class Of Nuke 'Em High" wanted it to become a "cult" film, but it ends up as any old high school B-movie, only tackier. The satire feels totally overshadowed by the extremely steretyped characters. It's very un-funny, even for a turkey. Question: is it a positive review?
Ex Output:
no
Ex Input:
Review: This movie is just not worth your time. Its reliance upon New-Age mysticism serves as its only semi-interesting distraction. The plot is one that has been re-cycled countless times.I was only prompted to even spend the time to put in a comment when I noted that some have tried to prop-up the reputation of this drivel. Their motivation & objectivity is dubious, since they encourage you not to look at the movies faults, but at its well intentioned message of New Age consciousness.So would it be alright for some twenty to thirty Evangelical Christians, or Islamic Fundamentalists to pour in positive ratings about movies/television that support their views? In spite of the poor qualities of production, or the lack of truth in any of its supposed historic basis? I hope not.I am sure the followers will come right behind me to say flowery things about this movie, in spite of the truth. Question: is it a positive review?
Ex Output:
|
no
|
task285_imdb_answer_generation
|
NIv2
|
fs_opt
| 1
|
train
|
Detailed Instructions: In this task, you are given a review of a movie and a boolean question whether this review 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: Review: A killer, wearing a plastic white mask and black overcoat, is killing the friends of Hollywood producer Shawn Banning(Danny Wolske)who inherited his position when someone sliced open his former employer from crotch to chest. Perhaps the psychopath is newly hired Maddy(Dabbie Rochon), an attractive, raven haired beauty with a troubled family past, plagued with nightmares. Shawn and his friends play a practical joke on Maddy, concerning a supposed Murder Club they started where each member randomly selected a victim to kill. When Maddy accidentally murders a woman in a parking garage because of a dent put into her car by this person, she finds that Shawn's pals were jerking her chain. But, Shawn and his comrades are concerned about Maddy's admittance towards committing the murder and contemplate turning her into the proper authorities. Deciding to wait on a definite decision, each member fall prey to the white-masked psycho with Maddy a suspect considering the fact that she already has killed before. Or, is someone else behind these murders? Low budget slasher, executive produced by Charles Band, with gore murders that fail to convince. Plenty of tits on display and Allen Nabors goofy character Chris might entertain those with low expectations. The murders include a stomach being opened with intestines showing, a neck sliced, an electrical cord thrown into a pool frying a female victim who had all day to escape, an ax buried into the back of a male victim, and, to top it all, a couple are strangled by a rope during their sexual climax(..for added effect, the killer uses the breaker bar of a socket wrench as extra leverage to twist the rope as tight as possible snapping their necks). There are enough plot holes to drive a truck through, such as why Maddy has nightmares of murders she didn't commit, how she could murder someone so violently(..with blood all over her)winding up waking in her bed without leaving something at the scene of the crime that would easily implicate her, and how Shawn could go so long, allowing her to continue working at the company despite what she told regarding the murder she committed, and a continual desire to join the supposed club that doesn't exist.What bothered me the most was the film's desire for having us somehow sympathizing with this female protagonist who wanted to join a club after killing someone, later proclaiming it to be an accident. The film builds Maddy as the potential psycho throughout because of her past. Her family disowned her for an abortion. She has black-outs and always appropriately winds up at the scenes of crimes after the fact. In a lot of slashers, the one who seems the most likely killer is often the red herring, but this film goes out of it's way to point the finger at Maddy. When the twist occurs, we're left rooting for Maddy, yet we know she's not right in the head. It's a tough sell caring for this chick. She does look great in a man's Army shirt, though. And, Rochon isn't afraid to let her puppies breathe, either. Low budget horror fans will get a kick out of seeing cult favorite Brinke Stevens as a religious fanatical mother who preaches against what Maddy did, calling her a murderer as beloved Troma producer Lloyd Kaufman is the aloof father who can not get in a word edge-wise to protect the daughter he truly cares about. Cult siren Julie Strain has a minor cameo, showing her tits(of course)as the opening murdered male's girlfriend getting her head crushed by a hammer. Oh, and check out the office for which Shawn works, you'll see a lot of Full Moon posters and art-work spread throughout the walls. Question: is it a negative review?
A:
|
yes
|
task285_imdb_answer_generation
|
NIv2
|
zs_opt
| 9
|
train
|
In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no".
One example: Review: For a movie that gets no respect there sure are a lot of memorable quotes listed for this gem. Imagine a movie where Joe Piscopo is actually funny! Maureen Stapleton is a scene stealer. The Moroni character is an absolute scream. Watch for Alan The Skipper Hale jr. as a police Sgt. Question: is it a positive review?
Solution is here: yes
Explanation: There is an expression of appreciation in this movie review, hence we can say it's positive. So generated label is 'yes'.
Now, solve this: Review: This is so exciting! After I saw "La Roue" this afternoon, a short, light-hearted little movie, I consider this one a real treat! This is absolutely delightful and one of the most charming pictures I saw this year. It is the more amazing since it is an early talkie and puts some great pictures of the 30's to shame due to its innovative use of sound in cinema. It's simply filled with music and an adorable mood that's really upbeat and, bottom line, it made me happy! Obviously it wouldn't be so difficult to retrieve the lottery ticket the male lead was looking for, but the pace is so exhilarating and the movie is so spectacularly entertaining that I didn't even think of it twice. The comedy is many times hilarious and I think it is even superior to the Marx Brothers, possibly the biggest comedic force of the time. This is rather perfect. Question: is it a negative review?
Solution:
|
no
|
task285_imdb_answer_generation
|
NIv2
|
fs_opt
| 6
|
train
|
Detailed Instructions: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no".
See one example below:
Problem: Review: For a movie that gets no respect there sure are a lot of memorable quotes listed for this gem. Imagine a movie where Joe Piscopo is actually funny! Maureen Stapleton is a scene stealer. The Moroni character is an absolute scream. Watch for Alan The Skipper Hale jr. as a police Sgt. Question: is it a positive review?
Solution: yes
Explanation: There is an expression of appreciation in this movie review, hence we can say it's positive. So generated label is 'yes'.
Problem: Review: PROBLEM CHILD is one of the worst movies I have seen in the last decade! This is a bad movie about a savage boy adopted by two parents, but he gets into trouble later. That Junior can drive Grandpa's car. He can scare people with a bear. He can put a room on fire! It is a bad movie as much as BATTLEFIELD EARTH. A sequel is an even worse fate. Rent CHICKEN RUN instead.*1/2 out of **** I give it. Question: is it a negative review?
Solution:
|
yes
|
task285_imdb_answer_generation
|
NIv2
|
fs_opt
| 4
|
test
|
instruction:
In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no".
question:
Review: This wasn't the major disaster that I was expecting, but that is about as positive as I can be in my description of the movie. I'm not sure what was meant to be funny about this movie, but I suppose it's all a matter of taste. Personally, I don't find it funny to watch morons living their idiotic lives or making fools of themselves on television, but then again, I'm not a fan of Jerry Springer's pathetic daytime talk show. I didn't get too bored watching this, but I was definitely never enjoying it, either. If you're in the mood to see a bad movie, but one that isn't too painful to sit through, this is a good choice. Question: is it a negative review?
answer:
yes
question:
Review: It was in 1988, when I saw "The Ronnie and Nancy Show" for the first time (on Austrian television). At that time, I was already a very big fan of Spitting Image (since when it won the bronze rose of the Montreux Film Festival in 1986). Of course I recorded every show on tape and watched it again and again - especially "The Ronnie and Nancy Show". I remember that scene when Ronnie stood in front of a painting of Abraham Lincoln (thinking it was a mirror) and said to himself "I need a shave". Or most amusing of all, when he played ball with his dog - but vice-versa!It's such a shame, that Spitting Image seems to fall into oblivion; it was one of the most fantastic and most intelligent made TV-shows ever. Compared to other satirical broadcasts it was definitely the best of all. Well, almost 20 years have passed since then, and I wish I could see the show again. Is it possible to purchase it from someone... somewhere? Question: is it a negative review?
answer:
no
question:
Review: Welcome to movie 17 on the chilling classics 50 pack. Where we'll see, That's right. Another movie that makes absolutely no sense. Seriously, this movie had me so confused at the end, i thought i was rewatching "At Dawn they Sleep." The plot seems simple enough....well that is until 3 seconds into the movie where a girl supposedly killed a cat and then...um.. explodes? i have no idea what happened. and that was BEFORE THE TITLE SCREEN. That's really sad when i can't even tell what happened in the first 3 minutes.Anyway it stars a photographer with a big mustache who finds this girl after dumping his other girlfriend on the way to take pictures of something somewhere. so we get there but not before somebody steals their jeep to drive it 200 feet out of the way towards a town. suspicious? nah. so they decide to stay at this deserted village with one old lady. and then blah blah stuff happens and blah blah talking. The guy with the mustache goes out in the fog for some reason even though the old lady tells him not to. He gets lost and then finds his way back.Oh, i forgot to mention this is all after an incredibly pointless 20 minutes of them staying in the house of a guy who looks like that buggy eyed guy from casablanca. Then they leave. There's really no point to this scene. It's really just padding. if you cut it out no one would have noticed or cared.But sadly, that was actually the best part of the movie. wait. let me rephrase that. REALLY sadly that was the best part of the movie. because the rest is so confusing that i had to look on IMDb to find out what happened. But of course no one else knows so i'm SOL. Seriously, the last 30 minutes of the movie were some of the most mindscrewing moments i've ever seen on film. They dressed her up in a dress, he gets kidnapped, then released, he runs back to the house, then at the end the witches are in the house and it ends? seriously. i have hardly ever been so confused in a movie. i mean, as bad as movies such as "War of the Robots" are, at least they MAKE SENSE. this movie doesn't even make the ATTEMPT to be coherent. the ending was as confusing as the end of "At dawn they sleep" and the plot was much more boring. This movie gets a 1 just for its sheer "i have no idea what happened in this movie"ness. "Witches mountain" gets 1 confused movie watcher out of 10. Question: is it a negative review?
answer:
|
yes
|
task285_imdb_answer_generation
|
NIv2
|
fs_opt
| 9
|
validation
|
You will be given a definition of a task first, then some input of the task.
You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Arabic.
母と 5人の子供
Output:
|
كانت أمي ومعها خمس أطفال.
|
task1224_ted_translation_ja_ar
|
NIv2
|
zs_opt
| 1
|
train
|
Instructions: You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Arabic.
Input: だからシステムを変えればがんに対して著しい効果を発揮することができる
Output:
|
تغير ذلك النظام فتتمكن من الحصول على تأثيرات ملحوظة على السرطان
|
task1224_ted_translation_ja_ar
|
NIv2
|
zs_opt
| 3
|
train
|
instruction:
You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Arabic.
question:
このマシンの規模はどれほどでしょう
answer:
ما هي أبعاد هذه الآلة ؟
question:
体のサイズが最大になるのに５千万年かかりました
answer:
50 مليون عام لتصل لذلك الحجم الكبير
question:
真の戦いは我々自身の中にあります官僚主義や複雑さと戦うのです
answer:
|
إن المعركة الحقيقية هي ضد أنفسنا ، ضد روتيننا ، تعقيدنا.
|
task1224_ted_translation_ja_ar
|
NIv2
|
fs_opt
| 9
|
train
|
Given the task definition and input, reply with output. You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Arabic.
皆さんは気づいたかもしれませんが反対運動の最中では川の上を飛ばしているので安全です
|
إذن في الاحتجاجات ، ربما لاحظتم ، طارت الكاميرات فوق النهر فكانت نوعًا ما آمنة.
|
task1224_ted_translation_ja_ar
|
NIv2
|
zs_opt
| 5
|
train
|
Teacher:You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Arabic.
Teacher: Now, understand the problem? Solve this instance: 数億ドルを費やしてワクチンの製造を急いだのです
Student:
|
مئات ملايين الدولارات أنفقت لتسريع عملية تصنيع اللقاح.
|
task1224_ted_translation_ja_ar
|
NIv2
|
zs_opt
| 6
|
train
|
Detailed Instructions: You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Arabic.
See one example below:
Problem: 地球が今よりも無垢だった時代を訪れたかのようでした
Solution: كان الأمر كزيارة أكثر عصور البراءة على كوكب الأرض
Explanation: The Japanese sentence is correctly translated into Arabic, because the meaning is preserved.
Problem: 静かにしてくれバリー
Solution:
|
ابعد لسانك قليلا... باري
|
task1224_ted_translation_ja_ar
|
NIv2
|
fs_opt
| 4
|
train
|
Instructions: You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Arabic.
Input: 車ばかりの道の代わりに好きな人に沢山出会える道を選ぶことで道のりは全く違ったものになります
Output:
|
أسلك المسار المليء بـالناس الذين تحبهم وليس المليء بـالسيارات ، وسيكون لديك مسار مختلف تمامًا.
|
task1224_ted_translation_ja_ar
|
NIv2
|
zs_opt
| 3
|
train
|
Teacher: You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Arabic.
Teacher: Now, understand the problem? If you are still confused, see the following example:
地球が今よりも無垢だった時代を訪れたかのようでした
Solution: كان الأمر كزيارة أكثر عصور البراءة على كوكب الأرض
Reason: The Japanese sentence is correctly translated into Arabic, because the meaning is preserved.
Now, solve this instance: 人類はこの問題にリオ宣言と京都議定書以来 25年間取り組んでいます
Student:
|
لقد عملنا على حل هذه المشكلة لمدة 25 عاماً ، منذ مؤتمر ريو ، بروتوكولات كيوتو.
|
task1224_ted_translation_ja_ar
|
NIv2
|
fs_opt
| 2
|
train
|
Q: You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Arabic.
私はこれが本当に ― 最近母にこれを見せました
A:
|
التي أرى أنها كانت حقاً... ؛ عرضتها على أمي في مؤخراً.
|
task1224_ted_translation_ja_ar
|
NIv2
|
zs_opt
| 7
|
test
|
Q: You are given a sentence in Japanese. Your job is to translate the Japanese sentence into Arabic.
これらはまだ公開されていないプロジェクトです
A:
|
لذلك فهذه بعض المشاريع الأحدث و التي لم يتم نشرها فعليا بعد.
|
task1224_ted_translation_ja_ar
|
NIv2
|
zs_opt
| 7
|
validation
|
instruction:
In this task, you're given a pair of sentences, sentence 1 and sentence 2, that agree with each other. Your job is to alter sentence 2 so that the pair neither agree nor contradict each other. Generated sentences must be short, with less than 15 words. New information can be introduced. Avoid using pronouns to confuse the subject of the sentence.
question:
Sentence 1: There is a man with an Afro taking photographs of a man grinding on a rainbow rail. Sentence 2: A man is skateboarding while another man photos him.
answer:
The man with the Afro has on bellbottoms.
question:
Sentence 1: An African American man speaks intensely into the microphone. Sentence 2: The man is talking.
answer:
A man is speaking of politics.
question:
Sentence 1: Three ballerinas in pink enter synchronized poses as part of a routine. Sentence 2: Three small ballerinas perform a dance routine.
answer:
|
Some ballerinas are on stage dancing.
|
task184_snli_entailment_to_neutral_text_modification
|
NIv2
|
fs_opt
| 9
|
train
|
instruction:
In this task, you're given a pair of sentences, sentence 1 and sentence 2, that agree with each other. Your job is to alter sentence 2 so that the pair neither agree nor contradict each other. Generated sentences must be short, with less than 15 words. New information can be introduced. Avoid using pronouns to confuse the subject of the sentence.
question:
Sentence 1: Cyclists wait while a man and woman cross the road. Sentence 2: People wait while a man and woman cross the road.
answer:
Cyclists wait while a man and woman cross the busy road.
question:
Sentence 1: This is a bustling city street. Sentence 2: There are a lot of people walking along
answer:
The all the people are walking in the same direction.
question:
Sentence 1: Group of people sitting around a table next to meat hanging on hooks and laid out on a table. Sentence 2: The people are sitting around a table
answer:
|
The people are hanging on hooks laid out
|
task184_snli_entailment_to_neutral_text_modification
|
NIv2
|
fs_opt
| 9
|
train
|
In this task, you're given a pair of sentences, sentence 1 and sentence 2, that agree with each other. Your job is to alter sentence 2 so that the pair neither agree nor contradict each other. Generated sentences must be short, with less than 15 words. New information can be introduced. Avoid using pronouns to confuse the subject of the sentence.
Q: Sentence 1: An older man hunched over doing some pottery while three woman watch him. Sentence 2: One person making pottery while three other people look on.
A:
|
A man making a a jar from clay at a pottery exhibition while three women watch.
|
task184_snli_entailment_to_neutral_text_modification
|
NIv2
|
zs_opt
| 4
|
train
|
In this task, you're given a pair of sentences, sentence 1 and sentence 2, that agree with each other. Your job is to alter sentence 2 so that the pair neither agree nor contradict each other. Generated sentences must be short, with less than 15 words. New information can be introduced. Avoid using pronouns to confuse the subject of the sentence.
Let me give you an example: Sentence 1: Jon saw his friend Tom coming out of the grocery store with a bag of fruit. Sentence 2: Tom had been shopping in the store.
The answer to this example can be: Tom had been shopping for fruit to give Jon.
Here is why: The given sentence is a good alteration. If the changed sentence was something like: "Tom had been sleeping in his house in that time", it'd contradict the first sentence. But this given sentence neither agrees with the first sentence, nor contradicts it.
OK. solve this:
Sentence 1: New sport is being played to show appreciation to the kids who can not walk. Sentence 2: People are playing a sport in honor of crippled people.
Answer:
|
People a playing a sport to help fund a crippled people fund.
|
task184_snli_entailment_to_neutral_text_modification
|
NIv2
|
fs_opt
| 8
|
train
|
Instructions: In this task, you're given a pair of sentences, sentence 1 and sentence 2, that agree with each other. Your job is to alter sentence 2 so that the pair neither agree nor contradict each other. Generated sentences must be short, with less than 15 words. New information can be introduced. Avoid using pronouns to confuse the subject of the sentence.
Input: Sentence 1: A man plays his accordion along the streets, entertaining passersby. Sentence 2: A man is playing an accordion outside.
Output:
|
A man is playing his accordion and collecting money in a hat on the street.
|
task184_snli_entailment_to_neutral_text_modification
|
NIv2
|
zs_opt
| 3
|
train
|
Detailed Instructions: In this task, you're given a pair of sentences, sentence 1 and sentence 2, that agree with each other. Your job is to alter sentence 2 so that the pair neither agree nor contradict each other. Generated sentences must be short, with less than 15 words. New information can be introduced. Avoid using pronouns to confuse the subject of the sentence.
See one example below:
Problem: Sentence 1: Jon saw his friend Tom coming out of the grocery store with a bag of fruit. Sentence 2: Tom had been shopping in the store.
Solution: Tom had been shopping for fruit to give Jon.
Explanation: The given sentence is a good alteration. If the changed sentence was something like: "Tom had been sleeping in his house in that time", it'd contradict the first sentence. But this given sentence neither agrees with the first sentence, nor contradicts it.
Problem: Sentence 1: A pretty asian girl smiles from a window next to a neon takeout sign. Sentence 2: A girl is smiling near a window.
Solution:
|
The girl is smiling because her mom went to get her somethign to eat.
|
task184_snli_entailment_to_neutral_text_modification
|
NIv2
|
fs_opt
| 4
|
train
|
Q: In this task, you're given a pair of sentences, sentence 1 and sentence 2, that agree with each other. Your job is to alter sentence 2 so that the pair neither agree nor contradict each other. Generated sentences must be short, with less than 15 words. New information can be introduced. Avoid using pronouns to confuse the subject of the sentence.
Sentence 1: A small boys dumps water on a baby. Sentence 2: A small boy and a baby
A:
|
A boy is dumping a bucket of water.
|
task184_snli_entailment_to_neutral_text_modification
|
NIv2
|
zs_opt
| 7
|
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, that agree with each other. Your job is to alter sentence 2 so that the pair neither agree nor contradict each other. Generated sentences must be short, with less than 15 words. New information can be introduced. Avoid using pronouns to confuse the subject of the sentence.
Sentence 1: A man is smiling at a stuffed lion Sentence 2: The man is smiling.
|
The man likes the lion.
|
task184_snli_entailment_to_neutral_text_modification
|
NIv2
|
zs_opt
| 5
|
train
|
In this task, you're given a pair of sentences, sentence 1 and sentence 2, that agree with each other. Your job is to alter sentence 2 so that the pair neither agree nor contradict each other. Generated sentences must be short, with less than 15 words. New information can be introduced. Avoid using pronouns to confuse the subject of the sentence.
Sentence 1: An African American man speaks intensely into the microphone. Sentence 2: The man is talking.
A man is speaking of politics.
Sentence 1: A man is sitting next to a pizza oven. Sentence 2: a person next to an oven
a man is cooking a pizza in the oven
Sentence 1: A little girl and a dog play near a stream. Sentence 2: A girl and a dog are outside.
|
A girl and her dog are playing in a park.
|
task184_snli_entailment_to_neutral_text_modification
|
NIv2
|
fs_opt
| 0
|
test
|
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, that agree with each other. Your job is to alter sentence 2 so that the pair neither agree nor contradict each other. Generated sentences must be short, with less than 15 words. New information can be introduced. Avoid using pronouns to confuse the subject of the sentence.
Sentence 1: A tall man in a green sweater is holding his hands out at chest height like he is holding a book in a room of 3 people. Sentence 2: A room full of people is doing poses.
Output:
|
a man preaches to a group of three
|
task184_snli_entailment_to_neutral_text_modification
|
NIv2
|
zs_opt
| 1
|
validation
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.