Search is not available for this dataset
sentence
string
pronoun
string
candidates
sequence
label
class label
The bee landed on the flower because it had pollen.
it
[ "The bee", "the flower" ]
11
The bee landed on the flower because it wanted pollen.
it
[ "The bee", "the flower" ]
00
When Debbie splashed Tina, she got in trouble.
she
[ "Debbie", "Tina" ]
00
When Debbie splashed Tina, she got wet.
she
[ "Debbie", "Tina" ]
11
The bus driver yelled at a kid after she drove her vehicle.
she
[ "The bus driver", "a kid" ]
00
The bus driver yelled at a kid after she broke a window.
she
[ "The bus driver", "a kid" ]
11
Jimbo was running from Bobbert because he smelled awful.
he
[ "Jimbo", "Bobbert" ]
11
Jimbo was running from Bobbert because he wanted to get to the car first.
he
[ "Jimbo", "Bobbert" ]
00
Jimbo attacked Bobbert because he stole an elephant from the zoo.
he
[ "Jimbo", "Bobbert" ]
11
Jimbo attacked Bobbert because he could not control his rage.
he
[ "Jimbo", "Bobbert" ]
00
Jimbo was afraid of Bobbert because she gets scared around new people.
she
[ "Jimbo", "Bobbert" ]
00
Jimbo was afraid of Bobbert because she was running around with a bloody spear.
she
[ "Jimbo", "Bobbert" ]
11
The man stole the neighbor's bike because he needed one.
he
[ "The man", "the neighbor" ]
00
The man stole the neighbor's bike because he had one extra.
he
[ "The man", "the neighbor" ]
11
The bird ate the pie and it died.
it
[ "The bird", "the pie" ]
00
The bird ate the pie and it was ruined.
it
[ "The bird", "the pie" ]
11
The bird perched on the limb and it bent.
it
[ "The bird", "the limb" ]
11
The bird perched on the limb and it sang.
it
[ "The bird", "the limb" ]
00
Mary cleaned Susan's room and she was thankful.
she
[ "Mary", "Susan" ]
11
Mary cleaned Susan's room and she asked a favor.
she
[ "Mary", "Susan" ]
00
Mary stabbed Jennifer, so John took her to the hospital.
her
[ "Mary", "Jennifer" ]
11
Mary stabbed Jennifer, so John reported her to the police.
her
[ "Mary", "Jennifer" ]
00
Lions eat zebras because they are predators.
they
[ "Lions", "zebras" ]
00
Lions eat zebras because they are meaty.
they
[ "Lions", "zebras" ]
11
The coach criticized the player because he did not adhere to the team's formation.
he
[ "The coach", "the player" ]
11
The coach criticized the player because he explicitly told everyone not to break the team's formation.
he
[ "The coach", "the player" ]
00
The academic clubs lost their members because they were poorly funded.
they
[ "The academic clubs", "their members" ]
00
The academic clubs lost their members because they did not have free time.
they
[ "The academic clubs", "their members" ]
11
James asked Robert for a favor, but he refused.
he
[ "James", "Robert" ]
11
James asked Robert for a favor, but he was refused.
he
[ "James", "Robert" ]
00
The teacher did not recommend William because he was not a good student.
he
[ "The teacher", "William" ]
11
The teacher did not recommend William because he had high standards.
he
[ "The teacher", "William" ]
00
The doctor told Susan that she had cancer.
she
[ "The doctor", "Susan" ]
11
The doctor told Susan that she had been busy.
she
[ "The doctor", "Susan" ]
00
The professor grading the student's paper said that he was stupid.
he
[ "The professor", "the student" ]
11
The professor grading the student's paper said that he loved it.
he
[ "The professor", "the student" ]
00
Jeremy annoyed Justin so he can leave the room.
he
[ "Jeremy", "Justin" ]
11
Jeremy annoyed Justin so he can have the room.
he
[ "Jeremy", "Justin" ]
00
Paula liked Ness more than Pokey because he was nice to her.
he
[ "Ness", "Pokey" ]
00
Paula liked Ness more than Pokey because he was mean to her.
he
[ "Ness", "Pokey" ]
11
Rocky lost to Clubber Lang because he was not ready for the fight.
he
[ "Rocky", "Clubber Lang" ]
00
Rocky lost to Clubber Lang because he was ready for the fight.
he
[ "Rocky", "Clubber Lang" ]
11
Aaron kissed Dan because he wanted to.
he
[ "Aaron", "Dan" ]
00
Aaron kissed Dan because he wanted him to.
he
[ "Aaron", "Dan" ]
11
The students fell asleep during the professor's lectures because they were boring.
they
[ "The students", "the professor's lectures" ]
11
The students fell asleep during the professor's lectures because they were bored.
they
[ "The students", "the professor's lectures" ]
00
Derrick begged his boss for a raise but he did not get one.
he
[ "Derrick", "his boss" ]
00
Derrick begged his boss for a raise but he did not give one.
he
[ "Derrick", "his boss" ]
11
The jurors deliberated on the defendants' fate for hours, but they did not reach a verdict.
they
[ "The jurors", "the defendants" ]
00
The jurors deliberated on the defendants' fate for hours, but they didn't receive the death penalty.
they
[ "The jurors", "the defendants" ]
11
The orchestra was booed by the audience because they had performed poorly.
they
[ "The orchestra", "the audience" ]
00
The orchestra was booed by the audience because they had expected a rock band.
they
[ "The orchestra", "the audience" ]
11
Jacob gave William money because he needed some.
he
[ "Jacob", "William" ]
11
Jacob gave William money because he sold the car.
he
[ "Jacob", "William" ]
00
Alexandra told Kelly not to get a tattoo because she raised her conservatively.
she
[ "Alexandra", "Kelly" ]
00
Alexandra told Kelly not to get a tattoo because she would seem unprofessional.
she
[ "Alexandra", "Kelly" ]
11
Olivia tried to counsel Emily, but she was not interested.
she
[ "Olivia", "Emily" ]
11
Olivia tried to counsel Emily, but she was rejected.
she
[ "Olivia", "Emily" ]
00
James went to Sully's arcade and he asked for tickets.
he
[ "James", "Sully" ]
00
James went to Sully's arcade but he refused to let him in.
he
[ "James", "Sully" ]
11
Kurt flew in Alex's plane, and he thanked him.
he
[ "Kurt", "Alex" ]
00
Kurt flew in Alex's plane, and he asked him to come again.
he
[ "Kurt", "Alex" ]
11
Bill was robbed by John, so the officer arrested him.
him
[ "Bill", "John" ]
11
Bill was robbed by John, so the officer helped him.
him
[ "Bill", "John" ]
00
He put snow on the smiley face because it was wet.
it
[ "snow", "the smiley face" ]
00
He put snow on the smiley face because it was dry.
it
[ "snow", "the smiley face" ]
11
The kitten played with the yarn because it was fun.
it
[ "The kitten", "the yarn" ]
11
The kitten played with the yarn because it was bored.
it
[ "The kitten", "the yarn" ]
00
I chopped down the tree with my axe because it was tall.
it
[ "the tree", "my axe" ]
00
I chopped down the tree with my axe because it was sharp.
it
[ "the tree", "my axe" ]
11
Spiderman defeated Magnito because he is a good guy.
he
[ "Spiderman", "Magnito" ]
00
Spiderman defeated Magnito because he is a bad guy.
he
[ "Spiderman", "Magnito" ]
11
The citizens rebelled against the government because they were being repressed.
they
[ "The citizens", "the government" ]
00
The citizens rebelled against the government because they were being mean.
they
[ "The citizens", "the government" ]
11
Cats are smarter than dogs because they always land on their feet.
they
[ "Cats", "dogs" ]
00
Cats are smarter than dogs because they bark for no reason.
they
[ "Cats", "dogs" ]
11
The ball hit the window and Bill repaired it.
it
[ "The ball", "the window" ]
11
The ball hit the window and Bill caught it.
it
[ "The ball", "the window" ]
00
Robert fired Chris because he couldn't do the job.
he
[ "Robert", "Chris" ]
11
Robert fired Chris because he no longer needed workers.
he
[ "Robert", "Chris" ]
00
Steve scratched Johnny because he was angry.
he
[ "Steve", "Johnny" ]
00
Steve scratched Johnny so he became angry.
he
[ "Steve", "Johnny" ]
11
The youth outran the old man because he was in shape.
he
[ "The youth", "the old man" ]
00
The youth outran the old man because he broke his hip.
he
[ "The youth", "the old man" ]
11
Video games are outselling movies because they are fun to play.
they
[ "Video games", "movies" ]
00
Video games are outselling movies because they are an old medium.
they
[ "Video games", "movies" ]
11
Google bought Motorola because they want its customer base.
they
[ "Google", "Motorola" ]
00
Google bought Motorola because they were bankrupt.
they
[ "Google", "Motorola" ]
11
Sam cheated Sally but she did not cry.
she
[ "Sally", "Sam" ]
00
Sam cheated Sally but she did not repent.
she
[ "Sally", "Sam" ]
11
Keith fired Blaine but he did not regret.
he
[ "Keith", "Blaine" ]
00
Keith fired Blaine even though he is diligent.
he
[ "Keith", "Blaine" ]
11
The storm delayed the flight as it was very dangerous.
it
[ "The storm", "the flight" ]
00
The storm delayed the flight as it was going over the ocean.
it
[ "The storm", "the flight" ]
11
John flicked Bill because he saw a fly on his shirt.
he
[ "John", "Bill" ]
00
John flicked Bill because he had a fly on his shirt.
he
[ "John", "Bill" ]
11
The zombies chased the survivors because they were hungry.
they
[ "The zombies", "the survivors" ]
00
The zombies chased the survivors because they were tasty.
they
[ "The zombies", "the survivors" ]
11
Medvedev will cede the presidency to Putin because he is more popular.
he
[ "Medvedev", "Putin" ]
11
Medvedev will cede the presidency to Putin because he is less popular.
he
[ "Medvedev", "Putin" ]
00

Dataset Card for "definite_pronoun_resolution"

Dataset Summary

Composed by 30 students from one of the author's undergraduate classes. These sentence pairs cover topics ranging from real events (e.g., Iran's plan to attack the Saudi ambassador to the U.S.) to events/characters in movies (e.g., Batman) and purely imaginary situations, largely reflecting the pop culture as perceived by the American kids born in the early 90s. Each annotated example spans four lines: the first line contains the sentence, the second line contains the target pronoun, the third line contains the two candidate antecedents, and the fourth line contains the correct antecedent. If the target pronoun appears more than once in the sentence, its first occurrence is the one to be resolved.

Supported Tasks and Leaderboards

More Information Needed

Languages

More Information Needed

Dataset Structure

Data Instances

plain_text

  • Size of downloaded dataset files: 0.23 MB
  • Size of the generated dataset: 0.24 MB
  • Total amount of disk used: 0.47 MB

An example of 'train' looks as follows.

{
    "candidates": ["coreference resolution", "chunking"],
    "label": 0,
    "pronoun": "it",
    "sentence": "There is currently more work on coreference resolution than on chunking because it is a problem that is still far from being solved."
}

Data Fields

The data fields are the same among all splits.

plain_text

  • sentence: a string feature.
  • pronoun: a string feature.
  • candidates: a list of string features.
  • label: a classification label, with possible values including 0 (0), 1 (1).

Data Splits

name train test
plain_text 1322 564

Dataset Creation

Curation Rationale

More Information Needed

Source Data

Initial Data Collection and Normalization

More Information Needed

Who are the source language producers?

More Information Needed

Annotations

Annotation process

More Information Needed

Who are the annotators?

More Information Needed

Personal and Sensitive Information

More Information Needed

Considerations for Using the Data

Social Impact of Dataset

More Information Needed

Discussion of Biases

More Information Needed

Other Known Limitations

More Information Needed

Additional Information

Dataset Curators

More Information Needed

Licensing Information

More Information Needed

Citation Information

@inproceedings{rahman2012resolving,
  title={Resolving complex cases of definite pronouns: the winograd schema challenge},
  author={Rahman, Altaf and Ng, Vincent},
  booktitle={Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning},
  pages={777--789},
  year={2012},
  organization={Association for Computational Linguistics}
}

Contributions

Thanks to @thomwolf, @lewtun, @patrickvonplaten for adding this dataset.

Downloads last month
129

Models trained or fine-tuned on community-datasets/definite_pronoun_resolution