Datasets:
annotations_creators:
- expert-generated
language_creators:
- crowdsourced
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- word-sense-disambiguation
paperswithcode_id: definite-pronoun-resolution-dataset
pretty_name: Definite Pronoun Resolution Dataset
dataset_info:
features:
- name: sentence
dtype: string
- name: pronoun
dtype: string
- name: candidates
sequence: string
length: 2
- name: label
dtype:
class_label:
names:
'0': '0'
'1': '1'
config_name: plain_text
splits:
- name: test
num_bytes: 71691
num_examples: 564
- name: train
num_bytes: 171511
num_examples: 1322
download_size: 227452
dataset_size: 243202
Dataset Card for "definite_pronoun_resolution"
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: https://www.hlt.utdallas.edu/~vince/data/emnlp12/
- Repository: More Information Needed
- Paper: More Information Needed
- Point of Contact: More Information Needed
- Size of downloaded dataset files: 0.23 MB
- Size of the generated dataset: 0.24 MB
- Total amount of disk used: 0.47 MB
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
Languages
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: astringfeature.pronoun: astringfeature.candidates: alistofstringfeatures.label: a classification label, with possible values including0(0),1(1).
Data Splits
| name | train | test |
|---|---|---|
| plain_text | 1322 | 564 |
Dataset Creation
Curation Rationale
Source Data
Initial Data Collection and Normalization
Who are the source language producers?
Annotations
Annotation process
Who are the annotators?
Personal and Sensitive Information
Considerations for Using the Data
Social Impact of Dataset
Discussion of Biases
Other Known Limitations
Additional Information
Dataset Curators
Licensing Information
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.