Datasets:
Tasks:
Question Answering
Modalities:
Text
Formats:
parquet
Sub-tasks:
open-domain-qa
Languages:
English
Size:
10K - 100K
ArXiv:
License:
metadata
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
language:
- en
license:
- mit
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- open-domain-qa
paperswithcode_id: commonsenseqa
pretty_name: CommonsenseQA
dataset_info:
features:
- name: id
dtype: string
- name: question
dtype: string
- name: question_concept
dtype: string
- name: choices
sequence:
- name: label
dtype: string
- name: text
dtype: string
- name: answerKey
dtype: string
splits:
- name: train
num_bytes: 2207794
num_examples: 9741
- name: validation
num_bytes: 273848
num_examples: 1221
- name: test
num_bytes: 257842
num_examples: 1140
download_size: 1558570
dataset_size: 2739484
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
Dataset Card for "commonsense_qa"
Table of Contents
- Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: https://www.tau-nlp.org/commonsenseqa
- Repository: https://github.com/jonathanherzig/commonsenseqa
- Paper: https://arxiv.org/abs/1811.00937
- Point of Contact: More Information Needed
- Size of downloaded dataset files: 4.68 MB
- Size of the generated dataset: 2.18 MB
- Total amount of disk used: 6.86 MB
Dataset Summary
CommonsenseQA is a new multiple-choice question answering dataset that requires different types of commonsense knowledge to predict the correct answers . It contains 12,102 questions with one correct answer and four distractor answers. The dataset is provided in two major training/validation/testing set splits: "Random split" which is the main evaluation split, and "Question token split", see paper for details.
Supported Tasks and Leaderboards
Languages
The dataset is in English (en
).
Dataset Structure
Data Instances
default
- Size of downloaded dataset files: 4.68 MB
- Size of the generated dataset: 2.18 MB
- Total amount of disk used: 6.86 MB
An example of 'train' looks as follows:
{'id': '075e483d21c29a511267ef62bedc0461',
'question': 'The sanctions against the school were a punishing blow, and they seemed to what the efforts the school had made to change?',
'question_concept': 'punishing',
'choices': {'label': ['A', 'B', 'C', 'D', 'E'],
'text': ['ignore', 'enforce', 'authoritarian', 'yell at', 'avoid']},
'answerKey': 'A'}
Data Fields
The data fields are the same among all splits.
default
id
(str
): Unique ID.question
: astring
feature.question_concept
(str
): ConceptNet concept associated to the question.choices
: a dictionary feature containing:label
: astring
feature.text
: astring
feature.
answerKey
: astring
feature.
Data Splits
name | train | validation | test |
---|---|---|---|
default | 9741 | 1221 | 1140 |
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
The dataset is licensed under the MIT License.
See: https://github.com/jonathanherzig/commonsenseqa/issues/5
Citation Information
@inproceedings{talmor-etal-2019-commonsenseqa,
title = "{C}ommonsense{QA}: A Question Answering Challenge Targeting Commonsense Knowledge",
author = "Talmor, Alon and
Herzig, Jonathan and
Lourie, Nicholas and
Berant, Jonathan",
booktitle = "Proceedings of the 2019 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)",
month = jun,
year = "2019",
address = "Minneapolis, Minnesota",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/N19-1421",
doi = "10.18653/v1/N19-1421",
pages = "4149--4158",
archivePrefix = "arXiv",
eprint = "1811.00937",
primaryClass = "cs",
}
Contributions
Thanks to @thomwolf, @lewtun, @albertvillanova, @patrickvonplaten for adding this dataset.