metadata
annotations_creators:
- crowdsourced
language:
- en
language_creators:
- found
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: Question Answering via Sentence Composition (QASC)
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- question-answering
- multiple-choice
task_ids:
- extractive-qa
- multiple-choice-qa
paperswithcode_id: qasc
dataset_info:
features:
- name: id
dtype: string
- name: question
dtype: string
- name: choices
sequence:
- name: text
dtype: string
- name: label
dtype: string
- name: answerKey
dtype: string
- name: fact1
dtype: string
- name: fact2
dtype: string
- name: combinedfact
dtype: string
- name: formatted_question
dtype: string
splits:
- name: test
num_bytes: 393683
num_examples: 920
- name: train
num_bytes: 4919377
num_examples: 8134
- name: validation
num_bytes: 562352
num_examples: 926
download_size: 1616514
dataset_size: 5875412
Dataset Card for "qasc"
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: https://allenai.org/data/qasc
- Repository: https://github.com/allenai/qasc/
- Paper: QASC: A Dataset for Question Answering via Sentence Composition
- Point of Contact: More Information Needed
- Size of downloaded dataset files: 1.61 MB
- Size of the generated dataset: 5.87 MB
- Total amount of disk used: 7.49 MB
Dataset Summary
QASC is a question-answering dataset with a focus on sentence composition. It consists of 9,980 8-way multiple-choice questions about grade school science (8,134 train, 926 dev, 920 test), and comes with a corpus of 17M sentences.
Supported Tasks and Leaderboards
Languages
Dataset Structure
Data Instances
default
- Size of downloaded dataset files: 1.61 MB
- Size of the generated dataset: 5.87 MB
- Total amount of disk used: 7.49 MB
An example of 'validation' looks as follows.
{
"answerKey": "F",
"choices": {
"label": ["A", "B", "C", "D", "E", "F", "G", "H"],
"text": ["sand", "occurs over a wide range", "forests", "Global warming", "rapid changes occur", "local weather conditions", "measure of motion", "city life"]
},
"combinedfact": "Climate is generally described in terms of local weather conditions",
"fact1": "Climate is generally described in terms of temperature and moisture.",
"fact2": "Fire behavior is driven by local weather conditions such as winds, temperature and moisture.",
"formatted_question": "Climate is generally described in terms of what? (A) sand (B) occurs over a wide range (C) forests (D) Global warming (E) rapid changes occur (F) local weather conditions (G) measure of motion (H) city life",
"id": "3NGI5ARFTT4HNGVWXAMLNBMFA0U1PG",
"question": "Climate is generally described in terms of what?"
}
Data Fields
The data fields are the same among all splits.
default
id
: astring
feature.question
: astring
feature.choices
: a dictionary feature containing:text
: astring
feature.label
: astring
feature.
answerKey
: astring
feature.fact1
: astring
feature.fact2
: astring
feature.combinedfact
: astring
feature.formatted_question
: astring
feature.
Data Splits
name | train | validation | test |
---|---|---|---|
default | 8134 | 926 | 920 |
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 released under CC BY 4.0 license.
Citation Information
@article{allenai:qasc,
author = {Tushar Khot and Peter Clark and Michal Guerquin and Peter Jansen and Ashish Sabharwal},
title = {QASC: A Dataset for Question Answering via Sentence Composition},
journal = {arXiv:1910.11473v2},
year = {2020},
}
Contributions
Thanks to @thomwolf, @patrickvonplaten, @lewtun for adding this dataset.