metadata
pretty_name: SQuAD2.0
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
language:
- en
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- open-domain-qa
- extractive-qa
paperswithcode_id: squad
train-eval-index:
- config: squad_v2
task: question-answering
task_id: extractive_question_answering
splits:
train_split: train
eval_split: validation
col_mapping:
question: question
context: context
answers:
text: text
answer_start: answer_start
metrics:
- type: squad_v2
name: SQuAD v2
dataset_info:
features:
- name: id
dtype: string
- name: title
dtype: string
- name: context
dtype: string
- name: question
dtype: string
- name: answers
sequence:
- name: text
dtype: string
- name: answer_start
dtype: int32
config_name: squad_v2
splits:
- name: train
num_bytes: 116699950
num_examples: 130319
- name: validation
num_bytes: 11660302
num_examples: 11873
download_size: 46494161
dataset_size: 128360252
Dataset Card for "squad_v2"
Table of Contents
- Dataset Card for "squad_v2"
Dataset Description
- Homepage: https://rajpurkar.github.io/SQuAD-explorer/
- Repository: More Information Needed
- Paper: More Information Needed
- Point of Contact: More Information Needed
- Size of downloaded dataset files: 46.49 MB
- Size of the generated dataset: 128.52 MB
- Total amount of disk used: 175.02 MB
Dataset Summary
combines the 100,000 questions in SQuAD1.1 with over 50,000 unanswerable questions written adversarially by crowdworkers to look similar to answerable ones. To do well on SQuAD2.0, systems must not only answer questions when possible, but also determine when no answer is supported by the paragraph and abstain from answering.
Supported Tasks and Leaderboards
Languages
Dataset Structure
Data Instances
squad_v2
- Size of downloaded dataset files: 46.49 MB
- Size of the generated dataset: 128.52 MB
- Total amount of disk used: 175.02 MB
An example of 'validation' looks as follows.
This example was too long and was cropped:
{
"answers": {
"answer_start": [94, 87, 94, 94],
"text": ["10th and 11th centuries", "in the 10th and 11th centuries", "10th and 11th centuries", "10th and 11th centuries"]
},
"context": "\"The Normans (Norman: Nourmands; French: Normands; Latin: Normanni) were the people who in the 10th and 11th centuries gave thei...",
"id": "56ddde6b9a695914005b9629",
"question": "When were the Normans in Normandy?",
"title": "Normans"
}
Data Fields
The data fields are the same among all splits.
squad_v2
id: astringfeature.title: astringfeature.context: astringfeature.question: astringfeature.answers: a dictionary feature containing:text: astringfeature.answer_start: aint32feature.
Data Splits
| name | train | validation |
|---|---|---|
| squad_v2 | 130319 | 11873 |
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
@article{2016arXiv160605250R,
author = {{Rajpurkar}, Pranav and {Zhang}, Jian and {Lopyrev},
Konstantin and {Liang}, Percy},
title = "{SQuAD: 100,000+ Questions for Machine Comprehension of Text}",
journal = {arXiv e-prints},
year = 2016,
eid = {arXiv:1606.05250},
pages = {arXiv:1606.05250},
archivePrefix = {arXiv},
eprint = {1606.05250},
}
Contributions
Thanks to @lewtun, @albertvillanova, @patrickvonplaten, @thomwolf for adding this dataset.