Datasets:
Tasks:
Question Answering
Modalities:
Text
Formats:
parquet
Sub-tasks:
open-domain-qa
Languages:
English
Size:
10K - 100K
License:
metadata
annotations_creators:
- no-annotation
language_creators:
- crowdsourced
language:
- en
license:
- cc-by-sa-3.0
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- open-domain-qa
paperswithcode_id: natural-questions
pretty_name: Natural Questions
dataset_info:
- config_name: default
features:
- name: id
dtype: string
- name: document
struct:
- name: html
dtype: string
- name: title
dtype: string
- name: tokens
sequence:
- name: end_byte
dtype: int64
- name: is_html
dtype: bool
- name: start_byte
dtype: int64
- name: token
dtype: string
- name: url
dtype: string
- name: question
struct:
- name: text
dtype: string
- name: tokens
sequence: string
- name: long_answer_candidates
sequence:
- name: end_byte
dtype: int64
- name: end_token
dtype: int64
- name: start_byte
dtype: int64
- name: start_token
dtype: int64
- name: top_level
dtype: bool
- name: annotations
sequence:
- name: id
dtype: string
- name: long_answer
struct:
- name: candidate_index
dtype: int64
- name: end_byte
dtype: int64
- name: end_token
dtype: int64
- name: start_byte
dtype: int64
- name: start_token
dtype: int64
- name: short_answers
sequence:
- name: end_byte
dtype: int64
- name: end_token
dtype: int64
- name: start_byte
dtype: int64
- name: start_token
dtype: int64
- name: text
dtype: string
- name: yes_no_answer
dtype:
class_label:
names:
'0': 'NO'
'1': 'YES'
splits:
- name: train
num_bytes: 143039948860
num_examples: 307373
- name: validation
num_bytes: 3451288641
num_examples: 7830
download_size: 56843626971
dataset_size: 146491237501
- config_name: dev
features:
- name: id
dtype: string
- name: document
struct:
- name: title
dtype: string
- name: url
dtype: string
- name: html
dtype: string
- name: tokens
sequence:
- name: token
dtype: string
- name: is_html
dtype: bool
- name: start_byte
dtype: int64
- name: end_byte
dtype: int64
- name: question
struct:
- name: text
dtype: string
- name: tokens
sequence: string
- name: long_answer_candidates
sequence:
- name: start_token
dtype: int64
- name: end_token
dtype: int64
- name: start_byte
dtype: int64
- name: end_byte
dtype: int64
- name: top_level
dtype: bool
- name: annotations
sequence:
- name: id
dtype: string
- name: long_answer
struct:
- name: start_token
dtype: int64
- name: end_token
dtype: int64
- name: start_byte
dtype: int64
- name: end_byte
dtype: int64
- name: candidate_index
dtype: int64
- name: short_answers
sequence:
- name: start_token
dtype: int64
- name: end_token
dtype: int64
- name: start_byte
dtype: int64
- name: end_byte
dtype: int64
- name: text
dtype: string
- name: yes_no_answer
dtype:
class_label:
names:
'0': 'NO'
'1': 'YES'
splits:
- name: validation
num_bytes: 3451288639
num_examples: 7830
download_size: 1337126358
dataset_size: 3451288639
configs:
- config_name: default
data_files:
- split: train
path: default/train-*
- split: validation
path: default/validation-*
- config_name: dev
data_files:
- split: validation
path: dev/validation-*
Dataset Card for Natural Questions
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: https://ai.google.com/research/NaturalQuestions/dataset
- Repository: https://github.com/google-research-datasets/natural-questions
- Paper: https://research.google/pubs/pub47761/
- Point of Contact: More Information Needed
- Size of downloaded dataset files: 45.07 GB
- Size of the generated dataset: 99.80 GB
- Total amount of disk used: 144.87 GB
Dataset Summary
The NQ corpus contains questions from real users, and it requires QA systems to read and comprehend an entire Wikipedia article that may or may not contain the answer to the question. The inclusion of real user questions, and the requirement that solutions should read an entire page to find the answer, cause NQ to be a more realistic and challenging task than prior QA datasets.
Supported Tasks and Leaderboards
https://ai.google.com/research/NaturalQuestions
Languages
en
Dataset Structure
Data Instances
- Size of downloaded dataset files: 45.07 GB
- Size of the generated dataset: 99.80 GB
- Total amount of disk used: 144.87 GB
An example of 'train' looks as follows. This is a toy example.
{
"id": "797803103760793766",
"document": {
"title": "Google",
"url": "http://www.wikipedia.org/Google",
"html": "<html><body><h1>Google Inc.</h1><p>Google was founded in 1998 By:<ul><li>Larry</li><li>Sergey</li></ul></p></body></html>",
"tokens":[
{"token": "<h1>", "start_byte": 12, "end_byte": 16, "is_html": True},
{"token": "Google", "start_byte": 16, "end_byte": 22, "is_html": False},
{"token": "inc", "start_byte": 23, "end_byte": 26, "is_html": False},
{"token": ".", "start_byte": 26, "end_byte": 27, "is_html": False},
{"token": "</h1>", "start_byte": 27, "end_byte": 32, "is_html": True},
{"token": "<p>", "start_byte": 32, "end_byte": 35, "is_html": True},
{"token": "Google", "start_byte": 35, "end_byte": 41, "is_html": False},
{"token": "was", "start_byte": 42, "end_byte": 45, "is_html": False},
{"token": "founded", "start_byte": 46, "end_byte": 53, "is_html": False},
{"token": "in", "start_byte": 54, "end_byte": 56, "is_html": False},
{"token": "1998", "start_byte": 57, "end_byte": 61, "is_html": False},
{"token": "by", "start_byte": 62, "end_byte": 64, "is_html": False},
{"token": ":", "start_byte": 64, "end_byte": 65, "is_html": False},
{"token": "<ul>", "start_byte": 65, "end_byte": 69, "is_html": True},
{"token": "<li>", "start_byte": 69, "end_byte": 73, "is_html": True},
{"token": "Larry", "start_byte": 73, "end_byte": 78, "is_html": False},
{"token": "</li>", "start_byte": 78, "end_byte": 83, "is_html": True},
{"token": "<li>", "start_byte": 83, "end_byte": 87, "is_html": True},
{"token": "Sergey", "start_byte": 87, "end_byte": 92, "is_html": False},
{"token": "</li>", "start_byte": 92, "end_byte": 97, "is_html": True},
{"token": "</ul>", "start_byte": 97, "end_byte": 102, "is_html": True},
{"token": "</p>", "start_byte": 102, "end_byte": 106, "is_html": True}
],
},
"question" :{
"text": "who founded google",
"tokens": ["who", "founded", "google"]
},
"long_answer_candidates": [
{"start_byte": 32, "end_byte": 106, "start_token": 5, "end_token": 22, "top_level": True},
{"start_byte": 65, "end_byte": 102, "start_token": 13, "end_token": 21, "top_level": False},
{"start_byte": 69, "end_byte": 83, "start_token": 14, "end_token": 17, "top_level": False},
{"start_byte": 83, "end_byte": 92, "start_token": 17, "end_token": 20 , "top_level": False}
],
"annotations": [{
"id": "6782080525527814293",
"long_answer": {"start_byte": 32, "end_byte": 106, "start_token": 5, "end_token": 22, "candidate_index": 0},
"short_answers": [
{"start_byte": 73, "end_byte": 78, "start_token": 15, "end_token": 16, "text": "Larry"},
{"start_byte": 87, "end_byte": 92, "start_token": 18, "end_token": 19, "text": "Sergey"}
],
"yes_no_answer": -1
}]
}
Data Fields
The data fields are the same among all splits.
default
id
: astring
feature.document
a dictionary feature containing:title
: astring
feature.url
: astring
feature.html
: astring
feature.tokens
: a dictionary feature containing:token
: astring
feature.is_html
: abool
feature.start_byte
: aint64
feature.end_byte
: aint64
feature.
question
: a dictionary feature containing:text
: astring
feature.tokens
: alist
ofstring
features.
long_answer_candidates
: a dictionary feature containing:start_token
: aint64
feature.end_token
: aint64
feature.start_byte
: aint64
feature.end_byte
: aint64
feature.top_level
: abool
feature.
annotations
: a dictionary feature containing:id
: astring
feature.long_answers
: a dictionary feature containing:start_token
: aint64
feature.end_token
: aint64
feature.start_byte
: aint64
feature.end_byte
: aint64
feature.candidate_index
: aint64
feature.
short_answers
: a dictionary feature containing:start_token
: aint64
feature.end_token
: aint64
feature.start_byte
: aint64
feature.end_byte
: aint64
feature.text
: astring
feature.
yes_no_answer
: a classification label, with possible values includingNO
(0),YES
(1).
Data Splits
name | train | validation |
---|---|---|
default | 307373 | 7830 |
dev | N/A | 7830 |
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
Creative Commons Attribution-ShareAlike 3.0 Unported.
Citation Information
@article{47761,
title = {Natural Questions: a Benchmark for Question Answering Research},
author = {Tom Kwiatkowski and Jennimaria Palomaki and Olivia Redfield and Michael Collins and Ankur Parikh and Chris Alberti and Danielle Epstein and Illia Polosukhin and Matthew Kelcey and Jacob Devlin and Kenton Lee and Kristina N. Toutanova and Llion Jones and Ming-Wei Chang and Andrew Dai and Jakob Uszkoreit and Quoc Le and Slav Petrov},
year = {2019},
journal = {Transactions of the Association of Computational Linguistics}
}