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

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

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: a string feature.
document a dictionary feature containing:
- title: a string feature.
- url: a string feature.
- html: a string feature.
- tokens: a dictionary feature containing:
  - token: a string feature.
  - is_html: a bool feature.
  - start_byte: a int64 feature.
  - end_byte: a int64 feature.
question: a dictionary feature containing:
- text: a string feature.
- tokens: a list of string features.
long_answer_candidates: a dictionary feature containing:
- start_token: a int64 feature.
- end_token: a int64 feature.
- start_byte: a int64 feature.
- end_byte: a int64 feature.
- top_level: a bool feature.
annotations: a dictionary feature containing:
- id: a string feature.
- long_answers: a dictionary feature containing:
  - start_token: a int64 feature.
  - end_token: a int64 feature.
  - start_byte: a int64 feature.
  - end_byte: a int64 feature.
  - candidate_index: a int64 feature.
- short_answers: a dictionary feature containing:
  - start_token: a int64 feature.
  - end_token: a int64 feature.
  - start_byte: a int64 feature.
  - end_byte: a int64 feature.
  - text: a string feature.
- yes_no_answer: a classification label, with possible values including NO (0), YES (1).

Data Splits

name	train	validation
default	307373	7830
dev	N/A	7830

Dataset Creation

Curation Rationale

More Information Needed

Source Data

Initial Data Collection and Normalization

More Information Needed

Who are the source language producers?

More Information Needed

Annotations

Considerations for Using the Data

Social Impact of Dataset

More Information Needed

Discussion of Biases

More Information Needed

Other Known Limitations

More Information Needed

Additional Information

Dataset Curators

More Information Needed

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}
}

Contributions

Thanks to @thomwolf, @lhoestq for adding this dataset.

Datasets:
natural_questions

Dataset Card for Natural Questions

Table of Contents

Dataset Description

Dataset Summary

Supported Tasks and Leaderboards

Languages

Dataset Structure

Data Instances

Data Fields

default

Data Splits

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

Contributions