Dataset:



Dataset Card for "wiki_dpr"

Dataset Summary

This is the wikipedia split used to evaluate the Dense Passage Retrieval (DPR) model. It contains 21M passages from wikipedia along with their DPR embeddings. The wikipedia articles were split into multiple, disjoint text blocks of 100 words as passages.

Supported Tasks

More Information Needed

Languages

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Dataset Structure

We show detailed information for up to 5 configurations of the dataset.

Data Instances

psgs_w100.multiset.compressed

  • Size of downloaded dataset files: 67678.16 MB
  • Size of the generated dataset: 74786.45 MB
  • Total amount of disk used: 145204.14 MB

An example of 'train' looks as follows.

This example was too long and was cropped:

{
    "embeddings": "[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1....",
    "id": "0",
    "text": "his is the text of a dummy passag",
    "title": "Title of the article"
}

psgs_w100.multiset.exact

  • Size of downloaded dataset files: 67678.16 MB
  • Size of the generated dataset: 74786.45 MB
  • Total amount of disk used: 178700.81 MB

An example of 'train' looks as follows.

This example was too long and was cropped:

{
    "embeddings": "[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1....",
    "id": "0",
    "text": "his is the text of a dummy passag",
    "title": "Title of the article"
}

psgs_w100.multiset.no_index

  • Size of downloaded dataset files: 67678.16 MB
  • Size of the generated dataset: 74786.45 MB
  • Total amount of disk used: 142464.62 MB

An example of 'train' looks as follows.

This example was too long and was cropped:

{
    "embeddings": "[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1....",
    "id": "0",
    "text": "his is the text of a dummy passag",
    "title": "Title of the article"
}

psgs_w100.nq.compressed

  • Size of downloaded dataset files: 67678.16 MB
  • Size of the generated dataset: 74786.45 MB
  • Total amount of disk used: 145204.14 MB

An example of 'train' looks as follows.

This example was too long and was cropped:

{
    "embeddings": "[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1....",
    "id": "0",
    "text": "his is the text of a dummy passag",
    "title": "Title of the article"
}

psgs_w100.nq.exact

  • Size of downloaded dataset files: 67678.16 MB
  • Size of the generated dataset: 74786.45 MB
  • Total amount of disk used: 178700.81 MB

An example of 'train' looks as follows.

This example was too long and was cropped:

{
    "embeddings": "[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1....",
    "id": "0",
    "text": "his is the text of a dummy passag",
    "title": "Title of the article"
}

Data Fields

The data fields are the same among all splits.

psgs_w100.multiset.compressed

  • id: a string feature.
  • text: a string feature.
  • title: a string feature.
  • embeddings: a list of float32 features.

psgs_w100.multiset.exact

  • id: a string feature.
  • text: a string feature.
  • title: a string feature.
  • embeddings: a list of float32 features.

psgs_w100.multiset.no_index

  • id: a string feature.
  • text: a string feature.
  • title: a string feature.
  • embeddings: a list of float32 features.

psgs_w100.nq.compressed

  • id: a string feature.
  • text: a string feature.
  • title: a string feature.
  • embeddings: a list of float32 features.

psgs_w100.nq.exact

  • id: a string feature.
  • text: a string feature.
  • title: a string feature.
  • embeddings: a list of float32 features.

Data Splits Sample Size

name train
psgs_w100.multiset.compressed 21015300
psgs_w100.multiset.exact 21015300
psgs_w100.multiset.no_index 21015300
psgs_w100.nq.compressed 21015300
psgs_w100.nq.exact 21015300

Dataset Creation

Curation Rationale

More Information Needed

Source Data

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Annotations

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Personal and Sensitive Information

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Considerations for Using the Data

Social Impact of Dataset

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Discussion of Biases

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Other Known Limitations

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Additional Information

Dataset Curators

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Licensing Information

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Citation Information


@misc{karpukhin2020dense,
    title={Dense Passage Retrieval for Open-Domain Question Answering},
    author={Vladimir Karpukhin and Barlas Oğuz and Sewon Min and Patrick Lewis and Ledell Wu and Sergey Edunov and Danqi Chen and Wen-tau Yih},
    year={2020},
    eprint={2004.04906},
    archivePrefix={arXiv},
    primaryClass={cs.CL}
}

Contributions

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

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