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Datasets:
wiki_dpr

Tasks:
Fill-Mask
Text Generation
Sub-tasks:
language-modeling
masked-language-modeling
Languages:
English
Multilinguality:
multilingual
Size Categories:
10M<n<100M
Language Creators:
crowdsourced
Annotations Creators:
no-annotation
Source Datasets:
original
ArXiv:
Tags:
text-search
License:
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metadata
annotations_creators:
  - no-annotation
language_creators:
  - crowdsourced
language:
  - en
license: cc-by-nc-4.0
multilinguality:
  - multilingual
size_categories:
  - 10M<n<100M
source_datasets:
  - original
task_categories:
  - fill-mask
  - text-generation
task_ids:
  - language-modeling
  - masked-language-modeling
pretty_name: Wiki-DPR
tags:
  - text-search
dataset_info:
  - config_name: psgs_w100.nq.exact
    features:
      - name: id
        dtype: string
      - name: text
        dtype: string
      - name: title
        dtype: string
      - name: embeddings
        sequence: float32
    splits:
      - name: train
        num_bytes: 78419248156
        num_examples: 21015300
    download_size: 85288677114
    dataset_size: 78419248156
  - config_name: psgs_w100.nq.compressed
    features:
      - name: id
        dtype: string
      - name: text
        dtype: string
      - name: title
        dtype: string
      - name: embeddings
        sequence: float32
    splits:
      - name: train
        num_bytes: 78419248156
        num_examples: 21015300
    download_size: 85288677114
    dataset_size: 78419248156
  - config_name: psgs_w100.nq.no_index
    features:
      - name: id
        dtype: string
      - name: text
        dtype: string
      - name: title
        dtype: string
      - name: embeddings
        sequence: float32
    splits:
      - name: train
        num_bytes: 78419248156
        num_examples: 21015300
    download_size: 85288677114
    dataset_size: 78419248156
  - config_name: psgs_w100.multiset.exact
    features:
      - name: id
        dtype: string
      - name: text
        dtype: string
      - name: title
        dtype: string
      - name: embeddings
        sequence: float32
    splits:
      - name: train
        num_bytes: 78419248156
        num_examples: 21015300
    download_size: 85289275855
    dataset_size: 78419248156
  - config_name: psgs_w100.multiset.compressed
    features:
      - name: id
        dtype: string
      - name: text
        dtype: string
      - name: title
        dtype: string
      - name: embeddings
        sequence: float32
    splits:
      - name: train
        num_bytes: 78419248156
        num_examples: 21015300
    download_size: 85289275855
    dataset_size: 78419248156
  - config_name: psgs_w100.multiset.no_index
    features:
      - name: id
        dtype: string
      - name: text
        dtype: string
      - name: title
        dtype: string
      - name: embeddings
        sequence: float32
    splits:
      - name: train
        num_bytes: 78419248156
        num_examples: 21015300
    download_size: 85289275855
    dataset_size: 78419248156

Dataset Card for "wiki_dpr"

Table of Contents

Dataset Description

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.

The wikipedia dump is the one from Dec. 20, 2018.

There are two types of DPR embeddings based on two different models:

  • nq: the model is trained on the Natural Questions dataset
  • multiset: the model is trained on multiple datasets

Additionally, a FAISS index can be created from the embeddings:

  • exact: with an exact FAISS index (high RAM usage)
  • compressed: with a compressed FAISS index (approximate, but lower RAM usage)
  • no_index: without FAISS index

Finally, there is the possibility of generating the dataset without the embeddings:

  • no_embeddings

Supported Tasks and Leaderboards

More Information Needed

Languages

More Information Needed

Dataset Structure

Data Instances

Each instance contains a paragraph of at most 100 words, as well as the title of the wikipedia page it comes from, and the DPR embedding (a 768-d vector).

psgs_w100.multiset.compressed

  • Size of downloaded dataset files: 70.97 GB
  • Size of the generated dataset: 78.42 GB
  • Total amount of disk used: 163.71 GB

An example of 'train' looks as follows.

This example was too long and was cropped:

{'id': '1',
 'text': 'Aaron Aaron ( or ; "Ah盲r么n") is a prophet, high priest, and the brother of Moses in the Abrahamic religions. Knowledge of Aaron, along with his brother Moses, comes exclusively from religious texts, such as the Bible and Quran. The Hebrew Bible relates that, unlike Moses, who grew up in the Egyptian royal court, Aaron and his elder sister Miriam remained with their kinsmen in the eastern border-land of Egypt (Goshen). When Moses first confronted the Egyptian king about the Israelites, Aaron served as his brother\'s spokesman ("prophet") to the Pharaoh. Part of the Law (Torah) that Moses received from'],
 'title': 'Aaron',
 'embeddings': [-0.07233893871307373,
   0.48035329580307007,
   0.18650995194911957,
   -0.5287084579467773,
   -0.37329429388046265,
   0.37622880935668945,
   0.25524479150772095,
   ...
   -0.336689829826355,
   0.6313082575798035,
   -0.7025573253631592]}

psgs_w100.multiset.exact

  • Size of downloaded dataset files: 85.23 GB
  • Size of the generated dataset: 78.42 GB
  • Total amount of disk used: 163.71 GB

An example of 'train' looks as follows.

This example was too long and was cropped:

{'id': '1',
 'text': 'Aaron Aaron ( or ; "Ah盲r么n") is a prophet, high priest, and the brother of Moses in the Abrahamic religions. Knowledge of Aaron, along with his brother Moses, comes exclusively from religious texts, such as the Bible and Quran. The Hebrew Bible relates that, unlike Moses, who grew up in the Egyptian royal court, Aaron and his elder sister Miriam remained with their kinsmen in the eastern border-land of Egypt (Goshen). When Moses first confronted the Egyptian king about the Israelites, Aaron served as his brother\'s spokesman ("prophet") to the Pharaoh. Part of the Law (Torah) that Moses received from'],
 'title': 'Aaron',
 'embeddings': [-0.07233893871307373,
   0.48035329580307007,
   0.18650995194911957,
   -0.5287084579467773,
   -0.37329429388046265,
   0.37622880935668945,
   0.25524479150772095,
   ...
   -0.336689829826355,
   0.6313082575798035,
   -0.7025573253631592]}

psgs_w100.multiset.no_index

  • Size of downloaded dataset files: 85.23 GB
  • Size of the generated dataset: 78.42 GB
  • Total amount of disk used: 163.71 GB

An example of 'train' looks as follows.

This example was too long and was cropped:

{'id': '1',
 'text': 'Aaron Aaron ( or ; "Ah盲r么n") is a prophet, high priest, and the brother of Moses in the Abrahamic religions. Knowledge of Aaron, along with his brother Moses, comes exclusively from religious texts, such as the Bible and Quran. The Hebrew Bible relates that, unlike Moses, who grew up in the Egyptian royal court, Aaron and his elder sister Miriam remained with their kinsmen in the eastern border-land of Egypt (Goshen). When Moses first confronted the Egyptian king about the Israelites, Aaron served as his brother\'s spokesman ("prophet") to the Pharaoh. Part of the Law (Torah) that Moses received from'],
 'title': 'Aaron',
 'embeddings': [-0.07233893871307373,
   0.48035329580307007,
   0.18650995194911957,
   -0.5287084579467773,
   -0.37329429388046265,
   0.37622880935668945,
   0.25524479150772095,
   ...
   -0.336689829826355,
   0.6313082575798035,
   -0.7025573253631592]}

psgs_w100.nq.compressed

  • Size of downloaded dataset files: 85.23 GB
  • Size of the generated dataset: 78.42 GB
  • Total amount of disk used: 163.71 GB

An example of 'train' looks as follows.

This example was too long and was cropped:

{'id': '1',
 'text': 'Aaron Aaron ( or ; "Ah盲r么n") is a prophet, high priest, and the brother of Moses in the Abrahamic religions. Knowledge of Aaron, along with his brother Moses, comes exclusively from religious texts, such as the Bible and Quran. The Hebrew Bible relates that, unlike Moses, who grew up in the Egyptian royal court, Aaron and his elder sister Miriam remained with their kinsmen in the eastern border-land of Egypt (Goshen). When Moses first confronted the Egyptian king about the Israelites, Aaron served as his brother\'s spokesman ("prophet") to the Pharaoh. Part of the Law (Torah) that Moses received from'],
 'title': 'Aaron',
 'embeddings': [0.013342111371457577,
   0.582173764705658,
   -0.31309744715690613,
   -0.6991612911224365,
   -0.5583199858665466,
   0.5187504887580872,
   0.7152731418609619,
   ...
   -0.5385938286781311,
   0.8093984127044678,
   -0.4741983711719513]}

psgs_w100.nq.exact

  • Size of downloaded dataset files: 85.23 GB
  • Size of the generated dataset: 78.42 GB
  • Total amount of disk used: 163.71 GB

An example of 'train' looks as follows.

This example was too long and was cropped:

{'id': '1',
 'text': 'Aaron Aaron ( or ; "Ah盲r么n") is a prophet, high priest, and the brother of Moses in the Abrahamic religions. Knowledge of Aaron, along with his brother Moses, comes exclusively from religious texts, such as the Bible and Quran. The Hebrew Bible relates that, unlike Moses, who grew up in the Egyptian royal court, Aaron and his elder sister Miriam remained with their kinsmen in the eastern border-land of Egypt (Goshen). When Moses first confronted the Egyptian king about the Israelites, Aaron served as his brother\'s spokesman ("prophet") to the Pharaoh. Part of the Law (Torah) that Moses received from'],
 'title': 'Aaron',
 'embeddings': [0.013342111371457577,
   0.582173764705658,
   -0.31309744715690613,
   -0.6991612911224365,
   -0.5583199858665466,
   0.5187504887580872,
   0.7152731418609619,
   ...
   -0.5385938286781311,
   0.8093984127044678,
   -0.4741983711719513]}

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

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

Initial Data Collection and Normalization

More Information Needed

Who are the source language producers?

More Information Needed

Annotations

Annotation process

More Information Needed

Who are the annotators?

More Information Needed

Personal and Sensitive Information

More Information Needed

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

DPR is CC-BY-NC 4.0 licensed: https://github.com/facebookresearch/DPR/blob/main/LICENSE

Citation Information 

@inproceedings{karpukhin-etal-2020-dense,
    title = "Dense Passage Retrieval for Open-Domain Question Answering",
    author = "Karpukhin, Vladimir and Oguz, Barlas and Min, Sewon and Lewis, Patrick and Wu, Ledell and Edunov, Sergey and Chen, Danqi and Yih, Wen-tau",
    booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)",
    month = nov,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/2020.emnlp-main.550",
    doi = "10.18653/v1/2020.emnlp-main.550",
    pages = "6769--6781",
}

Contributions

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