Dataset:
bookcorpusopen

Languages: en

Dataset Card for "bookcorpusopen"

Dataset Summary

Books are a rich source of both fine-grained information, how a character, an object or a scene looks like, as well as high-level semantics, what someone is thinking, feeling and how these states evolve through a story. This version of bookcorpus has 17868 dataset items (books). Each item contains two fields: title and text. The title is the name of the book (just the file name) while text contains unprocessed book text. The bookcorpus has been prepared by Shawn Presser and is generously hosted by The-Eye. The-Eye is a non-profit, community driven platform dedicated to the archiving and long-term preservation of any and all data including but by no means limited to... websites, books, games, software, video, audio, other digital-obscura and ideas.

Supported Tasks and Leaderboards

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Languages

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Dataset Structure

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

Data Instances

plain_text

  • Size of downloaded dataset files: 2292.89 MB
  • Size of the generated dataset: 6336.36 MB
  • Total amount of disk used: 8629.25 MB

An example of 'train' looks as follows.

This example was too long and was cropped:

{
    "text": "\"\\n\\nzONE\\n\\n## The end and the beginning\\n\\nby\\n\\nPhilip F. Blood\\n\\nSMASHWORDS EDITION\\n\\nVersion 3.55\\n\\nPUBLISHED BY:\\n\\nPhi...",
    "title": "zone-the-end-and-the-beginning.epub.txt"
}

Data Fields

The data fields are the same among all splits.

plain_text

  • title: a string feature.
  • text: a string feature.

Data Splits

name train
plain_text 17868

Dataset Creation

Curation Rationale

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Source Data

Initial Data Collection and Normalization

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Who are the source language producers?

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Annotations

Annotation process

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Who are the annotators?

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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

@InProceedings{Zhu_2015_ICCV,
    title = {Aligning Books and Movies: Towards Story-Like Visual Explanations by Watching Movies and Reading Books},
    author = {Zhu, Yukun and Kiros, Ryan and Zemel, Rich and Salakhutdinov, Ruslan and Urtasun, Raquel and Torralba, Antonio and Fidler, Sanja},
    booktitle = {The IEEE International Conference on Computer Vision (ICCV)},
    month = {December},
    year = {2015}
}

Contributions

Thanks to @vblagoje for adding this dataset.

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