Datasets:
Languages:
English
Multilinguality:
monolingual
Size Categories:
10M<n<100M
Language Creators:
found
Annotations Creators:
no-annotation
Source Datasets:
original
ArXiv:
Tags:
License:
metadata
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license:
- unknown
multilinguality:
- monolingual
pretty_name: BookCorpus
size_categories:
- 10M<n<100M
source_datasets:
- original
task_categories:
- text-generation
- fill-mask
task_ids:
- language-modeling
- masked-language-modeling
paperswithcode_id: bookcorpus
Dataset Card for BookCorpus
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: https://yknzhu.wixsite.com/mbweb
- Repository: More Information Needed
- Paper: More Information Needed
- Point of Contact: More Information Needed
- Size of downloaded dataset files: 1124.87 MB
- Size of the generated dataset: 4629.00 MB
- Total amount of disk used: 5753.87 MB
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 work aims to align books to their movie releases in order to providerich descriptive explanations for visual content that go semantically farbeyond the captions available in current datasets.
Supported Tasks and Leaderboards
Languages
Dataset Structure
Data Instances
plain_text
- Size of downloaded dataset files: 1124.87 MB
- Size of the generated dataset: 4629.00 MB
- Total amount of disk used: 5753.87 MB
An example of 'train' looks as follows.
{
"text": "But I traded all my life for some lovin' and some gold"
}
Data Fields
The data fields are the same among all splits.
plain_text
text
: astring
feature.
Data Splits
name | train |
---|---|
plain_text | 74004228 |
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
@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 @lewtun, @richarddwang, @lhoestq, @thomwolf for adding this dataset.