license: mit
task_categories:
- fill-mask
- text-generation
language:
- en
tags:
- art
pretty_name: Fiction 1B
size_categories:
- 1B<n<10B
Fiction 1B
More than 1B words of narrative fiction sourced from Project Gutenberg, AO3, and Internet Archive.
Dataset Details
Dataset Description
This contains the text of roughly 20,000 works of narrative fiction from the above sources. From the original full texts, a genre classifier was applied at the paragraph level to remove license text, metadata, and other content suspected not to be narrative prose.
Misc
- Curated by: Shawn Rushefsky - 🤗 | github
- Funded by: Salad Technologies
- Language(s) (NLP): English
- License: MIT
Dataset Sources
More information about specific source documents can be found in doc_index.csv
- Project Gutenberg: 76.4%
- Archive of our Own (AO3): 22.2%
- Internet Archive: 1.4%
Uses
The dataset is intended to be used for training language models on the syntactic patterns of narrative fiction.
Direct Use
- Fill-Mask training
- Text Generation training
- Research
Out-of-Scope Use
- Applications outside of fiction
Dataset Structure
data.zip contains a CSV file where each row contains the source, a document ID, paragraph index, approximately 500 words of text, and a word count for that section.
Dataset Creation
Curation Rationale
While much of this content is already present in extremely large web-scaped datasets, there is a scarcity of more approachable medium-sized datasets that focus specifically on narrative fiction. Datasets such as FineWeb with trillions of tokens are not practical for the average developer to work with.
Source Data
Data Collection and Processing
Project Gutenberg
Project Gutenberg hosts a catalog CSV that includes metadata such as title, author, and subjects. I filtered based on the presence of fiction-related keywords in the Subjects column, and used a python script to bulk download texts.
fiction_keywords = [
'fiction', 'novel', 'stories', 'tale', 'adventure',
'mystery', 'romance', 'fantasy', 'horror', 'detective',
'science fiction', 'historical fiction', 'western',
'thriller', 'suspense'
]
AO3
For AO3, I used the ao3-api python package to gradually paginate through the archive, filtering to English language work with at least 15,000 words but fewer than 500,000, sorted by “Kudos”, a measure of user favor.
Internet Archive
For Internet Archive, I used their search endpoint, and a significant amount of keyword filtering. Ultimately I did not get much content from this source due to licensing restrictions.
Who are the source data producers?
Professional and amateur writers of long-form narrative fiction in the English language over the last few hundred years.
Personal and Sensitive Information
This dataset contains only works of fiction.
Bias, Risks, and Limitations
The source text comes from a diverse set of english-language narrative fiction spanning hundreds of years of authorship, and may include subject matter and phrasing that offend. The age of much of the material from Project Gutenberg is such that white men from before the civil rights movement are vastly disproportionately represented as authors. Additionally, contemporary commercial fiction is nearly all but excluded due to licensing restrictions.
Recommendations
Use at your own risk.