Dataset Card for "billsum"

Dataset Summary

BillSum, summarization of US Congressional and California state bills.

There are several features:

• text: bill text.
• summary: summary of the bills.
• title: title of the bills. features for us bills. ca bills does not have.
• text_len: number of chars in text.
• sum_len: number of chars in summary.

Supported Tasks and Leaderboards

More Information Needed

Languages

More Information Needed

Dataset Structure

Data Instances

default

• Size of downloaded dataset files: 67.26 MB
• Size of the generated dataset: 272.42 MB
• Total amount of disk used: 339.68 MB

An example of 'train' looks as follows.

{
    "summary": "some summary",
    "text": "some text.",
    "title": "An act to amend Section xxx."
}

Data Fields

The data fields are the same among all splits.

default

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

Data Splits

name	train	ca_test	test
default	18949	1237	3269

Dataset Creation

Curation Rationale

More Information Needed

Source Data

Initial Data Collection and Normalization

The data consists of three parts: US training bills, US test bills and California test bills. The US bills were collected from the Govinfo service provided by the United States Government Publishing Office (GPO) under CC0-1.0 license. The California, bills from the 2015-2016 session are available from the legislature’s website .

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

More Information Needed

Citation Information

@misc{kornilova2019billsum,
    title={BillSum: A Corpus for Automatic Summarization of US Legislation},
    author={Anastassia Kornilova and Vlad Eidelman},
    year={2019},
    eprint={1910.00523},
    archivePrefix={arXiv},
    primaryClass={cs.CL}
}

Contributions

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