Datasets:
annotations_creators:
- expert-generated
language_creators:
- found
- expert-generated
language:
- en
license: cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- summarization
- text2text-generation
task_ids:
- text-simplification
pretty_name: >-
LegalOps: A summarisation corpus of Federal and Supreme Court Opinions from
the Justia Portal
dataset_info:
- config_name: default
splits:
- name: train
num_bytes: 33980817
num_examples: 1022
download_size: 17759423
dataset_size: 33980817
- config_name: federal
features:
- name: fulltext
dtype: string
- name: summary
dtype: string
- name: tag
dtype: string
- name: url
dtype: string
- name: file_urls
sequence: string
- name: files
list:
- name: checksum
dtype: string
- name: path
dtype: string
- name: status
dtype: string
- name: url
dtype: string
- name: metadata
struct:
- name: court_id
dtype: string
- name: date
dtype: string
- name: number
dtype: string
- name: title
dtype: string
splits:
- name: train
num_bytes: 625693535
num_examples: 284011
download_size: 309803008
dataset_size: 625693535
- config_name: supreme
features:
- name: Syllabus
dtype: string
- name: Dissent
dtype: string
- name: Opinion
dtype: string
- name: summary
dtype: string
- name: tag
dtype: string
- name: url
dtype: string
- name: file_urls
sequence: string
- name: files
list:
- name: checksum
dtype: string
- name: path
dtype: string
- name: status
dtype: string
- name: url
dtype: string
- name: metadata
struct:
- name: Advocates
dtype: string
- name: Argued
dtype: string
- name: Decided
dtype: string
- name: Docket No.
dtype: string
- name: First Party
dtype: string
- name: Granted
dtype: string
- name: Juris Postponed
dtype: string
- name: Official Citation
dtype: string
- name: Reargued
dtype: string
- name: Second Party
dtype: string
- name: page
dtype: int64
- name: volume
dtype: int64
splits:
- name: train
num_bytes: 33894538
num_examples: 1022
download_size: 17739369
dataset_size: 33894538
configs:
- config_name: default
data_files:
- split: train
path: supreme/train-*
- config_name: federal
data_files:
- split: train
path: federal/train-*
- config_name: supreme
data_files:
- split: train
path: supreme/train-*
tags:
- legal
Dataset Card for LegalOps JustiaCorpus
Table of Contents
- Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage:
- Repository:
- Paper:
- Leaderboard:
- Point of Contact:
Dataset Summary
As the highest court in the nation, the U.S. Supreme Court has shaped the rights and freedoms of Americans since the Founding. Justia provides a free collection of all U.S. Supreme Court decisions from 1791 to the present.
https://law.justia.com/cases/federal/
Supported Tasks and Leaderboards
- Text Summarisation
Languages
- English
Dataset Structure
Data Instances
[More Information Needed]
Data Fields
[More Information Needed]
Data Splits
[More Information Needed]
Additional Data
Within this repository, two tarballs containing the full PDF documents for each dataset can be found in the corresponding federal/ and supreme/ datasets.
federal/federal_pdfs.tar.gzsupreme/supreme_pdfs.tar.gz
to extract these, clone this dataset repo, navigate to the directory and untar:
tar -xzvf federal_pdfs.tar.gz
The mapping between case and PDF is stored in the "files" field in the dataset.
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]
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
[More Information Needed]
Contributions
Thanks to @RobFirth for adding this dataset.