Datasets:
metadata
dataset_info:
features:
- name: text
dtype: string
- name: summary
dtype: string
splits:
- name: train
num_bytes: 1483542519.7144387
num_examples: 55993
- name: validation
num_bytes: 185439503.0714796
num_examples: 6999
- name: test
num_bytes: 185465998.21408162
num_examples: 7000
download_size: 904301529
dataset_size: 1854448020.9999998
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
task_categories:
- summarization
language:
- en
size_categories:
- 10K<n<100K
LegalSumm: A Comprehensive Legal Document Summarization Dataset
LegalSumm is a merged dataset combining three prominent legal document collections (GovReport, BillSum, and CaseSumm) to create a comprehensive resource for training and evaluating legal text summarisation models.
Dataset Composition
Total samples: 69,992 document-summary pairs
Sources:
- GovReport: 19,466 U.S. government reports (27.8%)
- BillSum: 23,455 U.S. Congressional bills (33.5%)
- CaseSumm: 27,071 U.S. Supreme Court opinions (38.7%)
Features
- text: Original legal document (full text)
- summary: Human-written summary of the document
Preprocessing
Documents have been standardized to ensure consistent formatting across different legal document types.
All samples have been randomly shuffled and split into training (80%), validation (10%), and test (10%) sets.