Dataset: Legal Documents from STJ for Jurimetrics Research
Dataset Overview
This dataset contains legal documents from the Superior Tribunal de Justiça (STJ), designed for research in jurimetrics, automatic text summarization, and retrieval-augmented generation (RAG). The dataset focuses on the challenges posed by hierarchical structures, legal vocabulary, ambiguity, and citations in legal texts.
Contents
The dataset includes:
- Ementas (Summaries): Concise summaries of legal decisions.
- Document Types: Classified by resource types (e.g., appeals, decisions, opinions).
- Tokens Count: Pre-calculated token counts for analyzing document lengths.
- Metadata: Additional attributes such as document dates, involved parties, and court sections.
Dataset Features
| Feature Name | Description | Data Type |
|---|---|---|
id |
Unique identifier for the document. | String |
type_of_resource |
Type of the legal document (e.g., appeal). | String |
ementa |
Summary of the legal decision. | String |
full_text |
Full content of the legal decision. | String |
token_count |
Number of tokens in the document summary. | Integer |
date |
Date of the decision (YYYY-MM-DD). | Date |
metadata |
Additional information (parties, sections). | JSON Object |
Dataset Usage
This dataset can be used for tasks such as:
- Automatic Text Summarization: Evaluating algorithms for generating or refining summaries.
- Document Classification: Identifying the type or category of legal documents.
- Retrieval-Augmented Generation (RAG): Improving legal text retrieval and contextual generation.
- Token Analysis: Studying the distribution and challenges of token lengths in legal summaries.
Data Source
The data is sourced from publicly available legal decisions on the Superior Tribunal de Justiça (STJ). Preprocessing steps were applied to ensure data consistency and usability for machine learning models.
Note: Ensure compliance with ethical and legal considerations regarding the use of public legal documents.
How to Load the Dataset
Using the Hugging Face datasets library:
from datasets import load_dataset
dataset = load_dataset("your-username/stj-legal-documents")
print(dataset)