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# 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:
1. **Automatic Text Summarization:** Evaluating algorithms for generating or refining summaries.
2. **Document Classification:** Identifying the type or category of legal documents.
3. **Retrieval-Augmented Generation (RAG):** Improving legal text retrieval and contextual generation.
4. **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:
```python
from datasets import load_dataset
dataset = load_dataset("your-username/stj-legal-documents")
print(dataset)
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