---
annotations_creators:
- no-annotation
language:
- fr
language_creators:
- found
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: French Legal Cases Dataset
size_categories:
- n>1M
source_datasets:
- la-mousse/INCA-17-01-2025
- la-mousse/JADE-17-01-2025
- la-mousse/CASS-17-01-2025
- la-mousse/CAPP-17-01-2025
task_categories:
- text-generation
- text-classification
task_ids:
- language-modeling
- entity-linking-classification
- fact-checking
- intent-classification
- multi-label-classification
- multi-input-text-classification
- natural-language-inference
- semantic-similarity-classification
- sentiment-classification
- topic-classification 
- sentiment-analysis
- named-entity-recognition
- parsing
- extractive-qa
- open-domain-qa
- closed-domain-qa
- news-articles-summarization
- news-articles-headline-generation
- dialogue-modeling 
- dialogue-generation
- abstractive-qa
- closed-domain-qa
- keyword-spotting
- semantic-segmentation
- tabular-multi-class-classification
- tabular-multi-label-classification
- document-retrieval
- document-question-answering
paperswithcode_id: french-legal-cases
dataset_info:
  features:
  - name: id
    dtype: string
  - name: url
    dtype: string
  - name: case_number
    dtype: string
  - name: contenu
    dtype: string
  - name: sommaire
    dtype: string
  - name: sommaire_bis
    dtype: string
  - name: metadata
    dtype: string
  - name: dataset_source
    dtype: string
  - name: previous_text
    dtype: string
  - name: current_text
    dtype: string
  - name: next_text
    dtype: string
  - name: triplet_index
    dtype: int64
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---

# Dataset Card for French Legal Cases Dataset

## Dataset Description

- **Homepage:** [https://huggingface.co/datasets/la-mousse/combined-fe-caselaw](https://huggingface.co/datasets/la-mousse/combined-fe-caselaw)
- **Repository:** [https://huggingface.co/datasets/la-mousse/combined-fe-caselaw](https://huggingface.co/datasets/la-mousse/combined-fe-caselaw)
- **Paper:** N/A
- **Point of Contact:** [Your Contact Information]

### Dataset Summary

This dataset combines French legal cases from multiple sources (INCA, JADE, CASS, CAPP) into a unified format with overlapping text triplets. It includes decisions from various French courts, processed to facilitate natural language processing tasks.

### Supported Tasks and Leaderboards

- **Tasks:**
  - Text Generation
  - Legal Document Analysis
  - Text Classification
  - Language Modeling

### Languages

The dataset is monolingual (French).

## Dataset Structure

### Data Instances

Each instance contains:
- Document identifiers (id, url, case_number)
- Original text content (contenu)
- Summaries (sommaire, sommaire_bis)
- Metadata (JSON formatted string)
- Text triplets (previous_text, current_text, next_text)
- Position tracking (triplet_index, window_index)

Example:
```python
{
    'id': 'CASS12345',
    'url': 'https://...',
    'case_number': '12-34567',
    'contenu': 'Full text...',
    'sommaire': 'Summary...',
    'sommaire_bis': 'Additional summary...',
    'metadata': '{"date_decision": "2023-01-01", ...}',
    'dataset_source': 'CASS',
    'previous_text': 'Previous chunk...',
    'current_text': 'Current chunk...',
    'next_text': 'Next chunk...',
    'triplet_index': 0,
    'window_index': 0
}
```

### Data Fields

- `id`: Unique identifier
- `url`: Source URL
- `case_number`: Case reference number
- `contenu`: Full text content
- `sommaire`: Primary summary
- `sommaire_bis`: Secondary summary
- `metadata`: JSON string containing additional metadata
- `dataset_source`: Origin dataset (INCA/JADE/CASS/CAPP)
- `previous_text`: Previous text chunk
- `current_text`: Current text chunk
- `next_text`: Next text chunk
- `triplet_index`: Position in sequence of triplets
- `window_index`: Window number for long texts

### Data Splits

- Training split only

## Dataset Creation

### Curation Rationale

This dataset was created to provide a standardized format for French legal texts, with overlapping text chunks suitable for various NLP tasks.

### Source Data

#### Initial Data Collection and Normalization

- INCA: Court of Cassation decisions
- JADE: Administrative court decisions
- CASS: Court of Cassation decisions
- CAPP: Court of Appeal decisions

### Preprocessing

- Text chunking with 230-token chunks and 30-token overlap
- Sliding window approach for long texts
- Metadata preservation and standardization
- Token count verification
- JSON formatting for metadata

### Quality Control

- Token length verification
- Chunk coherence checks
- Metadata validation
- Error logging and handling

## Considerations for Using the Data

### Social Impact of Dataset

This dataset aims to improve access to and understanding of French legal decisions, potentially benefiting legal research and analysis.

### Discussion of Biases

The dataset may reflect inherent biases in the French legal system and case selection/publication processes.

### Other Known Limitations

- Limited to published decisions
- Varying detail levels across sources
- Potential OCR errors in source texts

## Additional Information

### Dataset Curators

La-Mousse

### Licensing Information

CC-BY-4.0

### Citation Information

```
@misc{french-legal-cases-2024,
    title={French Legal Cases Dataset},
    author={[Your Name]},
    year={2024},
    publisher={HuggingFace},
    url={https://huggingface.co/datasets/la-mousse/combined-fr-caselaw}
}
```

### Contributions

Thanks to [@huggingface](https://github.com/huggingface) for the dataset hosting and infrastructure.