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La-Mousse/JADE-17-01-2025

French Administrative Court Decisions Dataset (JADE) Dataset Description The French Administrative Court Decisions Dataset (JADE) is a comprehensive collection of judicial decisions from French administrative courts. This dataset contains decisions from various administrative jurisdictions, providing a valuable resource for legal research, analysis, and machine learning applications in the legal domain. Source Data The data is sourced from the… See the full description on the dataset page: https://huggingface.co/datasets/La-Mousse/JADE-17-01-2025.

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French Administrative Court Decisions Dataset (JADE)

Dataset Description

The French Administrative Court Decisions Dataset (JADE) is a comprehensive collection of judicial decisions from French administrative courts. This dataset contains decisions from various administrative jurisdictions, providing a valuable resource for legal research, analysis, and machine learning applications in the legal domain.

Source Data

The data is sourced from the official DILA (Direction de l'Information Légale et Administrative) platform through their open data initiative. The original data is available at: https://echanges.dila.gouv.fr/OPENDATA/JADE/

Content Description

Each entry in the dataset represents a single judicial decision and includes the following information:

  • —id: Unique identifier for the decision
  • —ancien_id: Previous identifier (if applicable)
  • —origine: Origin of the decision
  • —url: URL to the source document
  • —nature: Nature of the document
  • —titre: Title of the decision
  • —date_decision: Date when the decision was made
  • —juridiction: Court that made the decision
  • —numero: Case number
  • —formation: Court formation
  • —type_recours: Type of appeal
  • —publication_recueil: Publication details
  • —president: Presiding judge
  • —avocats: Lawyers involved
  • —rapporteur: Reporting judge
  • —commissaire_gouvernement: Government commissioner
  • —contenu: Full text content of the decision

Usage

This dataset can be loaded using the Hugging Face datasets library:

python
from datasets import load_dataset

dataset = load_dataset("username/dataset-name")