metadata

dataset_info:
  features:
    - name: book
      dtype: string
    - name: document
      dtype: string
    - name: timestamp
      dtype: string
    - name: id
      dtype: string
    - name: hash
      dtype: string
  splits:
    - name: fr
      num_bytes: 151400300
      num_examples: 153005
  download_size: 64396801
  dataset_size: 151400300
configs:
  - config_name: default
    data_files:
      - split: fr
        path: data/fr-*
license: cc-by-4.0
task_categories:
  - question-answering
  - text-generation
  - table-question-answering
language:
  - fr
tags:
  - legal
  - droit
  - fiscalité
  - taxation
  - δεξιά
  - recht
  - derecho
pretty_name: The Laws, centralizing legal texts for better use

Dataset Description

Repository: https://huggingface.co/datasets/HFforLegal/laws
Leaderboard: N/A
Point of Contact: Louis Brulé Naudet

The Laws, centralizing legal texts for better use, a community Dataset.

The Laws Dataset is a comprehensive collection of legal texts from various countries, centralized in a common format. This dataset aims to improve the development of legal AI models by providing a standardized, easily accessible corpus of global legal documents.

Join us in our mission to make AI more accessible and understandable for the legal world, ensuring that the power of language models can be harnessed effectively and ethically in the pursuit of justice.

Objective

The primary objective of this dataset is to centralize laws from around the world in a common format, thereby facilitating:

Comparative legal studies
Development of multilingual legal AI models
Cross-jurisdictional legal research
Improvement of legal technology tools

By providing a standardized dataset of global legal texts, we aim to accelerate the development of AI models in the legal domain, enabling more accurate and comprehensive legal analysis across different jurisdictions.

Dataset Structure

The dataset is organized with the following columns:

book: The name or code of the law book (e.g., "Civil Code", "Penal Code")
document: The full text content of the legal document
timestamp: The timestamp of when the law was enacted or last updated
id: A identifier for each document
hash: A SHA-256 hash of the document for verification purposes

Easy-to-use script for hashing the document:

import hashlib
import datasets

def hash(
  text: str
) -> str:
    """
    Create or update the hash of the document content.

    This function takes a text input, converts it to a string, encodes it in UTF-8, 
    and then generates a SHA-256 hash of the encoded text.

    Parameters
    ----------
    text : str
        The text content to be hashed.

    Returns
    -------
    str
        The SHA-256 hash of the input text, represented as a hexadecimal string.
    """
    return hashlib.sha256(str(text).encode()).hexdigest()

dataset = dataset.map(lambda x: {"hash": hash(x["document"])})

Country-based Splits

The dataset uses country-based splits to organize legal documents from different jurisdictions. Each split is identified by the ISO 3166-1 alpha-2 code of the corresponding country.

ISO 3166-1 alpha-2 Codes

ISO 3166-1 alpha-2 codes are two-letter country codes defined in ISO 3166-1, part of the ISO 3166 standard published by the International Organization for Standardization (ISO).

Some examples of ISO 3166-1 alpha-2 codes:

France: fr
United States: us
United Kingdom: gb
Germany: de
Japan: jp
Brazil: br
Australia: au

Before submitting a new split, please make sure the proposed split fits within the ISO code for the related country.

Accessing Country-specific Data

To access legal documents for a specific country, you can use the country's ISO 3166-1 alpha-2 code as the split name when loading the dataset. Here's an example:

from datasets import load_dataset

# Load the entire dataset
dataset = load_dataset("HFforLegal/laws")

# Access the French legal documents
fr_dataset = dataset['fr']

Ethical Considerations

While this dataset provides a valuable resource for legal AI development, users should be aware of the following ethical considerations:

Privacy: Ensure that all personal information has been properly anonymized.
Bias: Be aware of potential biases in the source material and in the selection of included laws.
Currency: Laws change over time. Always verify that you're working with the most up-to-date version of a law for any real-world application.
Jurisdiction: Legal interpretations can vary by jurisdiction. AI models trained on this data should not be used as a substitute for professional legal advice.

Citing & Authors

If you use this dataset in your research, please use the following BibTeX entry.

@misc{HFforLegal2024,
  author =       {Louis Brulé Naudet},
  title =        {The Laws, centralizing legal texts for better use},
  year =         {2024}
  howpublished = {\url{https://huggingface.co/datasets/HFforLegal/laws}},
}

Feedback

If you have any feedback, please reach out at louisbrulenaudet@icloud.com.