--- language: - fr - en license: cc-by-4.0 task_categories: - question-answering - text-generation - table-question-answering pretty_name: The case-law, centralizing legal decisions for better use configs: - config_name: default data_files: - split: us path: data/us-* tags: - legal - droit - fiscalité - taxation - δεξιά - recht - derecho dataset_info: features: - name: id dtype: string - name: title dtype: string - name: citation dtype: string - name: docket_number dtype: string - name: state dtype: string - name: issuer dtype: string - name: document dtype: string - name: hash dtype: string - name: timestamp dtype: string splits: - name: us num_bytes: 9138869838 num_examples: 541371 download_size: 4597435136 dataset_size: 9138869838 --- ## Dataset Description - **Repository:** https://huggingface.co/datasets/HFforLegal/case-law - **Leaderboard:** N/A - **Point of Contact:** [Louis Brulé Naudet](mailto:louisbrulenaudet@icloud.com) # The Case-law, centralizing legal decisions for better use, a community Dataset. The Case-law Dataset is a comprehensive collection of legal decisons 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: 1. Comparative legal studies 2. Development of multilingual legal AI models 3. Cross-jurisdictional legal research 4. 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: - `id`: A unique identifier for each document - `title`: The title of the legal document - `citation`: The citation information for the document, referencing legal precedents or sources - `docket_number`: The docket number associated with the legal case or document - `state`: The state or jurisdiction related to the document (e.g., "Maine"...) - `issuer`: The entity or authority that issued the document - `document`: The full text content of the legal document - `hash`: A SHA-256 hash of the document for verification purposes, ensuring data integrity - `timestamp`: The timestamp indicating when the document was created, enacted, or last updated Easy-to-use script for hashing the `document`: ```python 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: ```python from datasets import load_dataset # Load the entire dataset dataset = load_dataset("HFforLegal/case-law") # Access the French legal decisions 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. ```BibTeX @misc{HFforLegal2024, author = {Louis Brulé Naudet, Timothy Dolan}, title = {The case-law, centralizing legal decisions for better use}, year = {2024} howpublished = {\url{https://huggingface.co/datasets/HFforLegal/case-law}}, } ``` ## Feedback If you have any feedback, please reach out at [louisbrulenaudet@icloud.com](mailto:louisbrulenaudet@icloud.com).