Legal text analytics resources
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This repository serves as a curated collection of resources, methods, and tools for Legal Text Analytics. It targets researchers, developers, and legal professionals interested in applying Natural Language Processing (NLP) techniques to legal documents, aiming to streamline analysis, extract insights, and improve efficiency in the legal domain.
How It Works
The project organizes a wide array of information across various categories, including tasks, methods, libraries, datasets, LLMs, annotation schemes, tools, research groups, and tutorials. It leverages established NLP libraries and frameworks, alongside specialized legal NLP tools and datasets, to facilitate tasks like information extraction, classification, summarization, and question answering within legal texts. The approach emphasizes both traditional NLP methods and cutting-edge deep learning models, providing a comprehensive overview of the field.
Quick Start & Requirements
This is a curated list, not a runnable software package. To utilize the listed libraries and datasets, users will need to follow the installation and usage instructions for each individual resource. Prerequisites will vary widely depending on the chosen library or dataset, potentially including Python, specific NLP libraries (e.g., Spacy, Hugging Face Transformers), and significant data storage for large datasets.
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Maintenance & Community
The project encourages contributions via pull requests and discussions through issues. It is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Licensing & Compatibility
The repository itself is licensed under CC BY-SA 4.0. Individual resources listed within may have different licenses, requiring users to check each component for compatibility with commercial or closed-source applications.
Limitations & Caveats
As a curated list, this repository does not provide a unified software interface or direct execution capabilities. Users must independently integrate and manage the various tools and datasets mentioned. The rapid evolution of the legal tech field means some resources may become outdated.
9 months ago
Inactive