Project demonstrates an automated system extracting entities from legal documents, suggesting improved efficiency in document analysis.
Legal documents are complex and unstructured, making manual extraction of important entities inefficient and error-prone. This project presents an automated Named Entity Recognition (NER) system for legal documents using a fine-tuned Legal-BERT model. The system identifies key entities such as persons, organizations, dates, locations, and legal provisions. A Streamlit-based web application enables users to upload documents and view extracted entities interactively. The proposed solution reduces manual effort and improves the efficiency of legal document analysis.
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S et al. (2026) studied this question.
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