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.
Legal NER, Legal-BERT, NLP, Legal Documents, Streamlit
IRE Journals:
Surendran S, Pragadesh Kumar G S, Preetham M V, Sushanthi "Named Entity Recognition On Legal Documents Using Legal Bert" Iconic Research And Engineering Journals Volume 9 Issue 10 2026 Page 621-623 https://doi.org/10.64388/IREV9I10-1716069
IEEE:
Surendran S, Pragadesh Kumar G S, Preetham M V, Sushanthi
"Named Entity Recognition On Legal Documents Using Legal Bert" Iconic Research And Engineering Journals, 9(10) https://doi.org/10.64388/IREV9I10-1716069