Named Entity Recognition On Legal Documents Using Legal Bert

@article{1716069,
      author = {Surendran S, Pragadesh Kumar G S, Preetham M V, Sushanthi},
      title = {Named Entity Recognition On Legal Documents Using Legal Bert},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {9},
      number = {10},
      pages = {621-623},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1716069.pdf},
      abstract = {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.},
      keywords = {Legal NER, Legal-BERT, NLP, Legal Documents, Streamlit},
      month = {April},
      doi = {https://doi.org/10.64388/IREV9I10-1716069}
  }