Named Entity Recognition in Indian court judgments
This work addresses the need for fine-grained named entity recognition in legal texts to support AI applications in the legal domain, but it is incremental as it focuses on a specific dataset and baseline.
The authors tackled the problem of named entity recognition in Indian court judgments by introducing a new annotated corpus of 46,545 legal named entities across 14 types and developing a baseline model for extraction.
Identification of named entities from legal texts is an essential building block for developing other legal Artificial Intelligence applications. Named Entities in legal texts are slightly different and more fine-grained than commonly used named entities like Person, Organization, Location etc. In this paper, we introduce a new corpus of 46545 annotated legal named entities mapped to 14 legal entity types. The Baseline model for extracting legal named entities from judgment text is also developed.