AI Enabled- Information Retrival Engine (AI-IRE) in Legal Services: An Expert-Annotated NLP for Legal Judgements

The relationships between the law and fact, and the use of the facts to support a legal conclusion requires practice. This study introduces a technique called the "legal analysis of data extraction" which helps students/law practitioners to quickly assess a law article on the basis of the extracted attributes, and then apply their understanding in order to support a legal conclusion. To ease the processing of the law text data and retrieval of important information (entities) like names of Judges, appellants, respondents, judgment dates, etc. by utilizing NLP processes and ML techniques. This study demonstrates a novel approach of advanced information retrieval in the law articles leveraging natural language processing and machine learning techniques which are productized and used on live data as well. In this custom NER, aggregate accuracy of 95% is achieved using text classification followed by a regex fallback and flagging mechanism. This study consists of the following sections- a) Introduction b) Related Work c) About Dataset d) Methodology and approach e) Fallback mechanisms f) Results and Evaluations g) Conclusions & Future Scope with h) References.