IITP at AILA 2019: System Report for Artificial Intelligence for Legal Assistance Shared Task

TL;DR

This paper describes the system developed by IITP for the AILA 2019 shared task, focusing on automating legal assistance through NLP techniques to identify relevant cases and statutes, aiding judiciary processes.

Contribution

The paper introduces NLP-based approaches using BM25 and Doc2Vec for legal case and statute retrieval in the judicial domain, marking a step towards automation in Indian judiciary.

Findings

Achieved 3rd position in Task 1

Achieved modest position in Task 2

Demonstrated effectiveness of BM25 and Doc2Vec in legal retrieval

Abstract

In this article, we present a description of our systems as a part of our participation in the shared task namely Artificial Intelligence for Legal Assistance (AILA 2019). This is an integral event of Forum for Information Retrieval Evaluation-2019. The outcomes of this track would be helpful for the automation of the working process of the Indian Judiciary System. The manual working procedures and documentation at any level (from lower to higher court) of the judiciary system are very complex in nature. The systems produced as a part of this track would assist the law practitioners. It would be helpful for common men too. This kind of track also opens the path of research of Natural Language Processing (NLP) in the judicial domain. This track defined two problems such as Task 1: Identifying relevant prior cases for a given situation and Task 2: Identifying the most relevant statutes for a given situation. We tackled both of them. Our proposed approaches are based on BM25 and Doc2Vec. As per the results declared by the task organizers, we are in 3rd and a modest position in Task 1 and Task 2 respectively.