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Natural Language Processing (NLP) and Information Retrieval (IR) in thejudicial domain is an essential task. With the advent of availabilitydomain-specific data in electronic form and aid of different Artificialintelligence (AI) technologies, automated language processing becomes morecomfortable, and hence it becomes feasible for researchers and developers toprovide various automated tools to the legal community to reduce human burden.The Competition on Legal Information Extraction/Entailment (COLIEE-2019) run inassociation with the International Conference on Artificial Intelligence andLaw (ICAIL)-2019 has come up with few challenging tasks. The shared definedfour sub-tasks (i.e. Task1, Task2, Task3 and Task4), which will be able toprovide few automated systems to the judicial system. The paper presents ourworking note on the experiments carried out as a part of our participation inall the sub-tasks defined in this shared task. We make use of differentInformation Retrieval(IR) and deep learning based approaches to tackle theseproblems. We obtain encouraging results in all these four sub-tasks.

IITP@COLIEE 2019: Legal Information Retrieval using BM25 and BERT