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