Previous Opinions is All You Need - Legal Information Retrieval System

Maciej Osowski, Katarzyna Lorenc, Pawel Drozda, Rafal Scherer, Konrad Szalapak, Kajetan Komar-Komarowski, Julian Szymanski, Andrzej Sobecki

Abstract: We present a system for retrieving the most relevant legal opinions to a given legal case or question. To this end, we checked several state-of-the-art neural language models. As a training and testing data, we use tens of thousands of legal cases as question-opinion pairs. Text data has been subjected to advanced pre-processing adapted to the specifics of the legal domain. We empirically chose the BERT-based HerBERT model to perform the best in the considered scenario.