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.
Authors
- Maciej Osowski,
- Katarzyna Lorenc,
- Paweł Drozda,
- Rafał Scherer,
- Konrad Szałapak,
- Kajetan Komar-Komarowski,
- dr hab. inż. Julian Szymański link open in new tab ,
- dr inż. Andrzej Sobecki link open in new tab
Additional information
- DOI
- Digital Object Identifier link open in new tab 10.1007/978-3-031-41774-0
- Category
- Publikacja monograficzna
- Type
- rozdział, artykuł w książce - dziele zbiorowym /podręczniku w języku o zasięgu międzynarodowym
- Language
- angielski
- Publication year
- 2023
