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2023 (English)In: Legal knowledge and information systems: Jurix 2023: the thirty-sixth annual conference, Maastricht, the Netherlands, 18–20 December 2023 / [ed] Giovanni Sileno; Jerry Spanakis; Gijs van Dijck, IOS Press, 2023, p. 323-328Conference paper, Published paper (Refereed)
Abstract [en]
Case law citation prediction, i.e., predicting what historical cases are relevant for your current case, can assist legal discovery and decision-making, but legal documents are long, and often only parts of them are relevant for a particular use case. We therefore reframe case law citation prediction as a paragraph-to-paragraph citation task, introduce a new dataset, and train and evaluate new models. We also evaluate our models qualitatively. Our resources provide a first step toward discovering citation patterns and modeling legal rules in EU law from precedent documents.
Place, publisher, year, edition, pages
IOS Press, 2023
Series
Frontiers in Artificial Intelligence and Applications, ISSN 0922-6389, E-ISSN 1879-8314 ; 379
Keywords
case law citation, legal dataset, legal rules, link prediction
National Category
Law and Society
Identifiers
urn:nbn:se:umu:diva-219980 (URN)10.3233/FAIA230982 (DOI)2-s2.0-85181165382 (Scopus ID)978-1-64368-472-7 (ISBN)978-1-64368-473-4 (ISBN)
Conference
36th International Conference on Legal Knowledge and Information Systems, JURIX 2023, Maastricht, The Netherlands, December 18-20, 2023
2024-01-252024-01-252024-01-25Bibliographically approved