Abstract
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.
Originalsprog | Engelsk |
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Titel | Legal Knowledge and Information Systems - JURIX 2023 : 36th Annual Conference |
Redaktører | Giovanni Sileno, Jerry Spanakis, Gijs van Dijck |
Forlag | IOS Press BV |
Publikationsdato | 2023 |
Sider | 323-328 |
ISBN (Elektronisk) | 9781643684727 |
DOI | |
Status | Udgivet - 2023 |
Begivenhed | 36th International Conference on Legal Knowledge and Information Systems, JURIX 2023 - Maastricht, Holland Varighed: 18 dec. 2023 → 20 dec. 2023 |
Konference
Konference | 36th International Conference on Legal Knowledge and Information Systems, JURIX 2023 |
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Land/Område | Holland |
By | Maastricht |
Periode | 18/12/2023 → 20/12/2023 |
Navn | Frontiers in Artificial Intelligence and Applications |
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Vol/bind | 379 |
ISSN | 0922-6389 |
Bibliografisk note
Publisher Copyright:© 2023 The Authors.