Re-Framing Case Law Citation Prediction from a Paragraph Perspective

Henrik Palmer Olsen*, Nicolas Garneau, Yannis Panagis, Johan Lindholm, Anders Søgaard

*Corresponding author af dette arbejde

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningpeer review

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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.

OriginalsprogEngelsk
TitelLegal Knowledge and Information Systems - JURIX 2023 : 36th Annual Conference
RedaktørerGiovanni Sileno, Jerry Spanakis, Gijs van Dijck
ForlagIOS Press BV
Publikationsdato2023
Sider323-328
ISBN (Elektronisk)9781643684727
DOI
StatusUdgivet - 2023
Begivenhed36th International Conference on Legal Knowledge and Information Systems, JURIX 2023 - Maastricht, Holland
Varighed: 18 dec. 202320 dec. 2023

Konference

Konference36th International Conference on Legal Knowledge and Information Systems, JURIX 2023
Land/OmrådeHolland
ByMaastricht
Periode18/12/202320/12/2023
NavnFrontiers in Artificial Intelligence and Applications
Vol/bind379
ISSN0922-6389

Bibliografisk note

Publisher Copyright:
© 2023 The Authors.

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