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Re-Framing Case Law Citation Prediction from a Paragraph Perspective
Henrik Palmer Olsen, Nicolas Garneau, Yannis Panagis, Johan Lindholm, Anders Søgaard
323 - 328
10.3233/FAIA230982
Research Article
Frontiers in Artificial Intelligence and Applications
Volume 379: Legal Knowledge and Information Systems
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.

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