The successful application of argument mining in the legal domain can dramatically impact many disciplines related to law. For this purpose, we present Demosthenes, a novel corpus for argument mining in legal documents, composed of 40 decisions of the Court of Justice of the European Union on matters of fiscal state aid. The annotation specifies three hierarchical levels of information: the argumentative elements, their types, and their argument schemes. In our experimental evaluation, we address 4 different classification tasks, combining advanced language models and traditional classifiers.

Detecting Arguments in CJEU Decisions on Fiscal State Aid

Grundler Giulia
Co-primo
;
Santin Piera
Co-primo
;
Galassi Andrea
;
Galli Federico;Godano Francesco;Lagioia Francesca
;
Palmieri Elena;Ruggeri Federico;Sartor Giovanni;Torroni Paolo
2022

Abstract

The successful application of argument mining in the legal domain can dramatically impact many disciplines related to law. For this purpose, we present Demosthenes, a novel corpus for argument mining in legal documents, composed of 40 decisions of the Court of Justice of the European Union on matters of fiscal state aid. The annotation specifies three hierarchical levels of information: the argumentative elements, their types, and their argument schemes. In our experimental evaluation, we address 4 different classification tasks, combining advanced language models and traditional classifiers.
Proceedings of the 9th Workshop on Argument Mining
143
157
Grundler Giulia , Santin Piera , Galassi Andrea , Galli Federico , Godano Francesco , Lagioia Francesca , Palmieri Elena , Ruggeri Federico , Sartor Giovanni , Torroni Paolo
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/897007
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