Archivio Istituzionale della RicercaThe extraction of conceptual and terminological knowledge from legal documents is a crucial task in the legal domain. In this paper we propose ASKE (Automated System for Knowledge Extraction), a system for the extraction of knowledge that exploits contextual embedding and zero-shot learning techniques in order to retrieve relevant conceptual and terminological knowledge from legal documents. Moreover, in the paper we discuss some preliminary experimental results on a real dataset consisting of a corpus of Illinois State Courts’ decisions taken from the Caselaw Access Project (CAP).
Context-Aware Knowledge Extraction from Legal Documents Through Zero-Shot Classification / Ferrara, A.; Picascia, S.; Riva, D.. - 13650:(2022), pp. 81-90. (Intervento presentato al convegno Advances in Conceptual Modeling ER 2022 Workshops, CMLS, EmpER, and JUSMODDigital Law and Conceptual Modeling, JUSMOD 2022 held at 41st International Conference on Conceptual Modeling, ER 2022 tenutosi a Hyderabad (IND) nel October 17–20, 2022) [10.1007/978-3-031-22036-4_8].
Context-Aware Knowledge Extraction from Legal Documents Through Zero-Shot Classification
Riva D.
2022
Abstract
The extraction of conceptual and terminological knowledge from legal documents is a crucial task in the legal domain. In this paper we propose ASKE (Automated System for Knowledge Extraction), a system for the extraction of knowledge that exploits contextual embedding and zero-shot learning techniques in order to retrieve relevant conceptual and terminological knowledge from legal documents. Moreover, in the paper we discuss some preliminary experimental results on a real dataset consisting of a corpus of Illinois State Courts’ decisions taken from the Caselaw Access Project (CAP).
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https://hdl.handle.net/11583/2992896