Archivio Istituzionale della RicercaIn this paper, we present the ASKE (Automated System for Knowledge Extraction) approach to legal knowledge extraction, based on a combination of context-aware embedding models and zero-shot learning techniques into a three-phase extraction cycle, which is executed a number of times to progressively extract concepts representative of the different meanings of terminology used in legal documents chunks. We show ASKE in action in a case study of legal knowledge extraction from a real corpus of case law decisions in the framework of the NGUPP project.
Automated Knowledge Extraction from Legal Texts using ASKE / Castano, Silvana; Ferrara, Alfio; Montanelli, Stefano; Picascia, Sergio; Riva, Davide. - 3741:(2024), pp. 446-455. (Intervento presentato al convegno SEBD 2024: 32nd Symposium on Advanced Database Systems tenutosi a Villasimius (ITA) nel 23-26 June 2024).
Automated Knowledge Extraction from Legal Texts using ASKE
Davide Riva
2024
Abstract
In this paper, we present the ASKE (Automated System for Knowledge Extraction) approach to legal knowledge extraction, based on a combination of context-aware embedding models and zero-shot learning techniques into a three-phase extraction cycle, which is executed a number of times to progressively extract concepts representative of the different meanings of terminology used in legal documents chunks. We show ASKE in action in a case study of legal knowledge extraction from a real corpus of case law decisions in the framework of the NGUPP project.
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https://hdl.handle.net/11583/2992932