Knowledge extraction systems are strongly demanded in the legal domain, to provide legal actors like judges or lawyers with useful and relevant information to enforce a knowledge-based evaluation and judge- ment of new cases. In this paper, we present LATO-KM, a three-layer legal knowledge model where terms featuring legal knowledge, both law and case-law, are properly formalized as entities and relationships and they are implemented in the LATO ontology using SKOS. The LATO ontology constitutes the core component of CRIKE (CRIme Knowledge Extraction), a data-science approach and related tool environment con- ceived to support legal knowledge extraction and enrichment from a cor- pus of Court Decision documents.

The LATO knowledge model for automated knowledge extraction and enrichment from court decisions corpora / S. Castano, M. Falduti, A. Ferrara, S. Montanelli (CEUR WORKSHOP PROCEEDINGS). - In: COUrT 2020 : CAiSE for Legal Documents 2020 / [a cura di] A. Tagarelli, E. Zumpano, A. Kamisalić Latifić, A. Calì. - [s.l] : CEUR-WS, 2020. - pp. 15-26 (( convegno First International Workshop "CAiSE for Legal Documents" (COUrT 2020), co-located with the 32nd International Conference on Advanced Information Systems Engineering (CAiSE 2020) tenutosi a Grenoble nel 2020.

The LATO knowledge model for automated knowledge extraction and enrichment from court decisions corpora

S. Castano
Primo
;
M. Falduti
Secondo
;
A. Ferrara
Penultimo
;
S. Montanelli
Ultimo
2020

Abstract

Knowledge extraction systems are strongly demanded in the legal domain, to provide legal actors like judges or lawyers with useful and relevant information to enforce a knowledge-based evaluation and judge- ment of new cases. In this paper, we present LATO-KM, a three-layer legal knowledge model where terms featuring legal knowledge, both law and case-law, are properly formalized as entities and relationships and they are implemented in the LATO ontology using SKOS. The LATO ontology constitutes the core component of CRIKE (CRIme Knowledge Extraction), a data-science approach and related tool environment con- ceived to support legal knowledge extraction and enrichment from a cor- pus of Court Decision documents.
Legal Knowledge Model; Legal Ontology; Knowledge Extraction; Knowledge Enrichment
Settore INF/01 - Informatica
2020
http://ceur-ws.org/Vol-2690/COUrT-paper2.pdf
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/891357
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