This paper presents the Open Knowledge Extraction (OKE) tools combined with natural language analysis of the sentence in order to enrich the semantic of the legal knowledge extracted from legal text. In particular the use case is on international private law with specific regard to the Rome I Regulation EC 593/2008, Rome II Regulation EC 864/2007, and Brussels I bis Regulation EU 1215/2012. A Knowledge Graph (KG) is built using OKE and Natural Language Processing (NLP) methods jointly with the main ontology design patterns defined for the legal domain (e.g., event, time, role, agent, right, obligations, jurisdiction). Using critical questions, underlined by legal experts in the domain, we have built a question answering tool capable to support the information retrieval and to answer to these queries. The system should help the legal expert to retrieve the relevant legal information connected with topics, concepts, entities, normative references in order to integrate his/her searching activities.

Legal Knowledge Extraction for Knowledge Graph Based Question-Answering / Francesco Sovrano, Monica Palmirani, Fabio Vitali. - ELETTRONICO. - 334:(2020), pp. 15.143-15.153. (Intervento presentato al convegno Legal Knowledge and Information Systems (JURIX 2020), 33rd International Conference. tenutosi a Brno, Czech Republic nel December 9–11, 2020) [10.3233/FAIA200858].

Legal Knowledge Extraction for Knowledge Graph Based Question-Answering

Francesco Sovrano
Primo
Conceptualization
;
Monica Palmirani
Secondo
Conceptualization
;
Fabio Vitali
Ultimo
Conceptualization
2020

Abstract

This paper presents the Open Knowledge Extraction (OKE) tools combined with natural language analysis of the sentence in order to enrich the semantic of the legal knowledge extracted from legal text. In particular the use case is on international private law with specific regard to the Rome I Regulation EC 593/2008, Rome II Regulation EC 864/2007, and Brussels I bis Regulation EU 1215/2012. A Knowledge Graph (KG) is built using OKE and Natural Language Processing (NLP) methods jointly with the main ontology design patterns defined for the legal domain (e.g., event, time, role, agent, right, obligations, jurisdiction). Using critical questions, underlined by legal experts in the domain, we have built a question answering tool capable to support the information retrieval and to answer to these queries. The system should help the legal expert to retrieve the relevant legal information connected with topics, concepts, entities, normative references in order to integrate his/her searching activities.
2020
Legal Knowledge and Information Systems JURIX 2020: The Thirty-third Annual Conference, Brno, Czech Republic, December 9–11, 2020
143
153
Legal Knowledge Extraction for Knowledge Graph Based Question-Answering / Francesco Sovrano, Monica Palmirani, Fabio Vitali. - ELETTRONICO. - 334:(2020), pp. 15.143-15.153. (Intervento presentato al convegno Legal Knowledge and Information Systems (JURIX 2020), 33rd International Conference. tenutosi a Brno, Czech Republic nel December 9–11, 2020) [10.3233/FAIA200858].
Francesco Sovrano, Monica Palmirani, Fabio Vitali
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/785891
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