Automated legal knowledge extraction systems are strongly demanded, to support annotation of legal documents as well as knowledge extraction from them, to provide useful and relevant suggestions to legal actors (e.g., judges, lawyers) for managing incoming new cases. In this paper, we propose CRIKE (CRIme Knowledge Extraction), a knowledge-based framework conceived to support legal knowledge extraction from a collection of legal documents, based on a reference legal ontology called LATO (Legal Abstract Term Ontology). We first introduce LATO-KM, the knowledge model of LATO where legal knowledge featuring documents in the collection is properly formalized as conceptual knowledge, in form of legal concepts and relationships, and terminological knowledge, in form of term-sets associated with legal concepts. Then, we present the bootstrapping cycle of CRIKE that aims to progressively enrich the terminological knowledge layer of LATO by extracting new terms from legal documents to be used for enriching the term-set associated with a corresponding legal concept. Finally, to evaluate the results obtained through CRIKE, we discuss experimental results on a real dataset of 180,000 court decisions of the State of Illinois taken from the Caselaw Access Project (CAP).

A knowledge-centered framework for exploration and retrieval of legal documents / S. Castano, M. Falduti, A. Ferrara, S. Montanelli. - In: INFORMATION SYSTEMS. - ISSN 0306-4379. - (2021), pp. 101842.1-101842.14. [Epub ahead of print] [10.1016/j.is.2021.101842]

A knowledge-centered framework for exploration and retrieval of legal documents

S. Castano
Primo
;
M. Falduti
Secondo
;
A. Ferrara
Penultimo
;
S. Montanelli
Ultimo
2021

Abstract

Automated legal knowledge extraction systems are strongly demanded, to support annotation of legal documents as well as knowledge extraction from them, to provide useful and relevant suggestions to legal actors (e.g., judges, lawyers) for managing incoming new cases. In this paper, we propose CRIKE (CRIme Knowledge Extraction), a knowledge-based framework conceived to support legal knowledge extraction from a collection of legal documents, based on a reference legal ontology called LATO (Legal Abstract Term Ontology). We first introduce LATO-KM, the knowledge model of LATO where legal knowledge featuring documents in the collection is properly formalized as conceptual knowledge, in form of legal concepts and relationships, and terminological knowledge, in form of term-sets associated with legal concepts. Then, we present the bootstrapping cycle of CRIKE that aims to progressively enrich the terminological knowledge layer of LATO by extracting new terms from legal documents to be used for enriching the term-set associated with a corresponding legal concept. Finally, to evaluate the results obtained through CRIKE, we discuss experimental results on a real dataset of 180,000 court decisions of the State of Illinois taken from the Caselaw Access Project (CAP).
Legal document retrieval and exploration; Legal knowledge extraction; Legal knowledge model
Settore INF/01 - Informatica
2021
7-lug-2021
Article (author)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/891355
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