A methodology to create legal ontologies in a logic programming based web information retrieval system
David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jack Alan Reynolds
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Artificial Intelligence and Law 12 (4):397-417 (2004)
Web legal information retrieval systems need the capability to reason with the knowledge modeled by legal ontologies. Using this knowledge it is possible to represent and to make inferences about the semantic content of legal documents. In this paper a methodology for applying NLP techniques to automatically create a legal ontology is proposed. The ontology is defined in the OWL semantic web language and it is used in a logic programming framework, EVOLP+ISCO, to allow users to query the semantic content of the documents. ISCO allows an easy and efficient integration of declarative, object-oriented and constraint-based programming techniques with the capability to create connections with external databases. EVOLP is a dynamic logic programming framework allowing the definition of rules for actions and events. An application of the proposed methodology to the legal web information retrieval system of the Portuguese Attorney General’s Office is described.
|Keywords||Ontologies OWL natural language processing logic programming|
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Adam Wyner & Rinke Hoekstra (2012). A Legal Case OWL Ontology with an Instantiation of Popov V. Hayashi. Artificial Intelligence and Law 20 (1):83-107.
Leonardo Lesmo, Alessandro Mazzei, Monica Palmirani & Daniele P. Radicioni (2013). TULSI: An NLP System for Extracting Legal Modificatory Provisions. [REVIEW] Artificial Intelligence and Law 21 (2):139-172.
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