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Towards a Methodology for Formalizing Legal Texts in LegalRuleML
Adeline Nazarenko, Francois Levy, Adam Wyner
149 - 154
10.3233/978-1-61499-726-9-149
Frontiers in Artificial Intelligence and Applications
Volume 294: Legal Knowledge and Information Systems
Abstract

It is well recognised that it is difficult to make the semantic content of legal texts machine readable. We propose a systematic methodology to begin to render a sample legal text into LegalRuleML, which is a proposed markup for legal rules. We propose three levels – coarse, medium, and fine-grained analyses – each of which is compatible with LegalRuleML and which facilitate development from text to formal LegalRuleML. This paper provides guidelines for a coarse-grained analysis, highlighting some of the challenges to address even at this level.

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