Towards a methodology for formalizing legal texts in LegalRuleML

Adeline Nazarenko*, Francois Levy, Adam Wyner

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

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.

Original languageEnglish
Title of host publicationLegal Knowledge and Information Systems - JURIX 2016
Subtitle of host publicationThe 29th Annual Conference
PublisherIOS Press
Pages149-154
Number of pages6
Volume294
ISBN (Electronic)9781614997252
DOIs
Publication statusPublished - 2016
Event29th International Conference on Legal Knowledge and Information Systems, JURIX 2016 - Nice, France
Duration: 14 Dec 201616 Dec 2016

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume294
ISSN (Print)0922-6389

Conference

Conference29th International Conference on Legal Knowledge and Information Systems, JURIX 2016
CountryFrance
CityNice
Period14/12/1616/12/16

Keywords

  • Legal text processing
  • Markup language
  • Methodology

ASJC Scopus subject areas

  • Artificial Intelligence

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  • Cite this

    Nazarenko, A., Levy, F., & Wyner, A. (2016). Towards a methodology for formalizing legal texts in LegalRuleML. In Legal Knowledge and Information Systems - JURIX 2016: The 29th Annual Conference (Vol. 294, pp. 149-154). (Frontiers in Artificial Intelligence and Applications; Vol. 294). IOS Press. https://doi.org/10.3233/978-1-61499-726-9-149