TY - GEN
T1 - Towards a methodology for formalizing legal texts in LegalRuleML
AU - Nazarenko, Adeline
AU - Levy, Francois
AU - Wyner, Adam
PY - 2016
Y1 - 2016
N2 - 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.
AB - 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.
KW - Legal text processing
KW - Markup language
KW - Methodology
UR - http://www.scopus.com/inward/record.url?scp=85014769254&partnerID=8YFLogxK
U2 - 10.3233/978-1-61499-726-9-149
DO - 10.3233/978-1-61499-726-9-149
M3 - Published conference contribution
AN - SCOPUS:85014769254
VL - 294
T3 - Frontiers in Artificial Intelligence and Applications
SP - 149
EP - 154
BT - Legal Knowledge and Information Systems - JURIX 2016
PB - IOS Press
T2 - 29th International Conference on Legal Knowledge and Information Systems, JURIX 2016
Y2 - 14 December 2016 through 16 December 2016
ER -