Legal requirements; semantic legal metadata; natural language processing
Résumé :
[en] [Context] Semantic legal metadata provides information that helps with understanding and interpreting the meaning of legal provisions. Such metadata is important for the systematic analysis of legal requirements. [Objectives] Our work is motivated by two observations: (1) The existing requirements engineering (RE) literature does not provide a harmonized view on the semantic metadata types that are useful for legal requirements analysis. (2) Automated support for the extraction of semantic legal metadata is scarce, and further does not exploit the full potential of natural language processing (NLP). Our objective is to take steps toward addressing these limitations. [Methods] We review and reconcile the semantic legal metadata types proposed in RE. Subsequently, we conduct a qualitative study aimed at investigating how the identified metadata types can be extracted automatically. [Results and Conclusions] We propose (1) a harmonized conceptual model for the semantic metadata types pertinent to legal requirements analysis, and (2) automated extraction rules for these metadata types based on NLP. We evaluate the extraction rules through a case study. Our results indicate that the rules generate metadata annotations with high accuracy.
Centre de recherche :
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > Software Verification and Validation Lab (SVV Lab)
Disciplines :
Sciences informatiques
Auteur, co-auteur :
SLEIMI, Amin ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
SANNIER, Nicolas ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
SABETZADEH, Mehrdad ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
BRIAND, Lionel ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Dann, John; Ministry of State > Central Legislative Service
Co-auteurs externes :
no
Langue du document :
Anglais
Titre :
Automated Extraction of Semantic Legal Metadata Using Natural Language Processing
Date de publication/diffusion :
août 2018
Nom de la manifestation :
the 26th IEEE International Requirements Engineering Conference
Date de la manifestation :
from 20-08-2018 to 24-08-2018
Manifestation à portée :
International
Titre de l'ouvrage principal :
the 26th IEEE International Requirements Engineering Conference, Banff, Alberta, 20-24 August 2018
Pagination :
124-135
Peer reviewed :
Peer reviewed
Projet FnR :
FNR11554296 - Automated Retrieval Of Metadata From Legal Texts, 2016 (01/01/2017-31/12/2018) - Mehrdad Sabetzadeh
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