On annotation of the textual contents of Scottish legal instruments

Adam Wyner*, Fraser Gough, Francois Levy, Matt Lynch, Adeline Nazarenko

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

6 Citations (Scopus)
14 Downloads (Pure)


LegalRuleML is a developing standard for representing the fine-grained semantic contents of legal texts. Such a representation would be highly useful for Semantic Web applications, but deriving formal rules from the textual source is problematic; there is currently little in the way of methodology to systematically transform language to LegalRuleML. To address this, we outline the purposes, processes, and outputs of a pilot study on the annotation of the contents of Scottish legal instruments, using key LegalRuleML elements as annotations. The resulting annotated corpus is assessed in terms of how well it answers the users’ queries.

Original languageEnglish
Title of host publicationLegal Knowledge and Information Systems - JURIX 2017
Subtitle of host publicationThe 30th Annual Conference
EditorsAdam Wyner, Giovanni Casini
Place of PublicationAmsterdam
PublisherIOS Press
Number of pages6
ISBN (Electronic)9781614998389
ISBN (Print)9781614998372
Publication statusPublished - 2017
Event30th International Conference on Legal Knowledge and Information Systems, JURIX 2017 - Luxembourg, Luxembourg
Duration: 13 Dec 201715 Dec 2017

Publication series

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


Conference30th International Conference on Legal Knowledge and Information Systems, JURIX 2017

Bibliographical note

We thank the funding from the University of Aberdeen’s Impact, Knowledge Exchange, and Commercialisation Award for this 10 week study. This work was also supported by the French National Research Agency (ANR-10-LABX-0083) in the context of the Labex EFL. We also thank the student staff: A. Andonov, A. Faulds, E. Onwa, L. Schelling, R. Stoyanov, and O. Toloch.


  • Legal text processing
  • Markup language
  • Methodology
  • Semantic annotation


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