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.
|Title of host publication||Legal Knowledge and Information Systems - JURIX 2017|
|Subtitle of host publication||The 30th Annual Conference|
|Editors||Adam Wyner, Giovanni Casini|
|Place of Publication||Amsterdam|
|Number of pages||6|
|Publication status||Published - 2017|
|Event||30th International Conference on Legal Knowledge and Information Systems, JURIX 2017 - Luxembourg, Luxembourg|
Duration: 13 Dec 2017 → 15 Dec 2017
|Name||Frontiers in Artificial Intelligence and Applications|
|Conference||30th International Conference on Legal Knowledge and Information Systems, JURIX 2017|
|Period||13/12/17 → 15/12/17|
Bibliographical noteWe 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
- Semantic annotation