Populating Legal Ontologies using Semantic Role Labeling

Llio Humphreys, Guido Boella, Luigi Di Caro, Livio Robaldo, Leon van der Torre, Sepideh Ghanavati, Robert Muthuri


Abstract
This paper is concerned with the goal of maintaining legal information and compliance systems: the ‘resource consumption bottleneck’ of creating semantic technologies manually. The use of automated information extraction techniques could significantly reduce this bottleneck. The research question of this paper is: How to address the resource bottleneck problem of creating specialist knowledge management systems? In particular, how to semi-automate the extraction of norms and their elements to populate legal ontologies? This paper shows that the acquisition paradox can be addressed by combining state-of-the-art general-purpose NLP modules with pre- and post-processing using rules based on domain knowledge. It describes a Semantic Role Labeling based information extraction system to extract norms from legislation and represent them as structured norms in legal ontologies. The output is intended to help make laws more accessible, understandable, and searchable in legal document management systems such as Eunomos (Boella et al., 2016).
Anthology ID:
2020.lrec-1.264
Volume:
Proceedings of the Twelfth Language Resources and Evaluation Conference
Month:
May
Year:
2020
Address:
Marseille, France
Editors:
Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
2157–2166
Language:
English
URL:
https://aclanthology.org/2020.lrec-1.264
DOI:
Bibkey:
Cite (ACL):
Llio Humphreys, Guido Boella, Luigi Di Caro, Livio Robaldo, Leon van der Torre, Sepideh Ghanavati, and Robert Muthuri. 2020. Populating Legal Ontologies using Semantic Role Labeling. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 2157–2166, Marseille, France. European Language Resources Association.
Cite (Informal):
Populating Legal Ontologies using Semantic Role Labeling (Humphreys et al., LREC 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.lrec-1.264.pdf