Semantic Role Labelling for Dutch Law Texts
Roos Bakker, Romy A.N. van Drie, Maaike de Boer, Robert van Doesburg, Tom van Engers
Abstract
Legal texts are often difficult to interpret, and people who interpret them need to make choices about the interpretation. To improve transparency, the interpretation of a legal text can be made explicit by formalising it. However, creating formalised representations of legal texts manually is quite labour-intensive. In this paper, we describe a method to extract structured representations in the Flint language (van Doesburg and van Engers, 2019) from natural language. Automated extraction of knowledge representation not only makes the interpretation and modelling efforts more efficient, it also contributes to reducing inter-coder dependencies. The Flint language offers a formal model that enables the interpretation of legal text by describing the norms in these texts as acts, facts and duties. To extract the components of a Flint representation, we use a rule-based method and a transformer-based method. In the transformer-based method we fine-tune the last layer with annotated legal texts. The results show that the transformed-based method (80% accuracy) outperforms the rule-based method (42% accuracy) on the Dutch Aliens Act. This indicates that the transformer-based method is a promising approach of automatically extracting Flint frames.- Anthology ID:
- 2022.lrec-1.47
- Volume:
- Proceedings of the Thirteenth Language Resources and Evaluation Conference
- Month:
- June
- Year:
- 2022
- 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, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 448–457
- Language:
- URL:
- https://aclanthology.org/2022.lrec-1.47
- DOI:
- Cite (ACL):
- Roos Bakker, Romy A.N. van Drie, Maaike de Boer, Robert van Doesburg, and Tom van Engers. 2022. Semantic Role Labelling for Dutch Law Texts. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 448–457, Marseille, France. European Language Resources Association.
- Cite (Informal):
- Semantic Role Labelling for Dutch Law Texts (Bakker et al., LREC 2022)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/2022.lrec-1.47.pdf