Abstract
In this work we illustrate a novel approach for solving an information extraction problem on legal texts. It is based on Natural Language Processing techniques and on the adoption of a formalization that allows coupling domain knowledge and syntactic information. The proposed approach is applied to extend an existing system to assist human annotators in handling normative modificatory provisions –that are the changes to other normative texts–. Such laws ‘versioning’ problem is a hard and relevant one. We provide a linguistic and legal analysis of a particular case of modificatory provision (the efficacy suspension), show how such knowledge can be formalized in a linguistic resource such as FrameNet, and used by the semantic interpreter.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Baker, C.F., Fillmore, C.J., Lowe, J.B.: The Berkeley FrameNet Project. In: Proceedings of the 17th International Conference on Computational Linguistics, vol. 1, pp. 86–90. Association for Computational Linguistics, Montreal (1998), http://portal.acm.org/citation.cfm?id=980860
Biagioli, C., Francesconi, E., Spinosa, P., Taddei, M.: The NIR project: Standards and tools for legislative drafting and legal document web publication. In: Proceedings of ICAIL Workshop on e-Government:Modelling Norms and Concepts as Key Issues, pp. 69–78 (2003)
Brighi, R., Lesmo, L., Mazzei, A., Palmirani, M., Radicioni, D.P.: Towards Semantic Interpretation of Legal Modifications through Deep Syntactic Analysis. In: Jurix 2008: The 21st Annual Conference. Frontiers in Artificial Intelligence and Applications, vol. 189, pp. 202–206. IOS Press (2008), http://www.di.unito.it/~radicion/papers/brighi08towards.pdf
Cherubini, M., Giardiello, G., Marchi, S., Montemagni, S., Spinosa, P., Venturi, G.: NLP-based metadata annotation of textual amendments. In: Proc. of Workshop On Legislative Xml, JURIX 2008 (2008)
Fillmore, C.J.: Scenes-and-frames semantics. In: Zampolli, A. (ed.) Linguistic Structures Processing, pp. 55–79. North-Holland, Amsterdam (1977)
Lesmo, L.: The Rule-Based Parser of the NLP Group of the University of Torino. Intelligenza Artificiale 2(4), 46–47 (2007)
Lesmo, L., Mazzei, A., Radicioni, D.P.: Semantic Annotation of Legal Modificatory Provisions. In: Serra, R., Cucchiara, R. (eds.) AI*IA 2009. LNCS, vol. 5883, pp. 304–313. Springer, Heidelberg (2009), http://dblp.uni-trier.de/db/conf/aiia/aiia2009.html#LesmoMR09
Lupo, C., Vitali, F., Francesconi, E., Palmirani, M., Winkels, R., de Maat, E., Boer, A., Mascellani, P.: General XML format(s) for legal Sources - ESTRELLA European Project. Deliverable 3.1, Faculty of Law, University of Amsterdam, Amsterdam, The Netherlands (2007), http://www.estrellaproject.org
de Maat, E., Winkels, R.: Automatic Classification of Sentences in Dutch Laws. In: Legal Knowledge and Information Systems, Jurix 2008: The 21st Annual Conference. Frontiers in Artificial Intelligence and Applications, pp. 207–216. IOS Press (December 2008)
Mazzei, A., Radicioni, D., Brighi, R.: NLP-based Extraction of Modificatory Provisions Semantics. In: Proceedings of the International Conference on Artificial Intelligence and Law, ICAIL 2009, pp. 50–57. ACM, Barcelona (2009)
McCarty, L.T.: Deep semantic interpretations of legal texts. In: ICAIL 2007: Proceedings of the 11th International Conference on Artificial Intelligence and Law, pp. 217–224. ACM, New York (2007)
Palmirani, M., Brighi, R.: An XML Editor for Legal Information Management. In: Traunmüller, R. (ed.) EGOV 2003. LNCS, vol. 2739, pp. 421–429. Springer, Heidelberg (2003)
Palmirani, M., Brighi, R.: Model Regularity of Legal Language in Active Modifications. In: Casanovas, P., Pagallo, U., Sartor, G., Ajani, G. (eds.) AICOL-II/JURIX 2009. LNCS, vol. 6237, pp. 54–73. Springer, Heidelberg (2010)
Palmirani, M., Brighi, R., Massini, M.: Automated Extraction of Normative References in Legal Texts. In: ICAIL 2003, pp. 105–106 (2003), http://dblp.uni-trier.de/db/conf/icail/icail2003.html#PalmiraniBM03
Soria, C., Bartolini, R., Lenci, A., Montemagni, S., Pirrelli, V.: Automatic Extraction of Semantics in Law Documents. In: Biagioli, C., Francesconi, E., Sartor, G. (eds.) Proceedings of the V Legislative XML Workshop, pp. 253–266. European Press Academic Publishing (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ceci, M., Lesmo, L., Mazzei, A., Palmirani, M., Radicioni, D.P. (2012). Semantic Annotation of Legal Texts through a FrameNet-Based Approach. In: Palmirani, M., Pagallo, U., Casanovas, P., Sartor, G. (eds) AI Approaches to the Complexity of Legal Systems. Models and Ethical Challenges for Legal Systems, Legal Language and Legal Ontologies, Argumentation and Software Agents. AICOL 2011. Lecture Notes in Computer Science(), vol 7639. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35731-2_17
Download citation
DOI: https://doi.org/10.1007/978-3-642-35731-2_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-35730-5
Online ISBN: 978-3-642-35731-2
eBook Packages: Computer ScienceComputer Science (R0)