Abstract
Currently, large amounts of data are available in text form. This makes the automatic semantic analysis of natural language texts a topical task. This very complex task can be rather effectively solved in case when consideration is limited by certain specific kind of texts. The paper describes the developed technology of extraction of deontological statements from legal acts through a multilevel analysis of text documents combining linguistic and semantic methods. The technology is tested on the example of Russian legislative documents and shows its potential effectiveness. Experiments have shown that certain types of Universal Dependencies relations with high accuracy identify the components of deontological statements.
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
References
Pospelov, D.A.: Modeling of reasoning. In: Experience from the Analysis of Cognitive Events (1989)
Alchourron, C.E., Bulygin, E.: Normative Systems. Springer, Vienna, New York (1971)
Martino, A.A., Socci Natali, F. (eds.): Automated Analysis of Legal Texts: Logic, Informatics, Law, North-Holland (1986)
Alchourron, C.E.: Philosophical foundations of deontic logic and the logic of defeasible conditionals. In: Meyer and Wieringa, pp. 43–84 (1993)
Allen, L.E., Saxon, C.S.: Analysis of the logical structure of legal rules by a modernized and formalized version of Hohfeld’s fundamental legal conceptions (1985)
Mann, B.H.: The formalization of informal law: arbitration before the American Revolution. NYUL Rev. 59, 443 (1984)
Francesconi, E., et al. (eds.): Semantic Processing of Legal Texts: Where the Language of Law Meets the Law of Language, vol. 6036. Springer, Cham (2010)
Brighi, R., Palmirani, M.: Legal text analysis of the modification provisions: a pattern oriented approach. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law, pp. 238–239. ACM (2009)
Von Wright, G.H.: Explanation and Understanding. Cornell University Press, Ithaca (2004)
International Migration Law Unit. https://www.iom.int/migration-law/
TensorFlow. https://www.tensorflow.org/
Universal Dependencies. http://universaldependencies.org
Zaliznyak, A.A.: Grammatical dictionary of the Russian language. http://odict.ru/
Thesaurus of the Russian language WordNet. http://wordnet.ru/
Google News. https://drive.google.com/file/d/0B7XkCwpI5KDYNlNUTTlSS21pQmM/edit?usp=sharing
Mikolov, T., Sutskever, I., Chen, K., Corrado, G., Dean, J.: Distributed representations of words and phrases and their compositionality. In: Proceedings of NIPS (2013)
SinTagRus. http://www.ruscorpora.ru/search-syntax.html
Google Russian Treebank. https://old.datahub.io/dataset/universal-dependencies-treebank-russian
Acknowledgements
The study was financially supported by RFBR project №. 16-29-12878 (ofi_m) “Development of methods for identification of dynamic models with random parameters and their application to forecasting migration in Eurasia”.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Dikovitsky, V.V., Shishaev, M.G. (2019). Automated Extraction of Deontological Statements Through a Multilevel Analysis of Legal Acts. In: Silhavy, R., Silhavy, P., Prokopova, Z. (eds) Computational and Statistical Methods in Intelligent Systems. CoMeSySo 2018. Advances in Intelligent Systems and Computing, vol 859. Springer, Cham. https://doi.org/10.1007/978-3-030-00211-4_11
Download citation
DOI: https://doi.org/10.1007/978-3-030-00211-4_11
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-00210-7
Online ISBN: 978-3-030-00211-4
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)