Abstract
In this chapter an approach to support knowledge acquisition in the legal domain is presented: it is based on a semantic model for legislation and implemented using knowledge extraction techniques on legislative texts. This methodology is targeted to propose a framework which can contribute to bridge the gap between consensus and authoritativeness in legal knowledge implementation.
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Notes
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Folksonomies (or social tagging mechanisms) have been widely implemented in knowledge sharing environments; the idea was first adopted by the social bookmarking site del.icio.us (2004) http://delicious.com
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“Typically regulations are not given in an empty environment; instead they make use of terminology and concepts which are relevant to the organisation and/or the aspect they seek to regulate. Thus, to be able to capture the meaning of regulations, one needs to encode not only the regulations themselves, but also the underlying ontological knowledge. This knowledge usually includes the terminology used, its basic structure, and integrity constraints that need to be satisfied.” Grigoris Antoniou, David Billington, Guido Governatori, and Michael J. Maher, “On the modeling and analysis of regulations”, in Proceedings of the Australian Conference Information Systems, pages 20–29, 1999.
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xmLegesExtractor has been developed in collaboration with the Institute of Computational Linguistics (ILC-CNR) in Pisa (Italy)
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Francesconi, E. (2011). A Learning Approach for Knowledge Acquisition in the Legal Domain. In: Sartor, G., Casanovas, P., Biasiotti, M., Fernández-Barrera, M. (eds) Approaches to Legal Ontologies. Law, Governance and Technology Series, vol 1. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-0120-5_13
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