Access the full text.
Sign up today, get DeepDyve free for 14 days.
Loading next page...
/lp/springer-journals/commonsense-causal-explanation-in-a-legal-domain-kVDVdcYkVu
- Publisher
- Springer Journals
- Copyright
- Copyright © 2007 by Springer Science+Business Media B.V.
- Subject
- Computer Science; Artificial Intelligence (incl. Robotics); International IT and Media Law, Intellectual Property Law; Philosophy of Law; Legal Aspects of Computing; Information Storage and Retrieval
- ISSN
- 0924-8463
- eISSN
- 1572-8382
- DOI
- 10.1007/s10506-007-9033-5
- Publisher site
- See Article on Publisher Site
Abstract
In this paper, we present an approach to commonsense causal explanation of stories that can be used for automatically determining the liable party in legal case descriptions. The approach is based on $${\mathsf {LRICore}}$$ , a core ontology for law that takes a commonsense perspective. Aside from our thesis that in the legal domain many terms still have a strong commonsense flavour, the descriptions of events in legal cases, as e.g. presented at judicial trials, are cast in commonsense terms as well. We present design principles for representing commonsense causation, and describe a process-based approach to automatic identification of causal relations in stories, which are described in terms of the core ontology. The resulting causal explanation forms a necessary condition for determining the liability and responsibility of agents that play a role in the case. We describe the basic architecture and working of $${\mathsf {DIRECT}}$$ , the demonstrator we are constructing to test the validity of our process oriented view on commonsense causation. This view holds that causal relations are in fact abstractions constructed on the basis of our commonsense understanding of physical and mental processes.
Journal
Artificial Intelligence and Law – Springer Journals
Published: Feb 10, 2007