Commonsense causal explanation in a legal domain

Artificial Intelligence and Law 15 (3):281-299 (2007)

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, 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, 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

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References found in this work

Causality: Models, Reasoning and Inference.Judea Pearl - 2000 - Cambridge University Press.
Using Language.Herbert Clark - 1996 - Cambridge University Press.
Causality: Models, Reasoning and Inference.Judea Pearl - 2000 - Tijdschrift Voor Filosofie 64 (1):201-202.
Qualitative Process Theory.Kenneth D. Forbus - 1984 - Artificial Intelligence 24 (1-3):85-168.

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