Representing and Evaluating Legal Narratives with Subscenarios in a Bayesian Network

Charlotte Vlek, Henry Prakken, Silja Renooij, Bart Verheij

In legal cases, stories or scenarios can serve as the context for a crime when reasoning with evidence. In order to develop a scientifically founded technique for evidential reasoning, a method is required for the representation and evaluation of various scenarios in a case. In this paper the probabilistic technique of Bayesian networks is proposed as a method for modeling narrative, and it is shown how this can be used to capture a number of narrative properties.

Bayesian networks quantify how the variables in a case interact. Recent research on Bayesian networks applied to legal cases includes the development of a list of legal idioms: recurring substructures in legal Bayesian networks. Scenarios are coherent presentations of a collection of states and events, and qualitative in nature. A method combining the quantitative, probabilistic approach with the narrative approach would strengthen the tools to represent and evaluate scenarios.

In a previous paper, the development of a design method for modeling multiple scenarios in a Bayesian network was initiated. The design method includes two narrative idioms: the scenario idiom and the merged scenarios idiom. In this current paper, the method of [34] is extended with a subscenario idiom and it is shown how the method can be used to represent characteristic features of narrative.

Manuscript (in PDF-format)

Reference:
Vlek, C., Prakken, H., Renooij, S., & Verheij, B. (2013). Representing and Evaluating Legal Narratives with Subscenarios in a Bayesian Network. Proceedings of the 2013 Workshop on Computational Models of Narrative (CMN 2013) (eds. Finlayson, M.A., Fisseni, B., Lwe, B., & Meister, J.C.), 315-332. Dagstuhl: OASICS.


Bart Verheij's home page - research - publications