In legal cases, stories or scenarios can serve as the context for a#R##N#crime when reasoning with evidence. In order to develop a#R##N#scientifically founded technique for evidential reasoning, a method is#R##N#required for the representation and evaluation of various scenarios in#R##N#a case. In this paper the probabilistic technique of Bayesian networks#R##N#is proposed as a method for modeling narrative, and it is shown how#R##N#this can be used to capture a number of narrative properties.#R##N##R##N#Bayesian networks quantify how the variables in a case interact.#R##N#Recent research on Bayesian networks applied to legal cases includes#R##N#the development of a list of legal idioms: recurring substructures in#R##N#legal Bayesian networks. Scenarios are coherent presentations of a#R##N#collection of states and events, and qualitative in nature. A method#R##N#combining the quantitative, probabilistic approach with the narrative#R##N#approach would strengthen the tools to represent and evaluate#R##N#scenarios.#R##N##R##N#In a previous paper, the development of a design method for modeling#R##N#multiple scenarios in a Bayesian network was initiated. The design#R##N#method includes two narrative idioms: the scenario idiom and the#R##N#merged scenarios idiom. In this current paper, the method of Vlek, et#R##N#al. (2013) is extended with a subscenario idiom and it is shown how#R##N#the method can be used to represent characteristic features of#R##N#narrative.
['Charlotte S. Vlek', 'Henry Prakken', 'Silja Renooij', 'Bart Verheij']
Representing and Evaluating Legal Narratives with Subscenarios in a Bayesian Network