Representing and Evaluating Legal Narratives with Subscenarios in a Bayesian Network

Authors Charlotte S. Vlek, Henry Prakken, Silja Renooij, Bart Verheij

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Charlotte S. Vlek
Henry Prakken
Silja Renooij
Bart Verheij

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Charlotte S. Vlek, Henry Prakken, Silja Renooij, and Bart Verheij. Representing and Evaluating Legal Narratives with Subscenarios in a Bayesian Network. In 2013 Workshop on Computational Models of Narrative. Open Access Series in Informatics (OASIcs), Volume 32, pp. 315-332, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2013)


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 Vlek, et al. (2013) is extended with a subscenario idiom and it is shown how the method can be used to represent characteristic features of narrative.
  • Narrative
  • Scenarios
  • Bayesian networks
  • Legal evidence


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