Legal Knowledge Conveyed by Narratives: Towards a Representational Model

Authors Giovanni Sileno, Alexander Boer, Tom van Engers

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Giovanni Sileno
Alexander Boer
Tom van Engers

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Giovanni Sileno, Alexander Boer, and Tom van Engers. Legal Knowledge Conveyed by Narratives: Towards a Representational Model. In 2014 Workshop on Computational Models of Narrative. Open Access Series in Informatics (OASIcs), Volume 41, pp. 182-191, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)


The paper investigates a representational model for narratives, aiming to facilitate the acquisition of the systematic core of stories concerning legal cases, i.e. the set of causal and temporal relationships that govern the world in which the narrated scenario takes place. At the discourse level, we consider narratives as sequences of "messages" collected in an "observation", including descriptions of agents, of agents' behaviour and of "mechanisms" relative to physical, mental and institutional domains. At the content level, stories correspond to synchronizations of embodied "agent-roles" scripts. Following this approach, the "Pierson v Post" case is analyzed in detail and represented as a Petri net.
  • story representation
  • story acquisition
  • legal narratives
  • knowledge representation
  • agent-roles
  • causation
  • expectations
  • agent-based modeling
  • petri


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