OASIcs.CMN.2014.182.pdf
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Legal Knowledge Conveyed by Narratives: Towards a Representational Model
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2014 Workshop on Computational Models of Narrative (CMN 2014)
Series: Open Access Series in Informatics (OASIcs) - License:
Creative Commons Attribution 3.0 Unported license
- Publication Date: 2014-08-08
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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)
https://doi.org/10.4230/OASIcs.CMN.2014.182
https://doi.org/10.4230/OASIcs.CMN.2014.182
Abstract
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.
Keywords
- story representation
- story acquisition
- legal narratives
- knowledge representation
- agent-roles
- causation
- expectations
- agent-based modeling
- petri
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