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Defeasible Reasoning with Knowledge Graphs

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Knowledge Graphs and Semantic Web (KGSWC 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14382))

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Abstract

Human knowledge is subject to uncertainties, imprecision, incompleteness and inconsistencies. Moreover, the meaning of many everyday terms is dependent on the context. That poses a huge challenge for the Semantic Web. This paper introduces work on an intuitive notation and model for defeasible reasoning with imperfect knowledge, and relates it to previous work on argumentation theory. PKN is to N3 as defeasible reasoning is to deductive logic. Further work is needed on an intuitive syntax for describing reasoning strategies and tactics in declarative terms, drawing upon the AIF ontology for inspiration. The paper closes with observations on symbolic approaches in the era of large language models.

The work described in this paper was supported by the European Union’s Horizon RIA research and innovation programme under grant agreement No. 101092908 (SMARTEDGE)

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Correspondence to Dave Raggett .

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Raggett, D. (2023). Defeasible Reasoning with Knowledge Graphs. In: Ortiz-Rodriguez, F., Villazón-Terrazas, B., Tiwari, S., Bobed, C. (eds) Knowledge Graphs and Semantic Web. KGSWC 2023. Lecture Notes in Computer Science, vol 14382. Springer, Cham. https://doi.org/10.1007/978-3-031-47745-4_4

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  • DOI: https://doi.org/10.1007/978-3-031-47745-4_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-47744-7

  • Online ISBN: 978-3-031-47745-4

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