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Reasoning Under Uncertainty in Knowledge Graphs

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Rules and Reasoning (RuleML+RR 2020)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 12173))

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Abstract

We provide a framework for probabilistic reasoning in Vadalog-based Knowledge Graphs (KGs), able to satisfy the requirements of ontological reasoning: full recursion, powerful existential quantification, and the ability to express inductive definitions. Vadalog is based on Warded Datalog+/−, an existential rule language that strikes a good balance between computational complexity: with tractable reasoning in data complexity, and expressive power covering SPARQL under set semantics and the entailment regime for OWL 2 QL. Vadalog and its logical core Warded Datalog+/− are not covered by existing probabilistic programming and statistical relational models for many reasons including weak support for existentials, recursion and the impossibility to express inductive definitions. We introduce Soft Vadalog, a probabilistic extension to Vadalog satisfying these desiderata. It defines a probability distribution over the nodes of a chase network, a structure induced by the grounding of a Soft Vadalog program with the chase procedure.

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Acknowledgements

The work on this paper was supported by EPSRC programme grant EP/M025268/1, the EU H2020 grant 809965, and the Vienna Science and Technology (WWTF) grant VRG18-013.

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Authors and Affiliations

  1. Banca d’Italia, Rome, Italy

    Luigi Bellomarini & Eleonora Laurenza

  2. TU Wien, Vienna, Austria

    Emanuel Sallinger

  3. University of Oxford, Oxford, UK

    Emanuel Sallinger & Evgeny Sherkhonov

Authors
  1. Luigi Bellomarini
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  2. Eleonora Laurenza
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  3. Emanuel Sallinger
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  4. Evgeny Sherkhonov
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Corresponding author

Correspondence to Luigi Bellomarini .

Editor information

Editors and Affiliations

  1. School of Computer Science and Informatics, Cardiff University, Cardiff, UK

    Víctor Gutiérrez-Basulto

  2. University of Economics, Prague, Prague, Czech Republic

    Tomáš Kliegr

  3. Norwegian University of Science and Technology, Gjøvik, Norway

    Ahmet Soylu

  4. Department Of Informatics, University of Oslo, Oslo, Norway

    Martin Giese

  5. SINTEF AS, Oslo, Norway

    Dumitru Roman

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Bellomarini, L., Laurenza, E., Sallinger, E., Sherkhonov, E. (2020). Reasoning Under Uncertainty in Knowledge Graphs. In: Gutiérrez-Basulto, V., Kliegr, T., Soylu, A., Giese, M., Roman, D. (eds) Rules and Reasoning. RuleML+RR 2020. Lecture Notes in Computer Science(), vol 12173. Springer, Cham. https://doi.org/10.1007/978-3-030-57977-7_9

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  • DOI: https://doi.org/10.1007/978-3-030-57977-7_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-57976-0

  • Online ISBN: 978-3-030-57977-7

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