KR2020Proceedings of the 17th International Conference on Principles of Knowledge Representation and ReasoningProceedings of the 17th International Conference on Principles of Knowledge Representation and Reasoning

Rhodes, Greece. September 12-18, 2020.

Edited by

ISSN: 2334-1033
ISBN: 978-0-9992411-7-2

Sponsored by
Published by

Copyright © 2020 International Joint Conferences on Artificial Intelligence Organization

Explanations for Negative Query Answers under Existential Rules

  1. İsmail İlkan Ceylan(University of Oxford)
  2. Thomas Lukasiewicz(University of Oxford)
  3. Enrico Malizia(King's College London)
  4. Cristian Molinaro(University of Calabria)
  5. Andrius Vaicenavičius(University of Oxford)


  1. Ontology formalisms and models-General
  2. Knowledge representation languages-General
  3. Ontology-based data access, integration, and exchange-General
  4. Explanation finding, diagnosis, causal reasoning, abduction-General


Ontology-mediated query answering is an extensively studied paradigm, where the conceptual knowledge provided by an ontology is leveraged towards more enhanced querying of data sources. A major advantage of ontological reasoning is its interpretability, which allows one to derive explanations for query answers. Indeed, explanations have a long history in knowledge representation, and have also been investigated for ontology languages based on description logics and existential rules. Existing works on existential rules, however, merely focus on understanding why a query is entailed, i.e., explaining positive query answers. In this paper, we continue this line of research and address another important problem, namely, explaining why a query is not entailed under existential rules, i.e., explaining negative query answers. We consider various problems related to explaining non-entailments from the abduction literature, and also introduce new problems. For all considered problems, we give a detailed complexity analysis for a wide range of existential rule languages and complexity measures.