Detecting Inconsistencies in Large First-Order Knowledge Bases

  • Stephan SchulzEmail author
  • Geoff SutcliffeEmail author
  • Josef UrbanEmail author
  • Adam PeaseEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10395)


Large formalizations carry the risk of inconsistency, and hence may lead to instances of spurious reasoning. This paper describes a new approach and tool that automatically probes large first-order axiomatizations for inconsistency, by selecting subsets of the axioms centered on certain function and predicate symbols, and handling the subsets to a first-order theorem prover to test for unsatisfiability. The tool has been applied to several large axiomatizations, inconsistencies have been found, inconsistent cores extracted, and semi-automatic analysis of the inconsistent cores has helped to pinpoint the axioms that appear to be the underlying cause of inconsistency.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.DHBW StuttgartStuttgartGermany
  2. 2.University of MiamiCoral GablesUSA
  3. 3.Czech Technical University in PraguePragueCzech Republic
  4. 4.Articulate SoftwareSan FranciscoUSA

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