Automated ontology population using information extraction algorithms can produce inconsistent knowledge bases. Confidence values assigned by the extraction algorithms may serve as evidence helping to repair produced inconsistencies. Dempster-Shafer theory of evidence is a formalism, which allows appropriate interpretation of extractors’
confidence values. The talk presents an algorithm for translating the subontologies containing conflicts into belief propagation networks and repairing conflicts based on Dempster-Shafer plausibility.

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