Tackling Winograd Schemas by Formalizing Relevance Theory in Knowledge Graphs - (:unkn) unknown (ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE, 2014)
We study disambiguating of pronoun references in Winograd Schemas, which are part of the Winograd Schema Challenge, a proposed replacement for the Turing test. In particular we consider sentences where the pronoun can be resolved to both antecedents without semantic violations in world knowledge, that means for both readings of the sentence there is a possible consistent world. Nevertheless humans will strongly prefer one answer, which can be explained by pragmatic effects described in Relevance Theory. We state formal optimization criteria based on principles of Relevance Theory in a simplification of Roger Schank's graph framework for natural language understanding. We perform experiments using Answer Set Programming and report the usefulness of our criteria for disambiguation and their sensitivity to parameter variations.
Keywords: LANGUAGE; DEPENDENCY; SPACE