Abstract: Natural language processing systems, even when given proper syntactic and semantic interpretations, still lack the common sense inference capabilities required for genuinely understanding a sentence. Recently, there have been several studies developing a semantic classification of verbs and their sentential complements, aiming at determining which inferences people draw from them. Such constructions may give rise to implied commitments that the author normally cannot disavow without being incoherent or without contradicting herself, as described for instance in the work of Kartunnen. In this paper, we model such knowledge at the semantic level by attempting to associate such inferences with specific word senses, drawing on WordNet and VerbNet. This allows us to investigate to what extent the inferences apply to semantically equivalent words within and across languages.
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