Verbs can only be used with a few specific arrangements of their arguments (syntactic frames). Most theorists note that verbs can be organized into a hierarchy of verb classes based on the frames they admit. Here we show that such a hierarchy is objectively well-supported by the patterns of verbs and frames in English, since a systematic hierarchical clustering algorithm converges on the same structure as the handcrafted taxonomy of VerbNet, a broad-coverage verb lexicon. We also show that the hierarchies capture meaningful psychological dimensions of generalization by predicting novel verb coercions by human participants. We discuss limitations of a simple hierarchical representation and suggest similar approaches for identifying the representations underpinning verb argument structure.

This research describes efforts to use crowdsourcing to improve the validity of the semantic predicates in VerbNet, a lexicon of about 6300 English verbs.The current semantic predicates can be thought of semantic primitives, into which the concepts denoted by a verb can be decomposed.For example, the verb spray (of the Spray class), involves the predicates MOTION, NOT, and LOCATION, where the event can be decomposed into an AGENT causing a THEME that was originally not in a particular location to now be in that location.Although VerbNet's predicates are theoretically well-motivated, systematic empirical data is scarce.This paper describes a recently-launched attempt to address this issue with a series of human judgment tasks, posed to subjects in the form of games.