Broad-coverage repositories of semantic relations between verbs could benefit many NLP tasks. We present a semi-automatic method for extracting fine-grained semantic relations between verbs. We detect similarity, strength, antonymy, enablement, and temporal happens-before relations between pairs of strongly associated verbs using lexicosyntactic patterns over the Web. On a set of 29,165 strongly associated verb pairs, our extraction algorithm yielded 65.5% accuracy. Analysis of error types shows that on the relation strength we achieved 75% accuracy. We provide the resource, called VERBOCEAN, for download at
VerbOcean REF ) is a resource of strongly associated verb pairs and their semantic relationship.
VerbOcean: Mining The Web For Fine-Grained Semantic Verb Relations
SIGDAT Conference On Empirical Methods In Natural Language Processing
Computer Science