VerbOcean: Mining the Web for Fine-Grained Semantic Verb Relations

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 http://semantics.isi.edu/ocean/.

• Type: Conference
• Year: 2004
• Where: EMNLP
• Authors: Timothy Chklovski, Patrick Pantel
• Keywords: Associated Verb, EMNLP 2004, EMNLP 2007, Fine-grained Semantic Relations, Semantic Relations