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

  title={VerbOcean: Mining the Web for Fine-Grained Semantic Verb Relations},
  author={Timothy Chklovski and Patrick Pantel},
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… CONTINUE READING
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Publications referenced by this paper.
Showing 1-10 of 31 references

Nonparametric Statistics for the Behavioral Sciences

  • S. Siegel, N. Castellan
  • McGraw-Hill.
  • 1988
Highly Influential
1 Excerpt

Semantic innocence and uncompromising situations

  • J. Barwise, J. Perry
  • In: Martinich, A. P. (ed.) The Philosophy of…
  • 1985
Highly Influential
2 Excerpts