Paper: Learning Verb Inference Rules from Linguistically-Motivated Evidence

ACL ID D12-1018
Title Learning Verb Inference Rules from Linguistically-Motivated Evidence
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2012
Authors

Learning inference relations between verbs is at the heart of many semantic applications. However, most prior work on learning such rules focused on a rather narrow set of in- formation sources: mainly distributional sim- ilarity, and to a lesser extent manually con- structed verb co-occurrence patterns. In this paper, we claim that it is imperative to uti- lize information from various textual scopes: verb co-occurrence within a sentence, verb co- occurrence within a document, as well as over- all corpus statistics. To this end, we propose a much richer novel set of linguistically mo- tivated cues for detecting entailment between verbs and combine them as features in a su- pervised classification framework. We empir- ically demonstrate that our model significantly outperforms previous met...