Paper: Large-Scale Verb Entailment Acquisition from the Web

ACL ID D09-1122
Title Large-Scale Verb Entailment Acquisition from the Web
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2009

Textual entailment recognition plays a fundamental role in tasks that require in- depth natural language understanding. In order to use entailment recognition tech- nologies for real-world applications, a large-scale entailment knowledge base is indispensable. This paper proposes a con- ditional probability based directional sim- ilarity measure to acquire verb entailment pairs on a large scale. We targeted 52,562 verb types that were derived from 10 8 Japanese Web documents, without regard for whether they were used in daily life or only in specific fields. In an evaluation of the top 20,000 verb entailment pairs ac- quired by previous methods and ours, we found that our similarity measure outper- formed the previous ones. Our method also worked well for the top 100,000 re- sults.