Paper: Exploiting Multiple Sources for Open-Domain Hypernym Discovery

ACL ID D13-1122
Title Exploiting Multiple Sources for Open-Domain Hypernym Discovery
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2013
Authors

Hypernym discovery aims to extract such noun pairs that one noun is a hypernym of the other. Most previous methods are based on lexical patterns but perform badly on open- domain data. Other work extracts hypernym relations from encyclopedias but has limited coverage. This paper proposes a simple yet ef- fective distant supervision framework for Chi- nese open-domain hypernym discovery. Giv- en an entity name, we try to discover its hy- pernyms by leveraging knowledge from mul- tiple sources, i.e., search engine results, ency- clopedias, and morphology of the entity name. First, we extract candidate hypernyms from the above sources. Then, we apply a statistical ranking model to select correct hypernyms. A set of novel features is proposed for the rank- ing model. We also present a heuristi...