RESEARCH
SPEECH & AUDIO
Hearst Patterns Revisited: Automatic Hypernym Detection from Large Text Corpora
July 16, 2018
Abstract
Methods for unsupervised hypernym detection may broadly be categorized according to two paradigms: pattern-based and distributional methods. In this paper, we study the performance of both approaches on several hypernymy tasks and find that simple pattern-based methods consistently outperform distributional methods on common benchmark datasets. Our results show that pattern-based models provide important contextual constraints which are not yet captured in distributional methods.
AUTHORS
Publisher
ACL
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