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Hearst Patterns Revisited: Automatic Hypernym Detection from Large Text Corpora

, , and . ACL (2), page 358-363. Association for Computational Linguistics, (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.

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roller2018hearst
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