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Hearst Patterns Revisited: Automatic Hypernym Detection from Large Text Corpora

2018-06-08ACL 2018Code Available0· sign in to hype

Stephen Roller, Douwe Kiela, Maximilian Nickel

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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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