Hearst Patterns Revisited: Automatic Hypernym Detection from Large Text Corpora [article]

Stephen Roller, Douwe Kiela, Maximilian Nickel
<span title="2018-06-08">2018</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
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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