Why we have switched from building full-fledged taxonomies to simply detecting hypernymy relations
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The study of taxonomies and hypernymy relations has been extensive on the Natural Language Processing (NLP) literature. However, the evaluation of taxonomy learning approaches has been traditionally troublesome, as it mainly relies on ad-hoc experiments which are hardly reproducible and manually expensive. Partly because of this, current research has been lately focusing on the hypernymy detection task. In this paper we reflect on this trend, analyzing issues related to current evaluation procedures. Finally, we propose three potential avenues for future work so that is-a relations and resources based on them play a more important role in downstream NLP applications.
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