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The study of taxonomies and hypernymy relations has been extensive on theNatural Language Processing (NLP) literature. However, the evaluation oftaxonomy learning approaches has been traditionally troublesome, as it mainlyrelies on ad-hoc experiments which are hardly reproducible and manuallyexpensive. Partly because of this, current research has been lately focusing onthe hypernymy detection task. In this paper we reflect on this trend, analyzingissues related to current evaluation procedures. Finally, we propose threepotential avenues for future work so that is-a relations and resources based onthem play a more important role in downstream NLP applications.

Why we have switched from building full-fledged taxonomies to simply detecting hypernymy relations