Unsupervised sense-aware hypernymy extraction

Dmitry Ustalov, Alexander Panchenko, Chris Biemann, Simone Paolo Ponzetto

Research output: Contribution to conferencePaperpeer-review


In this paper, we show how unsupervised sense representations can be used to improve hypernymy extraction. We present a method for extracting disambiguated hypernymy relationships that propagate hypernyms to sets of synonyms (synsets), constructs embeddings for these sets, and establishes sense-aware relationships between matching synsets. Evaluation on two gold standard datasets for English and Russian shows that the method successfully recognizes hypernymy relationships that cannot be found with standard Hearst patterns and Wiktionary datasets for the respective languages.

Original languageEnglish
Number of pages10
Publication statusPublished - 2018
Externally publishedYes
Event14th Conference on Natural Language Processing, KONVENS 2018 - Vienna, Austria
Duration: 19 Sep 201821 Sep 2018


Conference14th Conference on Natural Language Processing, KONVENS 2018

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