Unsupervised sense-aware hypernymy extraction

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

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URL: https://madoc.bib.uni-mannheim.de/46078
Additional URL: https://www.oeaw.ac.at/fileadmin/subsites/academia...
URN: urn:nbn:de:bsz:180-madoc-460786
Document Type: Conference or workshop publication
Year of publication: 2018
Book title: Proceedings Konvens 2018 = Proceedings of the 14th Conference on Natural Language Processing : Vienna, Austria, September 19-21, 2018
Page range: 192-201
Conference title: 14th Conference on Natural Language Processing (KONVENS 2018)
Location of the conference venue: Vienna, Austria
Date of the conference: September 19-21, 2018
Publisher: Barbaresi, Adrien
Place of publication: Vienna
Publishing house: ÖGAI, Österreichische Akademie der Wissenschaften
Related URLs:
Publication language: English
Institution: School of Business Informatics and Mathematics > Information Systems III: Enterprise Data Analysis (Ponzetto 2016-)
License: CC BY 4.0 Creative Commons Attribution 4.0 International (CC BY 4.0)
Subject: 004 Computer science, internet
Abstract: 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.

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