Watset : automatic induction of synsets from a graph of synonyms


Ustalov, Dmitry ; Panchenko, Alexander ; Biemann, Chris


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DOI: https://doi.org/10.18653/v1/P17-1145
URL: https://ub-madoc.bib.uni-mannheim.de/43324
Additional URL: http://aclweb.org/anthology/P17-1145
URN: urn:nbn:de:bsz:180-madoc-433240
Document Type: Conference or workshop publication
Year of publication: 2017
Book title: The 55th Annual Meeting of the Association for Computational Linguistics : proceedings of the conference : July 30-August 4, 2017, Vancouver, Canada : ACL 2017 ; Vol. 1 (Long papers)
Page range: 1579-1590
Conference title: 55th Annual Meeting of the Association for Computational Linguistics
Location of the conference venue: Vancouver, Canada
Date of the conference: July 30-August 4, 2017
Publisher: Barzilay, Regina
Place of publication: Stroudsburg, PA
Publishing house: Association for Computational Linguistics
ISBN: 978-1-945626-75-3
Publication language: English
Institution: School of Business Informatics and Mathematics > Information Systems III: Enterprise Data Analysis (Ponzetto 2016-)
Subject: 004 Computer science, internet
Abstract: This paper presents a new graph-based approach that induces synsets using synonymy dictionaries and word embeddings. First, we build a weighted graph of synonyms extracted from commonly available resources, such as Wiktionary. Second, we apply word sense induction to deal with ambiguous words. Finally, we cluster the disambiguated version of the ambiguous input graph into synsets. Our meta-clustering approach lets us use an efficient hard clustering algorithm to perform a fuzzy clustering of the graph. Despite its simplicity, our approach shows excellent results, outperforming five competitive state-of-the-art methods in terms of F-score on three gold standard datasets for English and Russian derived from large-scale manually constructed lexical resources.




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