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A Language-independent Sense Clustering Approach for Enhanced WSD

  • We present a method for clustering word senses of a lexical-semantic resource by mapping them to those of another sense inventory. This is a promising way of reducing polysemy in sense inventories and consequently improving word sense disambiguation performance. In contrast to previous approaches, we use Dijkstra-WSA, a parameterizable alignment algorithm which is largely resource- and language-agnostic. To demonstrate this, we apply our technique to GermaNet, the German equivalent to WordNet. The GermaNet sense clusterings we induce through alignments to various collaboratively constructed resources achieve a significant boost in accuracy, even though our method is far less complex and less dependent on language-specific knowledge than past approaches.

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Author:Michael Matuschek, Tristan Miller, Iryna Gurevych
Parent Title (English):Proceedings of the 12th edition of the KONVENS conference
Document Type:Conference Proceeding
Date of Publication (online):2014/10/22
Release Date:2014/10/22
Tag:lexical resources; ontology
GND Keyword:Lexikalische Kategorie
First Page:11
Last Page:21
PPN:Link zum Katalog
Contributor:Faaß, Gertrud
Institutes:Fachbereich III / Informationswissenschaft und Sprachtechnologie
DDC classes:400 Sprache / 400 Sprache, Linguistik
Collections:KONVENS 2014 / Proceedings of the 12th KONVENS 2014
Licence (German):License LogoCreative Commons - Namensnennung 3.0