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dc.contributor.author Walentynowicz, Wiktor
dc.contributor.author Piasecki, Maciej
dc.date.accessioned 2025-12-17T10:32:22Z
dc.date.available 2025-12-17T10:32:22Z
dc.date.issued 2023-01-01
dc.identifier.uri http://hdl.handle.net/11321/1002
dc.description Derivational relations are an important element in defining meanings, as they help to explore word-formation schemes and predict senses of derivates (derived words). In this work, we analyse different methods of representing derivational forms obtained from WordNet – from quantitative vectors to contextual learned embedding methods – and compare ways of classifying the derivational relations occurring between them. Our research focuses on the explainability of the obtained representations and results. The data source for our research is plWordNet, which is the wordnet of the Polish language and includes a rich set of derivation examples.
dc.language.iso eng
dc.publisher Global Wordnet Association
dc.rights Creative Commons - Attribution 4.0 International (CC BY 4.0)
dc.rights.uri https://creativecommons.org/licenses/by/4.0/
dc.rights.label CC
dc.subject WordNet
dc.subject wordnet
dc.subject relations
dc.subject derivational relations
dc.title Wordnet-oriented Recognition of Derivational Relations
dc.type languageDescription
metashare.ResourceInfo#ContentInfo.detailedType other
metashare.ResourceInfo#ContentInfo.mediaType text
has.files yes
branding CLARIN-PL
contact.person Alicja Derych alicja.derych@pwr.edu.pl Politechnika Wrocławska
files.size 137119
files.count 1


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