Wordnet-oriented Recognition of Derivational Relations

PID

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.

Identifier
PID http://hdl.handle.net/11321/1002
Metadata Access https://clarin-pl.eu/oai/request?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai:clarin-pl.eu:11321/1002
Provenance
Creator Walentynowicz, Wiktor; Piasecki, Maciej
Publisher Global Wordnet Association
Publication Year 2023
Rights Creative Commons - Attribution 4.0 International (CC BY 4.0); https://creativecommons.org/licenses/by/4.0/; CC
OpenAccess true
Contact clarin-pl(at)pwr.edu.pl
Representation
Language English
Resource Type languageDescription
Format text/plain; charset=utf-8; application/pdf; downloadable_files_count: 1
Discipline Linguistics