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dc.contributor.author Maziarz, Marek
dc.contributor.author Rudnicka, Ewa
dc.date.accessioned 2025-12-17T10:27:19Z
dc.date.available 2025-12-17T10:27:19Z
dc.date.issued 2020-12-01
dc.identifier.uri http://hdl.handle.net/11321/990
dc.description Evocation — a phenomenon of sense associations going beyond standard (lexico)-semantic relations — is difficult to recognise for natural language processing systems. Machine learning models give predictions which are only moderately correlated with the evocation strength. It is believed that ordinary graph measures are not as good at this task as methods based on vector representations. The paper proposes a new method of enriching the WordNet structure with weighted polysemy and gloss links, and proves that Dijkstra’s algorithm performs equally as well as other more sophisticated measures when set together with such expanded structures.
dc.language.iso eng
dc.publisher Instytut Slawistyki Polskiej Akademii Nauk
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 evocation
dc.subject WordNet
dc.subject polysemy
dc.subject evocation strength
dc.subject semantic relations
dc.title Expanding WordNet with Gloss and Polysemy Links for Evocation Strength Recognition
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 2982000
files.count 1


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