Papers › Studying Taxonomy Enrichment on Diachronic WordNet Versions

Studying Taxonomy Enrichment on Diachronic WordNet Versions

23 Nov 2020COLING 2020 8arXiv:2011.11536archive 2025-07-28

Irina Nikishina, Alexander Panchenko, Varvara Logacheva, Natalia Loukachevitch

Ontologies, taxonomies, and thesauri are used in many NLP tasks. However, most studies are focused on the creation of these lexical resources rather than the maintenance of the existing ones. Thus, we address the problem of taxonomy enrichment. We explore the possibilities of taxonomy extension in a resource-poor setting and present methods which are applicable to a large number of languages. We create novel English and Russian datasets for training and evaluating taxonomy enrichment models and describe a technique of creating such datasets for other languages.

PaperPDFConference PDFCode

Code

skoltech-nlp/diachronic-wordnets officialmentioned in papermentioned on GitHubpytorch report

Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.

Code Syntology ran Syntology

Not run by Syntology. Nothing on this page verifies that the listed code works.

Results from the paper archive 2025-07-28

No leaderboard rows for this paper in the archive.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections