Abstract
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.
Cite
CITATION STYLE
Nikishina, I., Panchenko, A., Logacheva, V., & Loukachevitch, N. (2020). Studying Taxonomy Enrichment on Diachronic WordNet Versions. In COLING 2020 - 28th International Conference on Computational Linguistics, Proceedings of the Conference (pp. 3095–3106). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2020.coling-main.276
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