  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.
