In an era when large amounts of data are generated daily in various fields, the biomedical field among others, linguistic resources can be exploited for various tasks of Natural Language Processing. Moreover, increasing number of biomedical documents are available in languages other than English. To be able to extract information from natural language free text resources, methods and tools are needed for a variety of languages. This paper presents the creation of the MoNERo corpus, a gold standard biomedical corpus for Romanian, annotated with both part of speech tags and named entities. MoNERo comprises 154,825 morphologically annotated tokens and 23,188 entity annotations belonging to four entity semantic groups corresponding to UMLS Semantic Groups.

This paper presents the preliminary investigations in the process of integrating a specialized vocabulary, namely medical terminology, into the Romanian wordnet. We focus here on four classes from this vocabulary: anatomy (or body parts), disorders, medical procedures and chemicals. In this pilot study we selected two large concepts from each class and created the Romanian terminological (sub)trees for each of them, starting from a medical thesaurus (SNOMED CT) and translating the terms, process which raised various challenges, all of them asking for the expertise of a specialist in the health care domain. The integration of these (sub)trees in the Romanian wordnet also required careful decision making, given the structural differences between a wordnet and a terminological thesaurus. They are presented and discussed herein.