The main goal of this project is the semantic annotation of argument nouns of SenSem corpus with synsets of WordNet. The final objective of research is the acquisition of semantic preferences.

Type-level word embeddings use the same set of parameters to represent all instances of a word regardless of its context, ignoring the inherent lexical ambiguity in language. Instead, we embed semantic concepts (or synsets) as defined in WordNet and represent a word token in a particular context by estimating a distribution over relevant semantic concepts. We use the new, context-sensitive embe...

This paper describes the process of automatically adding synsets and hypernymy relations to an existing wordnet based on word embeddings computed for POStagged lemmas in a large news corpus, achieving exact match attachment accuracy of over 80%. The reported experiments are based on the Norwegian Wordnet, but the method is language independent and also applicable to other wordnets. Moreover, th...

This paper is motivated by the demand for more linguistic resources for the study of languages and the improvement of those already existing. The first step in our work is the selection of the most significant frames in the English FrameNet according to a representative medical corpus. These frames were subsequently attached to different EuroWordNet synsets and translated into Spanish. Results ...

Keeping pace with other wordnets development, we present the challenges raised by the Romanian derivational system and our methodology for identifying derived words and their stems in the Romanian Wordnet. To attain this aim we rely only on the list of literals in the wordnet and on a list of Romanian affixes; the automatically obtained pairs require automatic and manual validation, based on a ...