Towards Merging Common and Technical Lexicon Wordnets

The growing amount of available information and the growing importance given to the access to technical information enhance the potential role of NLP applications in enabling users to deal with information for a variety of knowledge domains. In this process, lexical resources are crucial. Using and comparing already existent wordnets for common and technical lexica, we set up a basis for integrating these resources without losing their specific information and properties. We demonstrate their compatibility and discuss strategies to overcome the issues arrising in their merging, namely aspects concerning conceptual variation, subnet and synset merging, and the incorporation of technical and non-technical information in definitions. As we are using models of the lexicon that mirror the organization of the mental lexicon, the accomplishment of this goal can provide insights on the type of relations holding between common lexical items and terms. Also, the results of integrating such resources can contribute to the better intercommunication between experts and non-experts, and provide a useful resource for NLP, particularly for tools simultaneously serving specialist and non-specialist publics.