The human sense of smell is one of our most sensitive senses and a powerful warning system for potentially dangerous situations such as rotten food or a gas leak. However, detecting references to smell and representing these in a machine interpretable format is as yet an under-researched topic in computer vision, natural language processing and the semantic web.
How can you find information in heterogeneous sources, available at different locations and managed by different owners? In the Dutch Digital Heritage Network (NDE) we are working on a distributed solution for this: the Network of Terms. We encourage our institutions to assign standardized terms to their digital heritage. Terms are descriptions of concepts or entities and make heritage easier to find for anyone interested in it. Yet it is quite a challenge for institutions to use terms.
This paper describes the steps taken to model a valency lexicon for Latin (Latin Vallex) according to the principles of the Linguistic Linked Open Data standards, and to interlink its valency frames with the lexical senses recorded in a manually checked subset of the Latin WordNet. The valency lexicon and the WordNet share lexical entries and are part of the LiLa Knowledge Base, which interlinks multiple linguistic resources for Latin.