Abstract
In this paper we present an approach for the translation and classification of short texts in one step. Our work lays in the tradition of Domain-Driven Word Sense Disambiguation, though a major emphasis is given to domain ontologies as the right tool for sense-tagging and topic detection of short texts which, by their nature, are known to be reluctant to statistical treatment. We claim that in a scenario where users can annotate knowledge items using different languages, domain ontologies can prove very suitable for driving the word disambiguation and topic classification tasks. In this way, two tasks are gainfully collapsed in a single one. Although this study is still in its infancy, in what follows we are able to articulate motivations, design, workflow analysis, and concrete evolutions envisioned for our tool.