Leveraging recurrent phrase structure in large-scale ontology translation

This paper presents a process for leveraging structural relationships and reusablephrases when translating large-scale ontologies. Digital libraries are becoming more and
more prevalent. An important step in providing universal access to such material is to pro-
vide multi-lingual access to the underlying principles of organization via ontologies,
thesauri, and controlled vocabularies. Machine translation of these resources requires high
accuracy and a deep vocabulary. Human input is often required, but full manual translation
can be slow and expensive. We report on a cost-effective approach to ontology translation.
We describe our technique of prioritization, our process of collecting aligned translations
and generating a new lexicon, and the resulting improvement to translation system output.
Our preliminary evaluation indicates that this technique provides significant cost savings
for human-assisted translation. The process we developed can be applied to ontologies in
other domains and is easily incorporated into other translation systems.