We explore and evaluate the usefulness of semantic annotation, particularly semantic relations, in cross-language information retrieval in the medical domain. As the baseline for automatic semantic annotation we use UMLS, which specifies semantic relations between medical concepts. We developed two methods to improve the accuracy and yield of relations in CLIR: a method for relation filtering and a method to discover new relation instances. Both techniques were applied to a corpus of English and German medical abstracts and evaluated for their efficiency in CLIR.
Results show that filtering reduces recall without significant increase in precision, while discovery of new relation instances indeed proved a successful method to improve retrieval.