Semantic splitting of German medical compounds

Abstract

Compounding is widespread in highly inflectional languages with a quarter of all nouns created by composition. In our field of study, the German medical language, the amount of compounds significantly outnumbers this figure with 64%. Thus, their correct splitting is a high-impact preprocessing step for any NLP-based application. In this work we address two challenges of medical decomposition: First, we introduce the consideration of unknown constituents in order to split compounds that were not recognized as such so far. Second, our approach builds on the corpus-based approach of Koehn and Knight and adds semantic knowledge from domain ontologies to increase the accuracy during disambiguation of the various split options. Using this first-of-a-kind semantic approach in a study on decomposition of German medical compounds, we outperform the existing approaches by far.