LIMSI @ CLEF eHealth 2015 - task 1b

This paper presents LIMSI's participation in the Clinical Named En- tity Recognition task at the CLEF eHealth 2015 workshop. Our system is based on the combination of three classifiers: two CRFs to detect entities' boundaries and a SVM to identify their semantic class. These classifiers rely on a set of fea- tures used in state-of-the-art classification systems, including token/POS ngrams, morphologic features, and dictionary consultation in language-dependent exter- nal sources. Although our system was not fully operational when we submitted our run, we obtained above-average scores. In this paper we also present two additional runs which improve on the submitted system.