TAKELAB: Medical Information Extraction and Linking with MINERAL
Goran Glavaš · 2015
Medical texts are filled with mentions of diseases, disorders, and other clinical conditions, with many different surface forms relating to the same condition.We describe MINERAL, a system for extraction and normalization of disease mentions in clinical text, with which we participated in the Task 14 of SemEval 2015 evaluation campaign.MINERAL relies on a conditional random fields-based model with a rich set of features for mention detection, and a semantic textual similarity measure for entity linking.MINERAL reaches joint extraction and linking performance of 75.9% relaxed F 1score (strict score of 72.7%) and ranks fourth among 16 participating teams.