A system for coreference resolution for the clinical narrative

Abstract:

Objective To research computational methods for coreference resolution in the clinical narrative and build a system implementing the best methods. Methods The Ontology Development and Information Extraction corpus annotated for coreference relations consists of 7214 coreferential markables, forming 5992 pairs and 1304 chains. We trained classifiers with semantic, syntactic, and surface features pruned by feature selection. For the three system components—for the resolution of relative pronouns, personal pronouns, and noun phrases—we experimented with support vector machines with linear and radial basis function (RBF) kernels, decision trees, and perceptrons. Evaluation of algorithms and varied feature sets was performed using standard metrics. Results The best performing combination is support vector machines with an RBF kernel and all features (MUC score=0.352 …