Paper: Discovering Temporal Narrative Containers in Clinical Text

ACL ID W13-1903
Title Discovering Temporal Narrative Containers in Clinical Text
Venue Workshop on Biomedical Natural Language Processing
Year 2013

The clinical narrative contains a great deal of valuable information that is only under- standable in a temporal context. Events, time expressions, and temporal relations convey information about the time course of a patient?s clinical record that must be understood for many applications of inter- est. In this paper, we focus on extracting information about how time expressions and events are related by narrative con- tainers. We use support vector machines with composite kernels, which allows for integrating standard feature kernels with tree kernels for representing structured features such as constituency trees. Our experiments show that using tree kernels in addition to standard feature kernels im- proves F1 classification for this task.