Towards practical temporal relation extraction from clinical notes: An analysis of direct temporal relations

Following the conventions developed in general domain, most of the current work on clinical temporal relation identification aims to identify a comprehensive set of temporal relations from source documents. This includes both explicit relations that is described in the documents and implicit relations that are identifiable only through inference. Although such an approach may provide a complete view of temporal information provided in a document, some temporal relations may not be practically essential, depending on the clinical application at hand. In addition, the performances of current systems that identify both explicit and implicit relations are still low and how to enhance the performances to be enough for practical use is not clear yet. In this paper, we propose focus on a subset of temporal relations, in order to provide insights into how to develop practically useful temporal information extraction methods for clinical text. We focus on "direct" temporal relations, which are intra-sentential temporal relations between a time expression and an event mention with limited syntactic distance. A corpus of 120 discharge summaries is constructed, leveraging an existing corpus, the 2012 i2b2 corpus. We show that the direct temporal relations constitute a major category of temporal relations. In addition, we show that the performance of the state-of-the art temporal relation extraction system, which is developed for both implicit and explicit relations, on direct temporal relations is still low. This indicates the need for development of methods tailored to direct temporal relations.