Task-Oriented Extraction of Temporal Information: The Case of Clinical Narratives

Most recent work on temporal relation extraction from text has addressed text drawn from the newswire domain and has attempted to extract all temporal relational information, as specified by proposed temporal annotation schemes such as TimeML. In this paper we explore the task of extracting restricted amounts of temporal information in support of an information extraction application in the medical domain, specifically that of extracting information about times of clinical investigations (X-rays, ultrasounds, etc.) from clinic letters. We describe the task, the corpus and evaluation data we have assembled, a baseline algorithm for extracting temporal relations between temporal expressions and clinical investigation events, and present evaluation results for the algorithm. Overall scores of precision 73.83% and recall 58.70% are promising for a simple baseline approach and suggest that extracting only a restricted subset of the temporal information available in a text may be a sensible way to proceed in the context of specific applications.