Temporal Expression Recognition and Temporal Relationship Extraction from Chinese Narrative Medical Records

As the first step of temporal information understanding, the results of Temporal Expression Recognition will directly affect the further usage of temporal information, such as temporal relationship extraction. For Chinese language, there are many distinct characters both in word morphology and syntax in temporal expression comparing with the western languages where many researches had been done in the last decade. This paper provided a Temporal Expression Recognition and Temporal Relationship Extraction framework focusing on Chinese narrative medical records. Firstly, this study developed a temporal expression syntax based on regular expression through statistical analysis and classification of a medical records corpus which covered 147 medical records from more than 30 clinical departments. The recognizing results showed that the method we proposed could cover most temporal expressions in the narrative medical records. Adhere to the result of temporal expression recognition, a temporal relationship extraction method based on CRF (Conditional Random Fields) was proposed to automatically extract temporal attributes of medical problems from Chinese narrative medical records. The test results showed the accuracy of temporal relationship extraction using the choice template file could reach 86.94%.