Corpus construction for named entities and entity relations on Chinese electronic medical records

An electronic medical record (EMR) is a patient's individual medical record written by health care providers and stored in digital format in which much medical knowledge and information about patient's personal health conditions are kept. The construction of annotated corpus for named entities and entity relations on EMR is a primary and fundamental task for information extraction which plays important role in clinical decision support, practice of evidence-based medicine, and other medical applications. Based on survey of current research on corpus construction for named entities and entity relations on EMR, this research proposes an annotation scheme for named entities and entity relations on Chinese electronic medical records (CEMR) according to characteristics of the records. Under the supervision of physicians, a complete and detailed annotation specification on CEMR is formulated, and an annotated corpus with high agreement is constructed. The corpus comprises 992 medical text documents, and inter-annotator agreement (IAA) of named entity annotations and entity relation annotations attain 0.922 and 0.895, respectively. The work presented in this paper builds substantial foundations for the subsequent research on information extraction in CEMR.