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Objective: To build a comprehensive corpus covering syntactic and semanticannotations of Chinese clinical texts with corresponding annotation guidelinesand methods as well as to develop tools trained on the annotated corpus, whichsupplies baselines for research on Chinese texts in the clinical domain.  Materials and methods: An iterative annotation method was proposed to trainannotators and to develop annotation guidelines. Then, by using annotationquality assurance measures, a comprehensive corpus was built, containingannotations of part-of-speech (POS) tags, syntactic tags, entities, assertions,and relations. Inter-annotator agreement (IAA) was calculated to evaluate theannotation quality and a Chinese clinical text processing and informationextraction system (CCTPIES) was developed based on our annotated corpus.  Results: The syntactic corpus consists of 138 Chinese clinical documents with47,424 tokens and 2553 full parsing trees, while the semantic corpus includes992 documents that annotated 39,511 entities with their assertions and 7695relations. IAA evaluation shows that this comprehensive corpus is of goodquality, and the system modules are effective.  Discussion: The annotated corpus makes a considerable contribution to naturallanguage processing (NLP) research into Chinese texts in the clinical domain.However, this corpus has a number of limitations. Some additional types ofclinical text should be introduced to improve corpus coverage and activelearning methods should be utilized to promote annotation efficiency.  Conclusions: In this study, several annotation guidelines and an annotationmethod for Chinese clinical texts were proposed, and a comprehensive corpuswith its NLP modules were constructed, providing a foundation for further studyof applying NLP techniques to Chinese texts in the clinical domain.

Building a comprehensive syntactic and semantic corpus of Chinese clinical texts