CLNov 7, 2016

Building a comprehensive syntactic and semantic corpus of Chinese clinical texts

arXiv:1611.02091v244 citations
Originality Synthesis-oriented
AI Analysis

This provides a foundational resource for NLP research in the Chinese clinical domain, though it is incremental as it applies existing annotation methods to a new dataset.

The researchers built a comprehensive corpus of Chinese clinical texts with syntactic and semantic annotations, resulting in 138 documents with 47,424 tokens and 2553 parsing trees for syntax, and 992 documents with 39,511 entities and 7695 relations for semantics, with inter-annotator agreement confirming good quality.

Objective: To build a comprehensive corpus covering syntactic and semantic annotations of Chinese clinical texts with corresponding annotation guidelines and methods as well as to develop tools trained on the annotated corpus, which supplies baselines for research on Chinese texts in the clinical domain. Materials and methods: An iterative annotation method was proposed to train annotators and to develop annotation guidelines. Then, by using annotation quality assurance measures, a comprehensive corpus was built, containing annotations of part-of-speech (POS) tags, syntactic tags, entities, assertions, and relations. Inter-annotator agreement (IAA) was calculated to evaluate the annotation quality and a Chinese clinical text processing and information extraction system (CCTPIES) was developed based on our annotated corpus. Results: The syntactic corpus consists of 138 Chinese clinical documents with 47,424 tokens and 2553 full parsing trees, while the semantic corpus includes 992 documents that annotated 39,511 entities with their assertions and 7695 relations. IAA evaluation shows that this comprehensive corpus is of good quality, and the system modules are effective. Discussion: The annotated corpus makes a considerable contribution to natural language processing (NLP) research into Chinese texts in the clinical domain. However, this corpus has a number of limitations. Some additional types of clinical text should be introduced to improve corpus coverage and active learning methods should be utilized to promote annotation efficiency. Conclusions: In this study, several annotation guidelines and an annotation method for Chinese clinical texts were proposed, and a comprehensive corpus with its NLP modules were constructed, providing a foundation for further study of applying NLP techniques to Chinese texts in the clinical domain.

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The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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