脑卒中疾病电子病历实体及实体关系标注语料库构建

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中文信息学报 ›› 2022, Vol. 36 ›› Issue (8) : 37-45.

语言资源建设与应用

脑卒中疾病电子病历实体及实体关系标注语料库构建

常洪阳^1,2,昝红英^1,2,马玉团^1,2,张坤丽^1,2

作者信息 +

Corpus Construction for Named-Entity and Entity Relations for Electronic Medical Records of Stroke Disease

CHANG Hongyang^1,2, ZAN Hongying^1,2, MA Yutuan^1,2, ZHANG Kunli ^1,2

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摘要

该文探讨了在脑卒中疾病中文电子病历文本中实体及实体间关系的标注问题,提出了适用于脑卒中疾病电子病历文本的实体及实体关系标注体系和规范。在标注体系和规范的指导下,进行了多轮的人工标注及校正工作,完成了158万余字的脑卒中电子病历文本实体及实体关系的标注工作。构建了脑卒中电子病历实体及实体关系标注语料库(Stroke Electronic Medical Record entity and entity related Corpus, SEMRC)。该文所构建的语料库共包含命名实体10 594个,实体关系14 457个。实体名标注一致率达到85.16％,实体关系标注一致率达到94.16％。

Abstract

This paper discusses the labeling of Named-Entity and Entity Relations in Chinese electronic medical records of stroke disease, and proposes a system and norms for labeling entity and entity relations that are suitable for content and characteristics of electronic medical records of stroke disease. Based on the guidance of the labeling system and norms, after multiple rounds of labeling and correction, we completed the labeling of entities and relationships in electronic medical record of stroke disease more than 1.5 million words(Stroke Electronic Medical Record entity and entity related Corpus, SEMRC). The constructed corpus contains 10,594 named entities and 14,597 entity relationships. The consistency of named entity reached 0.8516, and that of entity relationship reached 0.9416.

导出引用

常洪阳,昝红英,马玉团,张坤丽. 脑卒中疾病电子病历实体及实体关系标注语料库构建. 中文信息学报. 2022, 36(8): 37-45

CHANG Hongyang, ZAN Hongying, MA Yutuan, ZHANG Kunli. Corpus Construction for Named-Entity and Entity Relations for Electronic Medical Records of Stroke Disease. Journal of Chinese Information Processing. 2022, 36(8): 37-45

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基金

河南省医学科技攻关计划省部共建项目(SB201901021);河南省高等学校重点科研项目(20A520038);郑州市协同创新重大专项科技攻关项目(20XTZX11020)

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2022-02-21	2022-09-26
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2022-09-26

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