@inproceedings{chang-etal-2021-nao,
title = "脑卒中疾病电子病历实体及实体关系标注语料库构建(Corpus Construction for Named-Entity and Entity Relations for Electronic Medical Records of Stroke Disease)",
author = "Chang, Hongyang and
Zan, Hongying and
Ma, Yutuan and
Zhang, Kunli",
editor = "Li, Sheng and
Sun, Maosong and
Liu, Yang and
Wu, Hua and
Liu, Kang and
Che, Wanxiang and
He, Shizhu and
Rao, Gaoqi",
booktitle = "Proceedings of the 20th Chinese National Conference on Computational Linguistics",
month = aug,
year = "2021",
address = "Huhhot, China",
publisher = "Chinese Information Processing Society of China",
url = "https://aclanthology.org/2021.ccl-1.57",
pages = "633--642",
abstract = "本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)。所构建的语料库共包含命名实体10594个,实体关系14457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{\%}。",
language = "Chinese",
}
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<abstract>本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)。所构建的语料库共包含命名实体10594个,实体关系14457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>
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%0 Conference Proceedings
%T 脑卒中疾病电子病历实体及实体关系标注语料库构建(Corpus Construction for Named-Entity and Entity Relations for Electronic Medical Records of Stroke Disease)
%A Chang, Hongyang
%A Zan, Hongying
%A Ma, Yutuan
%A Zhang, Kunli
%Y Li, Sheng
%Y Sun, Maosong
%Y Liu, Yang
%Y Wu, Hua
%Y Liu, Kang
%Y Che, Wanxiang
%Y He, Shizhu
%Y Rao, Gaoqi
%S Proceedings of the 20th Chinese National Conference on Computational Linguistics
%D 2021
%8 August
%I Chinese Information Processing Society of China
%C Huhhot, China
%G Chinese
%F chang-etal-2021-nao
%X 本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)。所构建的语料库共包含命名实体10594个,实体关系14457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%。
%U https://aclanthology.org/2021.ccl-1.57
%P 633-642
Markdown (Informal)
[脑卒中疾病电子病历实体及实体关系标注语料库构建(Corpus Construction for Named-Entity and Entity Relations for Electronic Medical Records of Stroke Disease)](https://aclanthology.org/2021.ccl-1.57) (Chang et al., CCL 2021)
ACL