@inproceedings{hu-etal-2023-yi,
title = "汉语被动结构解析及其在{CAMR}中的应用研究(Parsing of Passive Structure in {C}hinese and Its Application in {CAMR})",
author = "Hu, Kang and
Qu, Weiguang and
Wei, Tingxin and
Zhou, Junsheng and
Li, Bin and
Gu, Yanhui",
editor = "Sun, Maosong and
Qin, Bing and
Qiu, Xipeng and
Jiang, Jing and
Han, Xianpei",
booktitle = "Proceedings of the 22nd Chinese National Conference on Computational Linguistics",
month = aug,
year = "2023",
address = "Harbin, China",
publisher = "Chinese Information Processing Society of China",
url = "https://aclanthology.org/2023.ccl-1.45",
pages = "502--522",
abstract = "{``}汉语被动句是一种重要的语言现象。本文采用BIO结合索引的标注方法,对被动句中的被动结构进行了细粒度标注,提出了一种基于BERT-wwm-ext预训练模型和双仿射注意力机制的CRF序列标注模型,实现对汉语被动句中内部结构的自动解析,F1值达到97.31{\%}。本文提出的模型具有良好的泛化性,实验证明,利用本文模型的被动结构解析结果对CAMR图后处理,能有效提高CAMR被动句解析任务的性能。{''}",
language = "Chinese",
}
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<abstract>“汉语被动句是一种重要的语言现象。本文采用BIO结合索引的标注方法,对被动句中的被动结构进行了细粒度标注,提出了一种基于BERT-wwm-ext预训练模型和双仿射注意力机制的CRF序列标注模型,实现对汉语被动句中内部结构的自动解析,F1值达到97.31%。本文提出的模型具有良好的泛化性,实验证明,利用本文模型的被动结构解析结果对CAMR图后处理,能有效提高CAMR被动句解析任务的性能。”</abstract>
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%0 Conference Proceedings
%T 汉语被动结构解析及其在CAMR中的应用研究(Parsing of Passive Structure in Chinese and Its Application in CAMR)
%A Hu, Kang
%A Qu, Weiguang
%A Wei, Tingxin
%A Zhou, Junsheng
%A Li, Bin
%A Gu, Yanhui
%Y Sun, Maosong
%Y Qin, Bing
%Y Qiu, Xipeng
%Y Jiang, Jing
%Y Han, Xianpei
%S Proceedings of the 22nd Chinese National Conference on Computational Linguistics
%D 2023
%8 August
%I Chinese Information Processing Society of China
%C Harbin, China
%G Chinese
%F hu-etal-2023-yi
%X “汉语被动句是一种重要的语言现象。本文采用BIO结合索引的标注方法,对被动句中的被动结构进行了细粒度标注,提出了一种基于BERT-wwm-ext预训练模型和双仿射注意力机制的CRF序列标注模型,实现对汉语被动句中内部结构的自动解析,F1值达到97.31%。本文提出的模型具有良好的泛化性,实验证明,利用本文模型的被动结构解析结果对CAMR图后处理,能有效提高CAMR被动句解析任务的性能。”
%U https://aclanthology.org/2023.ccl-1.45
%P 502-522
Markdown (Informal)
[汉语被动结构解析及其在CAMR中的应用研究(Parsing of Passive Structure in Chinese and Its Application in CAMR)](https://aclanthology.org/2023.ccl-1.45) (Hu et al., CCL 2023)
ACL