@inproceedings{hongying-etal-2024-ji,
title = "基于关系抽取的中文意合图语义解析方法研究",
author = "Hongying, Huo and
Shaoping, Huang and
Pengyuan, Liu",
editor = "Lin, Hongfei and
Tan, Hongye and
Li, Bin",
booktitle = "Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations)",
month = jul,
year = "2024",
address = "Taiyuan, China",
publisher = "Chinese Information Processing Society of China",
url = "https://aclanthology.org/2024.ccl-3.7/",
pages = "62--71",
language = "zho",
abstract = "{\textquotedblleft}意合图是以事件为中心的单根有向语义表征图,在语义计算与应用方面具有重要价值。在乃乃乌中串丰串临中文意合图语义解析评测任务中,为克服意合图为单根有向图、意合图包含隐性事件词以及意合图的语义关系类型十分丰富,导致关系类型过多等诸多方面的难点,本文提出一种将该任务转换为关系抽取的方法。该方法首先对标签进行扩充,分为正向标签和反向标签;其次,对输入进行扩充,将隐性事件词添加到输入中,无须额外对隐性事词进行预测;最后,细分为不带隐性事件词和带隐性事件词的关系抽取任务。实验结果表明,本文方法在官方盲测集上的F1值为64.44{\%},高出基线模型33.41{\%},证明了本文方法的有效性。{\textquotedblright}"
}
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<abstract>“意合图是以事件为中心的单根有向语义表征图,在语义计算与应用方面具有重要价值。在乃乃乌中串丰串临中文意合图语义解析评测任务中,为克服意合图为单根有向图、意合图包含隐性事件词以及意合图的语义关系类型十分丰富,导致关系类型过多等诸多方面的难点,本文提出一种将该任务转换为关系抽取的方法。该方法首先对标签进行扩充,分为正向标签和反向标签;其次,对输入进行扩充,将隐性事件词添加到输入中,无须额外对隐性事词进行预测;最后,细分为不带隐性事件词和带隐性事件词的关系抽取任务。实验结果表明,本文方法在官方盲测集上的F1值为64.44%,高出基线模型33.41%,证明了本文方法的有效性。”</abstract>
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%0 Conference Proceedings
%T 基于关系抽取的中文意合图语义解析方法研究
%A Hongying, Huo
%A Shaoping, Huang
%A Pengyuan, Liu
%Y Lin, Hongfei
%Y Tan, Hongye
%Y Li, Bin
%S Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations)
%D 2024
%8 July
%I Chinese Information Processing Society of China
%C Taiyuan, China
%G zho
%F hongying-etal-2024-ji
%X “意合图是以事件为中心的单根有向语义表征图,在语义计算与应用方面具有重要价值。在乃乃乌中串丰串临中文意合图语义解析评测任务中,为克服意合图为单根有向图、意合图包含隐性事件词以及意合图的语义关系类型十分丰富,导致关系类型过多等诸多方面的难点,本文提出一种将该任务转换为关系抽取的方法。该方法首先对标签进行扩充,分为正向标签和反向标签;其次,对输入进行扩充,将隐性事件词添加到输入中,无须额外对隐性事词进行预测;最后,细分为不带隐性事件词和带隐性事件词的关系抽取任务。实验结果表明,本文方法在官方盲测集上的F1值为64.44%,高出基线模型33.41%,证明了本文方法的有效性。”
%U https://aclanthology.org/2024.ccl-3.7/
%P 62-71
Markdown (Informal)
[基于关系抽取的中文意合图语义解析方法研究](https://aclanthology.org/2024.ccl-3.7/) (Hongying et al., CCL 2024)
ACL
- Huo Hongying, Huang Shaoping, and Liu Pengyuan. 2024. 基于关系抽取的中文意合图语义解析方法研究. In Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations), pages 62–71, Taiyuan, China. Chinese Information Processing Society of China.