@inproceedings{weiwei-etal-2024-ji,
title = "基于大小模型结合与半监督自训练方法的古文事件抽取",
author = "Weiwei, Fu and
Shiquan, Wang and
Ruiyu, Fang and
Mengxiang, Li and
Zhongjiang, He and
Yongxiang, Li and
Shuangyong, Song",
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-3.19/",
pages = "172--177",
language = "zho",
abstract = "{\textquotedblleft}本文描述了队伍{\textquotedblleft}TeleAI{\textquotedblright}在CCL2024古文历史事件类型抽取评测任务(CHED2024)中提交的参赛系统。该任务旨在自动识别出古代文本中的事件触发词与事件类型,其中事件类型判别被分为粗粒度和细粒度的事件类型判别两部分。为了提高古文历史事件类型抽取的性能,我们结合了大模型和小模型,并采用了半监督自训练的方法。在最终的评估中,我们在触发词识别任务得分0.763,粗粒度事件类型判别任务得分0.842,细粒度事件类型判别任务得分0.779,综合得分0.791,在所有单项任务和综合评分上均排名第一。{\textquotedblright}"
}
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<abstract>“本文描述了队伍“TeleAI”在CCL2024古文历史事件类型抽取评测任务(CHED2024)中提交的参赛系统。该任务旨在自动识别出古代文本中的事件触发词与事件类型,其中事件类型判别被分为粗粒度和细粒度的事件类型判别两部分。为了提高古文历史事件类型抽取的性能,我们结合了大模型和小模型,并采用了半监督自训练的方法。在最终的评估中,我们在触发词识别任务得分0.763,粗粒度事件类型判别任务得分0.842,细粒度事件类型判别任务得分0.779,综合得分0.791,在所有单项任务和综合评分上均排名第一。”</abstract>
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%0 Conference Proceedings
%T 基于大小模型结合与半监督自训练方法的古文事件抽取
%A Weiwei, Fu
%A Shiquan, Wang
%A Ruiyu, Fang
%A Mengxiang, Li
%A Zhongjiang, He
%A Yongxiang, Li
%A Shuangyong, Song
%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 weiwei-etal-2024-ji
%X “本文描述了队伍“TeleAI”在CCL2024古文历史事件类型抽取评测任务(CHED2024)中提交的参赛系统。该任务旨在自动识别出古代文本中的事件触发词与事件类型,其中事件类型判别被分为粗粒度和细粒度的事件类型判别两部分。为了提高古文历史事件类型抽取的性能,我们结合了大模型和小模型,并采用了半监督自训练的方法。在最终的评估中,我们在触发词识别任务得分0.763,粗粒度事件类型判别任务得分0.842,细粒度事件类型判别任务得分0.779,综合得分0.791,在所有单项任务和综合评分上均排名第一。”
%U https://aclanthology.org/2024.ccl-3.19/
%P 172-177
Markdown (Informal)
[基于大小模型结合与半监督自训练方法的古文事件抽取](https://aclanthology.org/2024.ccl-3.19/) (Weiwei et al., CCL 2024)
ACL
- Fu Weiwei, Wang Shiquan, Fang Ruiyu, Li Mengxiang, He Zhongjiang, Li Yongxiang, and Song Shuangyong. 2024. 基于大小模型结合与半监督自训练方法的古文事件抽取. In Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations), pages 172–177, Taiyuan, China. Chinese Information Processing Society of China.