@inproceedings{sheng-etal-2020-yi,
title = "汉语否定焦点识别研究:数据集与基线系统(Research on {C}hinese Negative Focus Identification: Dataset and Baseline)",
author = "Sheng, Jiaxuan and
Zou, Bowei and
Shen, Longxiang and
Ye, Jing and
Hong, Yu",
editor = "Sun, Maosong and
Li, Sujian and
Zhang, Yue and
Liu, Yang",
booktitle = "Proceedings of the 19th Chinese National Conference on Computational Linguistics",
month = oct,
year = "2020",
address = "Haikou, China",
publisher = "Chinese Information Processing Society of China",
url = "https://aclanthology.org/2020.ccl-1.51",
pages = "550--560",
abstract = "自然语言文本中存在大量否定语义表达,否定焦点识别任务作为更细粒度的否定语义分析,近年来开始受到自然语言处理学者的关注。该任务旨在识别句子中被否定词修饰和强调的文本片段,其对自然语言处理的下游任务,如情感分析、观点挖掘等具有重要意义。与英语相比,目前面向汉语的否定焦点识别研究彶展缓慢,其主要原因是尚未有中文数据集为模型提供训练和测试数据。为解决上述问题,本文在汉语否定与不确定语料库上进行了否定焦点的标注工作,初步探索了否定焦点在汉语上的语言现象,并构建了一个包含5,762个样本的数据集。同时,本文还提出了一个基于神经网络模型的基线系统,为后续相关研究提供参照。",
language = "Chinese",
}
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<abstract>自然语言文本中存在大量否定语义表达,否定焦点识别任务作为更细粒度的否定语义分析,近年来开始受到自然语言处理学者的关注。该任务旨在识别句子中被否定词修饰和强调的文本片段,其对自然语言处理的下游任务,如情感分析、观点挖掘等具有重要意义。与英语相比,目前面向汉语的否定焦点识别研究彶展缓慢,其主要原因是尚未有中文数据集为模型提供训练和测试数据。为解决上述问题,本文在汉语否定与不确定语料库上进行了否定焦点的标注工作,初步探索了否定焦点在汉语上的语言现象,并构建了一个包含5,762个样本的数据集。同时,本文还提出了一个基于神经网络模型的基线系统,为后续相关研究提供参照。</abstract>
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%0 Conference Proceedings
%T 汉语否定焦点识别研究:数据集与基线系统(Research on Chinese Negative Focus Identification: Dataset and Baseline)
%A Sheng, Jiaxuan
%A Zou, Bowei
%A Shen, Longxiang
%A Ye, Jing
%A Hong, Yu
%Y Sun, Maosong
%Y Li, Sujian
%Y Zhang, Yue
%Y Liu, Yang
%S Proceedings of the 19th Chinese National Conference on Computational Linguistics
%D 2020
%8 October
%I Chinese Information Processing Society of China
%C Haikou, China
%G Chinese
%F sheng-etal-2020-yi
%X 自然语言文本中存在大量否定语义表达,否定焦点识别任务作为更细粒度的否定语义分析,近年来开始受到自然语言处理学者的关注。该任务旨在识别句子中被否定词修饰和强调的文本片段,其对自然语言处理的下游任务,如情感分析、观点挖掘等具有重要意义。与英语相比,目前面向汉语的否定焦点识别研究彶展缓慢,其主要原因是尚未有中文数据集为模型提供训练和测试数据。为解决上述问题,本文在汉语否定与不确定语料库上进行了否定焦点的标注工作,初步探索了否定焦点在汉语上的语言现象,并构建了一个包含5,762个样本的数据集。同时,本文还提出了一个基于神经网络模型的基线系统,为后续相关研究提供参照。
%U https://aclanthology.org/2020.ccl-1.51
%P 550-560
Markdown (Informal)
[汉语否定焦点识别研究:数据集与基线系统(Research on Chinese Negative Focus Identification: Dataset and Baseline)](https://aclanthology.org/2020.ccl-1.51) (Sheng et al., CCL 2020)
ACL