基于NPN融入词性注意力机制的中文事件探测  

A Chinese event detection method based on nugget proposal network with part-of-speech attention mechanism

作　　者：胡庆孟 王红斌[1,2] 王俊钟[3] HU Qing-meng;WANG Hong-bin;WANG Jun-zhong(Faculty of Information Engineering and Automation,Kunming University of Science and Technology,Kunming 650500;Yunnan Key Laboratory of Artificial Intelligence,Kunming University of Science and Technology,Kunming 650500;Information Center,Department of Industry and Information Technology of Yunnan Province,Kunming 650011,China)

机构地区：[1]昆明理工大学信息工程与自动化学院,云南昆明650500 [2]昆明理工大学云南省人工智能重点实验室,云南昆明650500 [3]云南省工业和信息化厅信息中心,云南昆明650011

出　　处：《计算机工程与科学》2023年第8期1490-1497,共8页Computer Engineering & Science

基　　金：国家自然科学基金(61966020)。

摘　　要：事件探测主要研究触发词探测以及事件类型识别。现阶段基于深度学习的模型大部分集中在利用语义角色信息、句法依存树信息以及预训练模型方面,忽略了词性的重要性。针对这个问题,提出基于块提取网络融入词性注意力机制的中文事件探测方法,首先基于NLP词性标注工具获得词性序列,然后使用CBOW算法获得词性嵌入,最后在模型中使用词性嵌入计算词性注意力用于事件探测。在ACE2005数据集上进行实验,融入词性注意力后模型在事件探测任务上的F1分数分别提升了3.8%和2.4%,表明了该方法的有效性。Event detection mainly studies trigger word detection and event type recognition.At pre-sent,most models based on deep learning focus on semantic role information,syntactic dependency tree information and pre-training models,but ignore the importance of parts of speech.To solve this problem,this paper proposes a Chinese event detection method based on nugget proposal network with part-of-speech attention mechanism.The method firstly obtains part-of-speech sequence based on NLP part-of-speech tagging tool,then uses the CBOW algorithm to obtain part-of-speech embedding,and finally uses part-of-speech embedding in the model to calculate part-of-speech attention for event detection.Experiments on the ACE2005 show that the F1 score of the model with part-of-speech attention is improved by 3.8%and 2.4%respectively on the event detection task,which proves the effectiveness of the method.

关 键 词：块提取网络 词性向量 词性注意力 事件探测 事件抽取 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]