DE-AA:基于词对距离嵌入和轴向注意力机制的实体关系联合抽取模型  

Joint Extraction of Entities and Relations Based on Word-Pair Distance Embedding and Axial Attention Mechanism

作　　者：张梦赢 沈海龙[1] ZHANG Mengying;SHEN Hailong(School of Science,Northeastern University,Shenyang 110819,China)

机构地区：[1]东北大学理学院,沈阳110819

出　　处：《计算机科学》2024年第12期234-241,共8页Computer Science

摘　　要：实体关系联合抽取为知识图谱的构建提供了关键的技术支持,而重叠关系问题一直都是联合抽取模型研究的重点。现有的方法大多采用多步骤的建模方法,虽然在解决重叠关系问题上取得了很好的效果,但产生了曝光偏差问题。为同时解决重叠关系和曝光偏差问题,提出了一种基于词对距离嵌入和轴向注意力机制的实体关系联合抽取方法(DE-AA)。首先,构建代表词对关系的表特征,加入词对距离特征信息优化其表示;其次,应用基于行注意力和列注意力的轴向注意力模型去增强表特征,在融合全局特征的同时能够降低计算复杂度;最后,将表特征映射到各关系空间中,生成特定关系下的词对关系表,并使用表格填充法为表中各项分配标签,以三重分类的方式进行三元组的抽取。在公开数据集NYT和WebNLG上评估了所提出的模型,实验结果表明其与其他基线模型相比取得了更好的性能,且在处理重叠关系或多重关系问题上优势显著。The joint extraction of entities and relations provides key technical support for the construction of knowledge graphs,and the problem of overlapping relations has always been the focus of joint extraction model research.Many of the existing me-thods use multi-step modeling methods.Although they have achieved good results in solving the problem of overlapping relations,they have produced the problem of exposure bias.In order to solve the problem of overlapping relations and exposure bias at the same time,a joint entities and relations extraction method(DE-AA)based on word-pair distance embedding and axial attention mechanism is proposed.Firstly,the table features of the representative word-pair relation are constructed,and the word-pair distance feature information is added to optimize its representation.Secondly,the axial attention model based on row attention and column attention is applied to enhance the table features,which can reduce the computational complexity while fusing the global features.Finally,the table features are mapped to each relation space to generate the relation-specific word-pair relation table,and the table filling method is used to assign labels to each item in the table,and the triples are extracted by triple classification.The proposed model is evaluated on the public datasets NYT and WebNLG.Experimental results show that the proposed model achieves better performance than other baseline models,and has significant advantages in dealing with overlapping relations or multiple relations.

关 键 词：实体关系联合抽取 轴向注意力机制 词对距离嵌入 表格填充法 

分 类 号：TP391.1[自动化与计算机技术—计算机应用技术]