基于对span的预判断和多轮分类的实体关系抽取  

Entity relation extraction based on prejudgment and multi-round classification for span

作　　者：佟缘 姚念民[1] TONG Yuan;YAO Nian-min(School of Computer Science and Technology,Dalian University of Technology,Dalian 116024,China)

机构地区：[1]大连理工大学计算机科学与技术学院,辽宁大连116024

出　　处：《计算机工程与科学》2024年第5期916-928,共13页Computer Engineering & Science

摘　　要：针对自然语言处理领域中的实体识别和关系抽取任务,提出一种对词元序列(Token Sequence,又称span)进行预测的模型Smrc。模型整体上利用BERT预训练模型作为编码器,另外包含实体预判断(Pej)、实体多轮分类(Emr)和关系多轮分类(Rmr)3个模块。Smrc模型通过Pej模块的初步判断及Emr模块的多轮实体分类来进行实体识别,再利用Rmr模块的多轮关系分类来判断实体对间的关系,进而完成关系抽取任务。在CoNLL04、SciERC和ADE 3个实验数据集上,Smrc模型的实体识别F1值分别达到89.67%,70.62%和89.56%,关系抽取F1值分别达到73.11%,51.03%和79.89%,相较之前在3个数据集上的最佳模型Spert,Smrc模型凭借实体预判断和实体及关系多轮分类,在2个子任务上其F1值分别提高了0.73%,0.29%,0.61%及1.64%,0.19%,1.05%,表明了该模型的有效性及其优势。Aiming at entity recognition and relation extraction tasks in natural language processing,a model named Smrc is proposed,which makes predictions at the token sequence(span)level.The model uses BERT pre-training model as an encoder and include three modules:entity pre-judgment(Pej),entity multi-round classification(Emr)and relation multi-round classification(Rmr).The Smrc model performs entity recognition through the preliminary judgment of the Pej module and the multi-round entity classification of the Emr module,and then uses the Rmr module’s multi-round relation classification to determine the relationships between entities,thus completing the relation extraction task.On the experimental datasets of CoNLL04,SciERC,and ADE,the F1 values of entity recognition reach 89.67%,70.62%,and 89.56%,respectively,and the F1 values of relation extraction reach 73.11%,51.03%,and 79.89%,respectively.Compared with the previous best model Spert on the three datasets,the Smrc model achieves improvements of 0.73%,0.29%,and 0.61%in entity recognition and 1.64%,0.19%,and 1.05%in relation extraction through entity pre-judgment and multi-round classification of entities and relations,which demonstrates the effectiveness and advantages of the model.

关 键 词：对span的预判断 实体关系抽取 BERT预训练模型 多轮实体分类 多轮关系分类 

分 类 号：TP391.1[自动化与计算机技术—计算机应用技术]