广西师范大学学报（自然科学版）2025，Vol.43Issue(3)：12-22,11.DOI:10.16088/j.issn.1001-6600.2024092804
基于掩码注意力与多特征卷积网络的关系抽取方法
Relational Extraction Method Based on Mask Attention and Multi-feature Convolutional Networks
摘要
Abstract
Relation extraction aims to extract the semantic relationship between two named entities.Recently,prompt learning has unified the optimization objectives of pre-trained language models and fine-tuning by concatenating prompt templates and performing mask prediction,achieving excellent performance in the field of relationship extraction.However,weak semantic associations between fixed prompt templates and relation instances are observed,which limits the model's ability to perceive complex relationships.To address this issue,a relation extraction method based on mask attention and multi-feature convolution networks is proposed.The tri-affine attention mechanism is adopted to interactively map the mask in the prompt template with the semantic space of the original text.Two-dimensional mask semantics are then formed through this process.Multi-feature convolutional networks and multi-layer perceptron are employed to extract relational information from the two-dimensional mask semantics.Explicit semantic dependencies between the mask and the relation instance are established.This approach enhances the semantic perception of complex relationships in prompt models.Performances of 91.4%,91.2%,and 82.6%are achieved on the SemEval,SciERC,and CLTC datasets,respectively.The effectiveness of the proposed method is demonstrated by experimental results.关键词
自然语言处理/关系抽取/提示学习/三仿射注意力机制/卷积神经网络Key words
natural language processing/relation extraction/prompt learning/tri-affine attention mechanism/convolutional neural network分类
信息技术与安全科学引用本文复制引用
卢展跃,陈艳平,杨卫哲,黄瑞章,秦永彬..基于掩码注意力与多特征卷积网络的关系抽取方法[J].广西师范大学学报（自然科学版）,2025,43(3):12-22,11.基金项目
贵州省科学技术基金重点项目([2024]003) （[2024]003）
国家重点研发计划(2023YFC3304500) （2023YFC3304500）
国家自然科学基金(62166007) （62166007）
