计算机工程2025，Vol.51Issue(11)：100-111,12.DOI:10.19678/j.issn.1000-3428.0069745
面向铜基复合材料文献的复杂实体关系抽取方法
Complex Entity Relation Extraction Method for Copper-Based Composite Material Literatures
摘要
Abstract
Extracting entities and relations with precision from the copper-based composite material literature is imperative for constructing knowledge graphs and propelling research in materials science.The complex nature of entities in this domain,such as nested and discontinuous entities,along with the prevalence of Single Entity Overlap(SEO)relations,renders existing techniques for entity and relation extraction inadequate.To address this issue,this study presents a dedicated dataset for entity relation extraction from copper-based composite materials and introduces a novel two-stage extraction method.The initial phase combines inter-word relation classification with Bidirectional Gated Recurrent Unit(BiGRU)and multi-scale dilated convolutional networks,thereby augmenting the model's capacity to discern entity boundaries.The second phase involves annotating entity spans within text sequences and incorporating an entity type attention mechanism into a relation classification model.This method leverages multifaceted feature representation to classify relations.On three established public datasets-Matscholar,SOFC,and MSP-as well as the CBCM-IE dataset curated for this research,the proposed method outperforms baseline methodologies with improvements of 5.91(Precision),3.56(Recall),and 3.63(F1 score)percentage points,demonstrating its efficacy for entity relation extraction in the context of copper-based composite materials.关键词
命名实体识别/关系抽取/预训练语言模型/铜基复合材料Key words
named entity recognition/relation extraction/pretrained language model/copper-based composite material分类
计算机与自动化引用本文复制引用
郭桦宜,游进国,耿齐祁,陶静梅,易健宏..面向铜基复合材料文献的复杂实体关系抽取方法[J].计算机工程,2025,51(11):100-111,12.基金项目
国家自然科学基金(62062046). （62062046）
