科技情报研究2025，Vol.7Issue(1)：30-40,11.DOI:10.19809/j.cnki.kjqbyj.2025.01.003
基于自动生成句法模板的方法类实体关系抽取
Method Entity and Relation Extraction Based on Automatically Generat-ed Syntactic Templates:A Case Study of CSDN Artificial Intelligence Blog
摘要
Abstract
[Purpose/significance]There are many relationships between method entities and application scenarios,problems,organizations and other entities.Extracting these entity relationships helps to capture the development trend of technology and promote the improvement of innovation ability.[Method/process]This paper discusses a method for extracting method entities and relations based on automatically generated syntactic templates.By designing a new adaptive template,the method improves flexibility and adaptability,reducing dependence on large-scale labeled data.Using a small number of seed triples,the method iteratively generates syntactic templates and extracts method entities and relations for the CSDN artificial intelligence topic blog.It also improves the extraction quality using a filter model.[Result/conclusion]After 5 rounds of iterative extraction,the triplet extraction accuracy of the model reaches 55.2%,which is better than the existing general model.The results show that this method can effectively use the limited labeled data to extract method entities and their relationships in specific fields,and provide support for scientific and technological information analysis in academia and industry.关键词
实体关系抽取/方法类实体/自动生成/句法模板/种子学习Key words
entity relation Extraction/method entity/automatic generation/syntactic template/seed learning引用本文复制引用
李奎良,化柏林..基于自动生成句法模板的方法类实体关系抽取[J].科技情报研究,2025,7(1):30-40,11.基金项目
国家社会科学基金重大项目"大数据驱动的科技文献语义评价体系研究"(编号:21&ZD329) （编号:21&ZD329）
