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Scientific Information Research

Keywords

entity relation Extraction; method entity; automatic generation; syntactic template; seed learning

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.

Digital Object Identifier (DOI)

10.19809/j.cnki.kjqbyj.2025.01.003

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