|Table of Contents|

Relationship Extraction of Entities About Rice Diseases and Insect Pests Based on FastBert(PDF)

南京师范大学学报（工程技术版）[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2023年01期
Page:
33-38
Research Field:
计算机科学与技术
Publishing date:

Info

Title:
Relationship Extraction of Entities About Rice Diseases and Insect Pests Based on FastBert
Author(s):
Zhou Ye1; Xu Xiangying1; 2; Zhang Yonglong1; Chen Jiayun1; Wang Hongjiang1
(1.College of Information Engineering,Yangzhou University,Yangzhou 225012 China) (2.Joint International Research Laboratory of Agriculture and Agri-Product Safety,the Ministry of Education of China,Yangzhou 225127 China)
Keywords:
rice diseases and insect pests; knowledge graph; relationship extraction
PACS:
TP391.1
DOI:
10.3969/j.issn.1672-1292.2023.01.005
Abstract:
A FastBert model based Chinese entity relationship extraction method is proposed to extract the entities and relationships required for rice pest and disease knowledge graph. First of all, on the basis of Chinese corpus collected, a tool named Hanlp and a agricultural dictionary are used to extract the domain entities related to rice diseases and insect pests. According to the characteristics of the relationship between entities, seven types of diseases and pests are defined, such as alias, harm parts, suffer region, prevention and treatment, etc. Based on word embedding and sentence embedding, the extraction of the relation of rice diseases and insect pests is realized through the FastBert model. And the results are compared with those of other Bert related models. It shows that the FastBert model is better than other Bert related models in the relationship extraction task of entities in the Chinese corpus of rice diseases and insect pest. The F1 value obtained by the FastBert model is 0.72, and the accuracy of the model is 0.69. This method provides a reference for automated construction of Chinese knowledge map of agricultural pests and diseases.

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Last Update: 2023-03-15