Research on a geological entity relation extraction model for gold mine based on BERT

Abstract

Intelligent identification of entity relation is an important method and approach to improve literature mining and analysis, and knowledge extraction of gold mine. This study focuses on the core issues affecting current entity relation extraction of gold mine such as complex entity relation and less manual annotation information, and proposes a BERT (Bidirectional Encoder Representations from Transformer) remotely supervised relation extraction model. The accuracy of relation extraction is increased by optimizing and improving the modules related to geological data coding, geological classification and geological entity filtering. And the effectiveness of the model is verified by the entity relation extraction experiment of 290489 pieces of gold ore documents.

Keywords

• remote supervision
• relation extraction
• bert
• geological entity