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2021 Vol. 27, No. 3
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HUANG Xusheng, ZHU Yueqin, FU Lijun, LIU Yujiang, TANG Keke, LI Jin. 2021. Research on a geological entity relation extraction model for gold mine based on BERT. Journal of Geomechanics, 27(3): 391-399. doi: 10.12090/j.issn.1006-6616.2021.27.03.035
Citation: HUANG Xusheng, ZHU Yueqin, FU Lijun, LIU Yujiang, TANG Keke, LI Jin. 2021. Research on a geological entity relation extraction model for gold mine based on BERT. Journal of Geomechanics, 27(3): 391-399. doi: 10.12090/j.issn.1006-6616.2021.27.03.035
shu

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

  • 1.

    University of Chinese Academy of Sciences, Beijing 100049, China

  • 2.

    Shenyang Institute of Computing Technology, Chinese Academy of Sciences, Shenyang 110168, Liaoning, China

  • 3.

    Technology Innovation Center of Geological Information, MNR, Beijing 100037, China

  • 4.

    Development Research Center of China Geological Survey, Beijing 100037, China

  • 5.

    Laboratory of Big Data and Artificial Intelligence Technology, Shandong University, Jinan 250100, Shandong, China

    • Fund Project: This research is financially supported by the National Natural Science Foundation of China (Grant No.41872253), National Key Research and Development Program (Grant No.2018YFC1505501), and Geological Survey Project of China Geological Survey (Grant No.DD20190318)
More Information
Received Date:  20 November 2020
Revised Date:  10 January 2021
Publish Date:  28 June 2021
    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.

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