Fine-Grained Mechanical Chinese Named Entity Recognition Based on ALBERT-AttBiLSTM-CRF and Transfer Learning

Manufacturing text often exists as unlabeled data; the entity is fine-grained and the extraction is difficult. The above problems mean that the manufacturing industry knowledge utilization rate is low. This paper proposes a novel Chinese fine-grained NER (named entity recognition) method based on sy...

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Bibliographic Details
Main Authors: Liguo Yao, Haisong Huang, Kuan-Wei Wang, Shih-Huan Chen, Qiaoqiao Xiong
Format: Article
Language:English
Published: MDPI AG 2020-11-01
Series:Symmetry
Subjects:
NLP
Online Access:https://www.mdpi.com/2073-8994/12/12/1986