MATEC Web Conf.
Volume 336, 20212020 2nd International Conference on Computer Science Communication and Network Security (CSCNS2020)
|Number of page(s)||8|
|Section||Artificial Recognition and Application|
|Published online||15 February 2021|
Chinese named entity recognition model based on BERT
Modern Post College, Nanjing University of Posts and Telecommunications, Nanjing, China
* Corresponding author: firstname.lastname@example.org
Nowadays, most deep learning models ignore Chinese habits and global information when processing Chinese tasks. To solve this problem, we constructed the BERT-BiLSTM-Attention-CRF model. In the model, we embeded the BERT pre-training language model that adopts the Whole Word Mask strategy, and added a document-level attention. Experimental results show that our method achieves good results in the MSRA corpus, and F1 reaches 95.00%.
© The Authors, published by EDP Sciences, 2021
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