Named Entity Recognition with Gating Mechanism and Parallel BiLSTM

Authors

  • Yenan Yi School of Business, Hohai University, Nanjing, 211106, China https://orcid.org/0000-0001-8510-5335
  • Yijie Bian School of Business, Hohai University, Nanjing, 211106, China

DOI:

https://doi.org/10.13052/jwe1540-9589.20413

Keywords:

Named Entity Recognition, Parallel BiLSTM, Gating Mechanism, CoNLL-2003

Abstract

In this paper, we propose a novel neural network for named entity recognition, which is improved in two aspects. On the one hand, our model uses a parallel BiLSTM structure to generate character-level word representations. By inputting character sequences of words into several independent and parallel BiLSTMs, we can obtain word representations from different representation subspaces, because the parameters of these BiLSTMs are randomly initialized. This method can enhance the expression abilities of character-level word representations. On the other hand, we use a two-layer BiLSTM with gating mechanism to model sentences. Since the features extracted by each layer in a multi-layer LSTM from texts contain different types of information, we use the gating mechanism to assign appropriate weights to the outputs of each layer, and take the weighted sum of these outputs as the final output for named entity recognition. Our model only changes the structure, does not need any feature engineering or external knowledge source, which is a complete end-to-end NER model. We used the CoNLL-2003 English and German datasets to evaluate our model and got better results compared with baseline models.

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Author Biographies

Yenan Yi, School of Business, Hohai University, Nanjing, 211106, China

Yenan Yi received his B.S. degree from Nanjing University of Science and Technology, Nanjing, China, in 2012; M.S. degree from Hohai University, Nanjing, China, in 2017. He is currently a Ph.D. student at Hohai University, and his research interests are information management and intelligent question answering.

Yijie Bian, School of Business, Hohai University, Nanjing, 211106, China

Yijie Bian received his B.S., M.S. and Ph.D. degrees from Hohai University, Nanjing, China. He is a professor and doctoral supervisor of Hohai University. His research interests include information management and e-commerce, financial engineering and investment management.

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Published

2021-07-08

How to Cite

Yi, Y., & Bian, Y. (2021). Named Entity Recognition with Gating Mechanism and Parallel BiLSTM. Journal of Web Engineering, 20(4), 1157–1176. https://doi.org/10.13052/jwe1540-9589.20413

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Section

Articles