Janko at SemEval-2023 Task 2: Bidirectional LSTM Model Based on Pre-training for Chinese Named Entity Recognition
Jiankuo Li, Zhengyi Guan, Haiyan Ding
The 17th International Workshop on Semantic Evaluation (SemEval-2023) Task 2: multiconer ii multilingual complex named entity recognition Paper
TLDR:
This paper describes the method we submitted as the Janko team in the SemEval-2023 Task 2,Multilingual Complex Named Entity Recognition (MultiCoNER 2). We only participated in the Chinese track. In this paper, we implement the BERT-BiLSTM-RDrop model. We use the fine-tuned BERT models, take the outp
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Abstract:
This paper describes the method we submitted as the Janko team in the SemEval-2023 Task 2,Multilingual Complex Named Entity Recognition (MultiCoNER 2). We only participated in the Chinese track. In this paper, we implement the BERT-BiLSTM-RDrop model. We use the fine-tuned BERT models, take the output of BERT as the input of the BiLSTM network, and finally use R-Drop technology to optimize the loss function. Our submission achieved a macro-averaged F1 score of 0.579 on the testset.