Enhancing Chinese Named Entity Recognition with Disentangled Expert Knowledge

Author:

Wang Hongkai,Feng Jun,Wang Yidan,Pan Sichen,Zhao Shuai,Xue Yi

Publisher

Springer Nature Singapore

Reference36 articles.

1. Wang, D., Fan, H., Liu, J.: Learning with joint cross-document information via multi-task learning for named entity recognition. Inf. Sci. 579, 454–467 (2021)

2. Jimeno, A., Jimenez-Ruiz, E., Lee, V., Gaudan, S., Berlanga, R., Rebholz-Schuhmann, D.: Assessment of disease named entity recognition on a corpus of annotated sentences. BMC Bioinform. (2008)

3. Cabrera-Diego, L.A., Moreno, J.G., Doucet, A.: Using a frustratingly easy domain and tagset adaptation for creating slavic named entity recognition systems. In: Proceedings of the 8th Workshop on Balto-Slavic Natural Language Processing (2021)

4. Chiu, J.P., Nichols, E.: Named entity recognition with bidirectional LSTM-CNNs. Trans. Assoc. Comput. Linguist. 4, 357–370 (2016)

5. Cucerzan, S., Yarowsky, D.: Language independent named entity recognition combining morphological and contextual evidence. In: Empirical Methods in Natural Language Processing (1999)

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