PNRE: Proactive Learning for Neural Relation Extraction with Multiple Annotators

Author:

Qiu Rui,Ji Wen,Liang Yundan,Qu Haini,Xu Jingce

Publisher

Atlantis Press International BV

Reference22 articles.

1. Charu C. Aggarwal, Xiangnan Kong, Quanquan Gu, Jiawei Han, and Philip S. Yu. Active learning: A survey. In Data Classification: Algorithms and Applications, pages 571–606. CRC Press, 2014.

2. Cyrielle Mallart, Michel Le Nouy, Guillaume Gravier, and Pascale Se´billot. Active learning for interactive relation extraction in a french newspaper’s articles. In RANLP, pages 886–894. INCOMA Ltd., 2021.

3. Dan Roth and Wen-tau Yih. A linear programming formulation for global inference in natural language tasks. In CoNLL, pages 1–8. ACL, 2004.

4. Donggeun Yoo and In So Kweon. Learning loss for active learning. In CVPR, pages 93–102. Computer Vision Foundation/IEEE, 2019.

5. Haw-Shiuan Chang, Shankar Vembu, Sunil Mohan, Rheeya Uppaal, and Andrew McCallum. Using error decay prediction to overcome practical issues of deep active learning for named entity recognition. Mach. Learn., 109(9–10):1749–1778, 2020.

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