A Chinese Fine-grained Financial Event Extraction Dataset

Author:

Wu Mengjie1ORCID,Liu Maofu1ORCID,Wang Luyao1ORCID,Hu Huijun1ORCID

Affiliation:

1. School of Computer Science and Technology, Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System,Wuhan University of Science and Technology, China

Funder

the National Key Research and Development Program of China

Publisher

ACM

Reference12 articles.

1. Chung-Chi Chen, Hen-Hsen Huang, and Hsin-Hsi Chen. 2020. NLP in FinTech Applications: Past, Present and Future. CoRR abs/2005.01320 (2020). arXiv:2005.01320https://arxiv.org/abs/2005.01320

2. Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. CoRR abs/1810.04805 (2018). arXiv:1810.04805http://arxiv.org/abs/1810.04805

3. Cuiyun Han Jinchuan Zhang Xinyu Li Guojin Xu Weihua Peng and Zengfeng Zeng. 2022. DuEE-Fin: A Large-Scale Dataset for Document-Level Event Extraction. In Natural Language Processing and Chinese Computing Wei Lu Shujian Huang Yu Hong and Xiabing Zhou (Eds.). Cham 172–183.

4. Diederik P Kingma and Jimmy Ba. 2014. Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014).

5. John D. Lafferty, Andrew McCallum, and Fernando C. N. Pereira. 2001. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data. In Proceedings of the Eighteenth International Conference on Machine Learning(ICML ’01). Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 282–289.

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