دورية أكاديمية
Generating Chinese Event Extraction Method Based on ChatGPT and Prompt Learning
| العنوان: | Generating Chinese Event Extraction Method Based on ChatGPT and Prompt Learning |
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| المؤلفون: | Jianxun Chen, Peng Chen, Xuxu Wu |
| المصدر: | Applied Sciences, Vol 13, Iss 17, p 9500 (2023) |
| بيانات النشر: | MDPI AG, 2023. |
| سنة النشر: | 2023 |
| المجموعة: | LCC:Technology LCC:Engineering (General). Civil engineering (General) LCC:Biology (General) LCC:Physics LCC:Chemistry |
| مصطلحات موضوعية: | ChatGPT, prompt learning, event extraction, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999 |
| الوصف: | Regarding the scarcity of annotated data for existing event extraction tasks and the insufficient semantic mining of event extraction models in the Chinese domain, this paper proposes a generative joint event extraction model to improve existing models in two aspects. Firstly, it utilizes the content generation capability of ChatGPT to generate annotated data corpora for event extraction tasks and trains the model using supervised learning methods adapted to downstream tasks. Secondly, explicit entity markers and event knowledge are added to the text to construct generative input templates, enhancing the performance of event extraction. To validate the performance of this model, experiments are conducted on DuEE1.0 and Title2Event public datasets, and the results show that both data enhancement and prompt learning based on ChatGPT effectively improve the performance of the event extraction model, and the F1 values of the events extracted by the CPEE model proposed in this paper reach 85.1% and 59.9% on the two datasets, respectively, which are comparable to the existing models’ values of 1.3% and 10%, respectively; moreover, on the Title2Event dataset, the performance of different models on the event extraction task can be gradually improved as the data size of the annotated corpus of event extraction generated using ChatGPT increases. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 13179500 2076-3417 |
| Relation: | https://www.mdpi.com/2076-3417/13/17/9500; https://doaj.org/toc/2076-3417 |
| DOI: | 10.3390/app13179500 |
| URL الوصول: | https://doaj.org/article/1e0032ae8efa435ba0e8c0b6e5456427 |
| رقم الأكسشن: | edsdoj.1e0032ae8efa435ba0e8c0b6e5456427 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 13179500 20763417 |
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| DOI: | 10.3390/app13179500 |