Unleashing the Power of Large Language Models in Zero-shot Relation Extraction via Self-Prompting (2024.findings-emnlp)
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| Challenge: | Existing methods for zero-shot Relation Extraction (RE) lack detailed, context-specific prompts for understanding various sentences and relations. |
| Approach: | They propose a framework that uses a three-stage diversity approach to prompt LLMs by generating multiple synthetic samples that encapsulate specific relations from scratch. |
| Outcome: | The proposed framework outperforms existing LLM-based zero-shot RE methods on benchmark datasets and shows that it produces high-quality synthetic data that enhances performance. |
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Better Zero-Shot Reasoning with Role-Play Prompting (2024.naacl-long)
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Aobo Kong, Shiwan Zhao, Hao Chen, Qicheng Li, Yong Qin, Ruiqi Sun, Xin Zhou, Enzhi Wang, Xiaohang Dong
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