Papers with zero-shot Relation Extraction

1 papers
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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