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Prompt engineering for Knowledge Graph (KG) completion involves designing input prompts to guide Large Language Models (LLMs) in inferring and filling missing parts of KGs, which enhances multi-hop link prediction and allows handling of unseen cues in zero-sample scenarios.

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