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GoG is a training-free method designed for Incomplete Knowledge Graph Question Answering (IKGQA). It treats the LLM as both an agent to explore KGs and as a knowledge source to generate new factual triples when existing KG knowledge is insufficient. The method's Thinking-Searching-Generating framework enables the LLM to bridge knowledge gaps and answer questions that conventional KGQA methods fail on due to KG incompleteness.
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