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GoG is a training-free method for Incomplete Knowledge Graph Question Answering (IKGQA). It employs a Thinking-Searching-Generating framework, treating the LLM as both an agent to explore the KG and as a knowledge source to generate missing factual triples. This synergistic approach combines LLM's reasoning and internal knowledge with external KG facts to answer complex questions where the KG is incomplete.
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