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sub:assertion {
  <https://doi.org/10.48550/arXiv.2511.17012> dct:title "Supervised Fine-Tuning of Large Language Models for Domain-Specific Knowledge Graph Construction: A Case Study on Hunan's Historical Celebrities";
    <http://purl.org/spar/cito/describes> <https://neverblink.eu/ontologies/llm-kg/methods#ZhaoEtAl2025HunanCelebrityKGConstruction>;
    <http://purl.org/spar/cito/discusses> <https://neverblink.eu/ontologies/llm-kg/methods#ChainOfThought>,
      <https://neverblink.eu/ontologies/llm-kg/methods#InstructUIEFramework>, <https://neverblink.eu/ontologies/llm-kg/methods#SelfInstructFramework>;
    a prov:Entity .
  
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    rdfs:label "InstructUIE framework" .
  
  <https://neverblink.eu/ontologies/llm-kg/methods#SelfInstructFramework> a <http://purl.org/spar/fabio/Workflow>;
    rdfs:label "Self-Instruct framework" .
  
  <https://neverblink.eu/ontologies/llm-kg/methods#ZhaoEtAl2025HunanCelebrityKGConstruction>
    dct:subject <https://neverblink.eu/ontologies/llm-kg/categories#LLMAugmentedKGConstruction>;
    a <http://purl.org/spar/fabio/Workflow>;
    rdfs:comment "This method proposes a supervised fine-tuning approach for Large Language Models to enhance information extraction for domain-specific Knowledge Graph construction. It involves defining a fine-grained schema, constructing an instruction fine-tuning dataset, and employing LoRA for parameter-efficient fine-tuning of LLMs. The fine-tuned LLMs are then used to extract structured entities, relations, and properties from text to build a Knowledge Graph.";
    rdfs:label "ZhaoEtAl2025HunanCelebrityKGConstruction";
    <https://neverblink.eu/ontologies/llm-kg/hasTopCategory> <https://neverblink.eu/ontologies/llm-kg/top-categories#LLMAugmentedKG> .
}

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