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@prefix np: <http://www.nanopub.org/nschema#> .
@prefix dct: <http://purl.org/dc/terms/> .
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@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .
@prefix prov: <http://www.w3.org/ns/prov#> .
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sub:assertion {
  <https://doi.org/10.48550/arXiv.2411.17388> dct:title "Can LLMs be Good Graph Judge for Knowledge Graph Construction?";
    <http://purl.org/spar/cito/describes> <https://neverblink.eu/ontologies/llm-kg/methods#GraphJudge>;
    <http://purl.org/spar/cito/discusses> <https://neverblink.eu/ontologies/llm-kg/methods#IText2KG>,
      <https://neverblink.eu/ontologies/llm-kg/methods#KGGen>, <https://neverblink.eu/ontologies/llm-kg/methods#PiVe>,
      <https://neverblink.eu/ontologies/llm-kg/methods#RAKG>;
    a prov:Entity .
  
  <https://neverblink.eu/ontologies/llm-kg/methods#GraphJudge> dct:subject <https://neverblink.eu/ontologies/llm-kg/categories#LLMAugmentedKGConstruction>;
    a <http://purl.org/spar/fabio/Workflow>;
    rdfs:comment "GraphJudge is a framework designed to enhance Knowledge Graph Construction quality. It employs a closed-source LLM for initial entity-centric text denoising and triple extraction, then fine-tunes an open-source LLM to act as a \"graph judge\" for verifying and filtering the correctness of the extracted triples, addressing issues like noise, domain-specific inaccuracies, and hallucinations in KG construction.";
    rdfs:label "GraphJudge";
    <https://neverblink.eu/ontologies/llm-kg/hasTopCategory> <https://neverblink.eu/ontologies/llm-kg/top-categories#LLMAugmentedKG> .
  
  <https://neverblink.eu/ontologies/llm-kg/methods#IText2KG> a <http://purl.org/spar/fabio/Workflow>;
    rdfs:label "iText2KG" .
  
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    rdfs:label "KGGen" .
  
  <https://neverblink.eu/ontologies/llm-kg/methods#PiVe> a <http://purl.org/spar/fabio/Workflow>;
    rdfs:label "PiVe" .
  
  <https://neverblink.eu/ontologies/llm-kg/methods#RAKG> a <http://purl.org/spar/fabio/Workflow>;
    rdfs:label "RAKG" .
}

sub:provenance {
  sub:assertion prov:wasAttributedTo <https://neverblink.eu/ontologies/llm-kg/agent>;
    prov:wasDerivedFrom <https://doi.org/10.48550/arXiv.2411.17388> .
}

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