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https://w3id.org/np/RA9v-9d74dV2yZRJVkpEu9gtt9gRQI3Htrd1kw_jcx8Ps

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Content

@prefix this: <https://w3id.org/np/RA9v-9d74dV2yZRJVkpEu9gtt9gRQI3Htrd1kw_jcx8Ps> .
@prefix sub: <https://w3id.org/np/RA9v-9d74dV2yZRJVkpEu9gtt9gRQI3Htrd1kw_jcx8Ps/> .
@prefix np: <http://www.nanopub.org/nschema#> .
@prefix dct: <http://purl.org/dc/terms/> .
@prefix pav: <http://purl.org/pav/> .
@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
@prefix owl: <http://www.w3.org/2002/07/owl#> .
@prefix rdfg: <http://www.w3.org/2004/03/trix/rdfg-1/> .
@prefix dce: <http://purl.org/dc/elements/1.1/> .
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@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .
@prefix prov: <http://www.w3.org/ns/prov#> .
@prefix npx: <http://purl.org/nanopub/x/> .

sub:Head {
  this: a np:Nanopublication;
    np:hasAssertion sub:assertion;
    np:hasProvenance sub:provenance;
    np:hasPublicationInfo sub:pubinfo .
}

sub:assertion {
  <https://doi.org/10.48550/arXiv.2406.17231> a prov:Entity;
    dct:title "CogMG: Collaborative Augmentation Between Large Language Model and Knowledge Graph";
    <http://purl.org/spar/cito/describes> <https://neverblink.eu/ontologies/llm-kg/methods#CogMg>;
    <http://purl.org/spar/cito/discusses> <https://neverblink.eu/ontologies/llm-kg/methods#KbBinder>,
      <https://neverblink.eu/ontologies/llm-kg/methods#ReActAgentFramework> .
  
  <https://neverblink.eu/ontologies/llm-kg/methods#CogMg> a <http://purl.org/spar/fabio/Workflow>;
    dct:subject <https://neverblink.eu/ontologies/llm-kg/categories#SynergizedReasoning>;
    rdfs:comment "CogMG is a unified framework where the LLM acts as an agent, using its planning and reasoning capabilities to interact with the KG. It actively decomposes queries, processes results, and orchestrates the \"Graph Evolution\" by identifying and completing missing knowledge triples, which are then used to update the KG. This continuous, agent-driven interaction and mutual updating represent a synergistic reasoning process where the LLM leverages the KG and its own knowledge to answer questions and improve the KG's knowledge base.";
    rdfs:label "CogMG";
    <https://neverblink.eu/ontologies/llm-kg/hasTopCategory> <https://neverblink.eu/ontologies/llm-kg/top-categories#SynergizedLLMKG> .
  
  <https://neverblink.eu/ontologies/llm-kg/methods#KbBinder> a <http://purl.org/spar/fabio/Workflow>;
    rdfs:label "KB-BINDER" .
  
  <https://neverblink.eu/ontologies/llm-kg/methods#ReActAgentFramework> a <http://purl.org/spar/fabio/Workflow>;
    rdfs:label "ReAct Agent Framework" .
}

sub:provenance {
  sub:assertion prov:wasAttributedTo <https://neverblink.eu/ontologies/llm-kg/agent>;
    prov:wasDerivedFrom <https://doi.org/10.48550/arXiv.2406.17231> .
}

sub:pubinfo {
  this: dct:created "2026-02-26T13:21:27.806Z"^^xsd:dateTime;
    dct:creator <https://neverblink.eu/ontologies/llm-kg/agent>;
    npx:hasNanopubType <https://neverblink.eu/ontologies/llm-kg/PaperAssessmentResult>;
    rdfs:label "LLM-KG assessment for paper 10.48550/arXiv.2406.17231" .
  
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}