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sub:assertion {
  <https://doi.org/10.48550/arXiv.2403.03008> dct:title "Knowledge Graphs as Context Sources for LLM-Based Explanations of Learning Recommendations ⋆" ;
    <http://purl.org/spar/cito/describes> <https://neverblink.eu/ontologies/llm-kg/methods#kgContextualizedLlmExplanationGeneration> ;
    <http://purl.org/spar/cito/discusses> <https://neverblink.eu/ontologies/llm-kg/methods#gpt4> , <https://neverblink.eu/ontologies/llm-kg/methods#markovDecisionProcessBasedRecommendationAlgorithm> , <https://neverblink.eu/ontologies/llm-kg/methods#rougeMetric> ;
    a prov:Entity .
  <https://neverblink.eu/ontologies/llm-kg/methods#gpt4> a <http://purl.org/spar/fabio/Workflow> ;
    rdfs:label "GPT-4" .
  <https://neverblink.eu/ontologies/llm-kg/methods#kgContextualizedLlmExplanationGeneration> dct:subject <https://neverblink.eu/ontologies/llm-kg/categories#KGEnhancedLLMInference> ;
    a <http://purl.org/spar/fabio/Workflow> ;
    rdfs:comment "This method utilizes knowledge graphs (KGs) to provide structured factual context for LLM prompts during the inference stage. By extracting hierarchical information, semantic relations, and metadata from a KG, the method constructs a contextual part for the GPT-4 prompt, thereby guiding the LLM to generate more precise, relevant, and less hallucinatory explanations for learning recommendations in a sensitive domain." ;
    rdfs:label "KG-Contextualized LLM Explanation Generation" ;
    <https://neverblink.eu/ontologies/llm-kg/hasTopCategory> <https://neverblink.eu/ontologies/llm-kg/top-categories#KGEnhancedLLM> .
  <https://neverblink.eu/ontologies/llm-kg/methods#markovDecisionProcessBasedRecommendationAlgorithm> a <http://purl.org/spar/fabio/Workflow> ;
    rdfs:label "Markov Decision Process-based Recommendation Algorithm" .
  <https://neverblink.eu/ontologies/llm-kg/methods#rougeMetric> a <http://purl.org/spar/fabio/Workflow> ;
    rdfs:label "Rouge Metric" .
}
sub:provenance {
  sub:assertion prov:wasAttributedTo <https://neverblink.eu/ontologies/llm-kg/agent> ;
    prov:wasDerivedFrom <https://doi.org/10.48550/arXiv.2403.03008> .
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