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sub:assertion {
  <https://doi.org/10.48550/arXiv.2503.16131> dct:title "MKG-Rank: Enhancing Large Language Models with Knowledge Graph for Multilingual Medical Question Answering";
    <http://purl.org/spar/cito/describes> <https://neverblink.eu/ontologies/llm-kg/methods#CachingMechanism>,
      <https://neverblink.eu/ontologies/llm-kg/methods#DeclarativeConversion>, <https://neverblink.eu/ontologies/llm-kg/methods#MKGRank>,
      <https://neverblink.eu/ontologies/llm-kg/methods#MultiAngleRanking>, <https://neverblink.eu/ontologies/llm-kg/methods#SelfInformationMining>,
      <https://neverblink.eu/ontologies/llm-kg/methods#WordLevelTranslationMechanism>;
    <http://purl.org/spar/cito/discusses> <https://neverblink.eu/ontologies/llm-kg/methods#BM25>,
      <https://neverblink.eu/ontologies/llm-kg/methods#MedCPTCrossEncoder>, <https://neverblink.eu/ontologies/llm-kg/methods#UMLSBertEmbeddings>;
    a prov:Entity .
  
  <https://neverblink.eu/ontologies/llm-kg/methods#BM25> a <http://purl.org/spar/fabio/Workflow>;
    rdfs:label "BM25" .
  
  <https://neverblink.eu/ontologies/llm-kg/methods#CachingMechanism> dct:subject <https://neverblink.eu/ontologies/llm-kg/categories#KGEnhancedLLMInference>;
    a <http://purl.org/spar/fabio/Workflow>;
    rdfs:comment "This mechanism optimizes the retrieval of external medical KGs by storing previously retrieved KGs in a local knowledge base. It significantly reduces retrieval times during LLM inference, directly contributing to the efficiency of the overall KG-enhanced LLM system.";
    rdfs:label "Caching Mechanism";
    <https://neverblink.eu/ontologies/llm-kg/hasTopCategory> <https://neverblink.eu/ontologies/llm-kg/top-categories#KGEnhancedLLM> .
  
  <https://neverblink.eu/ontologies/llm-kg/methods#DeclarativeConversion> dct:subject
      <https://neverblink.eu/ontologies/llm-kg/categories#KGEnhancedLLMInference>;
    a <http://purl.org/spar/fabio/Workflow>;
    rdfs:comment "This mechanism converts raw medical KG triplets into LLM-digestible declarative sentences. It allows the LLM to better integrate and reason with external knowledge during inference, improving its ability to utilize the provided medical facts.";
    rdfs:label "Declarative Conversion";
    <https://neverblink.eu/ontologies/llm-kg/hasTopCategory> <https://neverblink.eu/ontologies/llm-kg/top-categories#KGEnhancedLLM> .
  
  <https://neverblink.eu/ontologies/llm-kg/methods#MKGRank> dct:subject <https://neverblink.eu/ontologies/llm-kg/categories#KGEnhancedLLMInference>;
    <http://purl.org/spar/fabio/hasURL> "https://anonymous.4open.science/r/MKG-Rank-6B72"^^xsd:anyURI;
    a <http://purl.org/spar/fabio/Workflow>;
    rdfs:comment "This framework enhances English-centric LLMs to perform multilingual medical QA by integrating comprehensive external medical knowledge graphs during the inference stage. It bridges language gaps and provides relevant, up-to-date knowledge to LLMs for better reasoning.";
    rdfs:label "MKG-Rank";
    <https://neverblink.eu/ontologies/llm-kg/hasTopCategory> <https://neverblink.eu/ontologies/llm-kg/top-categories#KGEnhancedLLM> .
  
  <https://neverblink.eu/ontologies/llm-kg/methods#MedCPTCrossEncoder> a <http://purl.org/spar/fabio/Workflow>;
    rdfs:label "MedCPT Cross Encoder" .
  
  <https://neverblink.eu/ontologies/llm-kg/methods#MultiAngleRanking> dct:subject <https://neverblink.eu/ontologies/llm-kg/categories#KGEnhancedLLMInference>;
    a <http://purl.org/spar/fabio/Workflow>;
    rdfs:comment "This strategy selects the most relevant medical triplets from retrieved KGs by ranking them based on similarity with the question (using UMLS-BERT embeddings) and further filtering with a MedCPT Cross Encoder. It ensures the LLM receives high-quality, pertinent information for accurate inference.";
    rdfs:label "Multi-Angle Ranking";
    <https://neverblink.eu/ontologies/llm-kg/hasTopCategory> <https://neverblink.eu/ontologies/llm-kg/top-categories#KGEnhancedLLM> .
  
  <https://neverblink.eu/ontologies/llm-kg/methods#SelfInformationMining> dct:subject
      <https://neverblink.eu/ontologies/llm-kg/categories#KGEnhancedLLMInference>;
    a <http://purl.org/spar/fabio/Workflow>;
    rdfs:comment "When external KG retrieval is ineffective, this method employs the BM25 algorithm to extract relevant world knowledge from the LLM's own internal representations. It acts as a fallback strategy to ensure the LLM consistently has background information for medical QA, enhancing its robustness during inference.";
    rdfs:label "Self-Information Mining";
    <https://neverblink.eu/ontologies/llm-kg/hasTopCategory> <https://neverblink.eu/ontologies/llm-kg/top-categories#KGEnhancedLLM> .
  
  <https://neverblink.eu/ontologies/llm-kg/methods#UMLSBertEmbeddings> a <http://purl.org/spar/fabio/Workflow>;
    rdfs:label "UMLS-BERT embeddings" .
  
  <https://neverblink.eu/ontologies/llm-kg/methods#WordLevelTranslationMechanism> dct:subject
      <https://neverblink.eu/ontologies/llm-kg/categories#KGEnhancedLLMInference>;
    a <http://purl.org/spar/fabio/Workflow>;
    rdfs:comment "This mechanism, part of MKG-Rank, extracts medical entities from multilingual questions and options using an LLM, then translates them into English. This enables the LLM to leverage English-centric KGs for multilingual QA, enhancing its performance during inference.";
    rdfs:label "Word-level Translation Mechanism";
    <https://neverblink.eu/ontologies/llm-kg/hasTopCategory> <https://neverblink.eu/ontologies/llm-kg/top-categories#KGEnhancedLLM> .
}

sub:provenance {
  sub:assertion prov:wasAttributedTo <https://neverblink.eu/ontologies/llm-kg/agent>;
    prov:wasDerivedFrom <https://doi.org/10.48550/arXiv.2503.16131> .
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