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@prefix dct: <http://purl.org/dc/terms/> .
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sub:Head {
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sub:assertion {
  <https://doi.org/10.48550/arXiv.2406.02110> dct:title "UniOQA: A Unified Framework for Knowledge Graph Question Answering with Large Language Models";
    <http://purl.org/spar/cito/describes> <https://neverblink.eu/ontologies/llm-kg/methods#DynamicDecisionAlgorithm>,
      <https://neverblink.eu/ontologies/llm-kg/methods#EntityAndRelationReplacementAlgorithm>,
      <https://neverblink.eu/ontologies/llm-kg/methods#GRAGProcess>, <https://neverblink.eu/ontologies/llm-kg/methods#UniOQA>;
    <http://purl.org/spar/cito/discusses> <https://neverblink.eu/ontologies/llm-kg/methods#BinaryLogicCombinationRule>,
      <https://neverblink.eu/ontologies/llm-kg/methods#ChainOfThought>, <https://neverblink.eu/ontologies/llm-kg/methods#InContextLearning>,
      <https://neverblink.eu/ontologies/llm-kg/methods#RetrievalAugmentedGeneration>, <https://neverblink.eu/ontologies/llm-kg/methods#Seq2Seq>,
      <https://neverblink.eu/ontologies/llm-kg/methods#Seq2SeqWithAttention>, <https://neverblink.eu/ontologies/llm-kg/methods#Seq2SeqWithCopy>,
      <https://neverblink.eu/ontologies/llm-kg/methods#TextToCQL>;
    a prov:Entity .
  
  <https://neverblink.eu/ontologies/llm-kg/methods#BinaryLogicCombinationRule> a <http://purl.org/spar/fabio/Workflow>;
    rdfs:label "Binary Logic Combination Rule (BNA)" .
  
  <https://neverblink.eu/ontologies/llm-kg/methods#ChainOfThought> a <http://purl.org/spar/fabio/Workflow>;
    rdfs:label "Chain-of-Thought (COT)" .
  
  <https://neverblink.eu/ontologies/llm-kg/methods#DynamicDecisionAlgorithm> dct:subject
      <https://neverblink.eu/ontologies/llm-kg/categories#SynergizedReasoning>;
    a <http://purl.org/spar/fabio/Workflow>;
    rdfs:comment "This algorithm serves to optimally combine the answers obtained from the two parallel workflows of UniOQA (Translator and Searcher). By dynamically selecting the better answer based on an F1 score criterion, it represents a synergized approach to reasoning, integrating results derived from both LLM-generated queries and LLM-augmented KG retrieval to yield the final, most accurate answer.";
    rdfs:label "Dynamic Decision Algorithm (DDA)";
    <https://neverblink.eu/ontologies/llm-kg/hasTopCategory> <https://neverblink.eu/ontologies/llm-kg/top-categories#SynergizedLLMKG> .
  
  <https://neverblink.eu/ontologies/llm-kg/methods#EntityAndRelationReplacementAlgorithm>
    dct:subject <https://neverblink.eu/ontologies/llm-kg/categories#LLMAugmentedKGQuestionAnswering>;
    a <http://purl.org/spar/fabio/Workflow>;
    rdfs:comment "This algorithm uses an LLM (Baichuan2-7B with a crafted instruction) to select and replace entities and relations in the generated Cypher Query Language (CQL) to align them with the knowledge graph. Its purpose is to enhance the executability and accuracy of the CQL, directly improving the performance of Knowledge Graph Question Answering by refining the query before execution.";
    rdfs:label "Entity and Relation Replacement (ERR) algorithm";
    <https://neverblink.eu/ontologies/llm-kg/hasTopCategory> <https://neverblink.eu/ontologies/llm-kg/top-categories#LLMAugmentedKG> .
  
  <https://neverblink.eu/ontologies/llm-kg/methods#GRAGProcess> dct:subject <https://neverblink.eu/ontologies/llm-kg/categories#LLMAugmentedKGQuestionAnswering>;
    a <http://purl.org/spar/fabio/Workflow>;
    rdfs:comment "GRAG (Knowledge Graph Retrieval-Augmented Generation) is a process that employs an LLM, combined with traditional information retrieval from the knowledge graph (retrieving relevant subgraphs), to directly generate answers to natural language questions. This directly uses LLMs to improve the task of question answering over KGs.";
    rdfs:label "GRAG Process";
    <https://neverblink.eu/ontologies/llm-kg/hasTopCategory> <https://neverblink.eu/ontologies/llm-kg/top-categories#LLMAugmentedKG> .
  
  <https://neverblink.eu/ontologies/llm-kg/methods#InContextLearning> a <http://purl.org/spar/fabio/Workflow>;
    rdfs:label "In-Context Learning (ICL)" .
  
  <https://neverblink.eu/ontologies/llm-kg/methods#RetrievalAugmentedGeneration> a <http://purl.org/spar/fabio/Workflow>;
    rdfs:label "Retrieval-Augmented Generation (RAG)" .
  
  <https://neverblink.eu/ontologies/llm-kg/methods#Seq2Seq> a <http://purl.org/spar/fabio/Workflow>;
    rdfs:label "Seq2Seq" .
  
  <https://neverblink.eu/ontologies/llm-kg/methods#Seq2SeqWithAttention> a <http://purl.org/spar/fabio/Workflow>;
    rdfs:label "Seq2Seq+Attention" .
  
  <https://neverblink.eu/ontologies/llm-kg/methods#Seq2SeqWithCopy> a <http://purl.org/spar/fabio/Workflow>;
    rdfs:label "Seq2Seq+Copy" .
  
  <https://neverblink.eu/ontologies/llm-kg/methods#TextToCQL> a <http://purl.org/spar/fabio/Workflow>;
    rdfs:label "Text-to-CQL" .
  
  <https://neverblink.eu/ontologies/llm-kg/methods#UniOQA> dct:subject <https://neverblink.eu/ontologies/llm-kg/categories#SynergizedReasoning>;
    a <http://purl.org/spar/fabio/Workflow>;
    rdfs:comment "UniOQA is presented as a \"unified framework\" that integrates two parallel workflows (Translator for CQL generation and Searcher for direct retrieval) and a \"dynamic decision algorithm\" to synthesize their outputs. This explicit combination and optimization of answers from both LLM-derived queries and KG-based retrieval constitutes a synergized approach to reasoning for Knowledge Graph Question Answering.";
    rdfs:label "UniOQA";
    <https://neverblink.eu/ontologies/llm-kg/hasTopCategory> <https://neverblink.eu/ontologies/llm-kg/top-categories#SynergizedLLMKG> .
}

sub:provenance {
  sub:assertion prov:wasAttributedTo <https://neverblink.eu/ontologies/llm-kg/agent>;
    prov:wasDerivedFrom <https://doi.org/10.48550/arXiv.2406.02110> .
}

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