Nanopublications

@prefix this: <https://w3id.org/np/RABTh6r58uXeKXx-GxV1gAan-TGqahFoDCnmz6cTD50Mg> .
@prefix sub: <https://w3id.org/np/RABTh6r58uXeKXx-GxV1gAan-TGqahFoDCnmz6cTD50Mg/> .
@prefix np: <http://www.nanopub.org/nschema#> .
@prefix dct: <http://purl.org/dc/terms/> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .
@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/> .

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sub:assertion {
  <https://doi.org/10.48550/arXiv.2507.10630> dct:title "Enhancing the Capabilities of Large Language Models for API calls through Knowledge Graphs" ;
    <http://purl.org/spar/cito/describes> <https://neverblink.eu/ontologies/llm-kg/methods#KG2data> ;
    <http://purl.org/spar/cito/discusses> <https://neverblink.eu/ontologies/llm-kg/methods#Chat2data> , <https://neverblink.eu/ontologies/llm-kg/methods#RAG2data> ;
    a prov:Entity .
  <https://neverblink.eu/ontologies/llm-kg/methods#Chat2data> a <http://purl.org/spar/fabio/Workflow> ;
    rdfs:label "Chat2data" .
  <https://neverblink.eu/ontologies/llm-kg/methods#KG2data> dct:subject <https://neverblink.eu/ontologies/llm-kg/categories#KGEnhancedLLMInference> ;
    a <http://purl.org/spar/fabio/Workflow> ;
    rdfs:comment "KG2data is a system that integrates knowledge graphs, LLMs, ReAct agents, and tool usage to improve the accuracy and robustness of LLM API calls in knowledge-intensive domains like meteorology. It uses the KG as a long-term memory module for the LLM-driven agent, providing domain-specific knowledge during the inference stage to overcome LLM's limitations without retraining." ;
    rdfs:label "KG2data" ;
    <https://neverblink.eu/ontologies/llm-kg/hasTopCategory> <https://neverblink.eu/ontologies/llm-kg/top-categories#KGEnhancedLLM> .
  <https://neverblink.eu/ontologies/llm-kg/methods#RAG2data> a <http://purl.org/spar/fabio/Workflow> ;
    rdfs:label "RAG2data" .
}

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sub:assertion prov:wasAttributedTo <https://neverblink.eu/ontologies/llm-kg/agent> ;
prov:wasDerivedFrom <https://doi.org/10.48550/arXiv.2507.10630> .
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