Nanopublications

@prefix this: <https://w3id.org/np/RAiyzaAhj15aaB48dhLqANMihGy8h7Z3H7fMC6x1oiwZM> .
@prefix sub: <https://w3id.org/np/RAiyzaAhj15aaB48dhLqANMihGy8h7Z3H7fMC6x1oiwZM/> .
@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/> .

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

sub:assertion {
  <https://doi.org/10.48550/arXiv.2402.11804> dct:title "LLM as Prompter: Low-resource Inductive Reasoning on Arbitrary Knowledge Graphs" ;
    <http://purl.org/spar/cito/describes> <https://neverblink.eu/ontologies/llm-kg/methods#Prolink> ;
    <http://purl.org/spar/cito/discusses> <https://neverblink.eu/ontologies/llm-kg/methods#Llama2KGReasoning> , <https://neverblink.eu/ontologies/llm-kg/methods#Ultra> ;
    a prov:Entity .
  <https://neverblink.eu/ontologies/llm-kg/methods#Llama2KGReasoning> dct:subject <https://neverblink.eu/ontologies/llm-kg/categories#LLMAugmentedKGCompletion> ;
    a <http://purl.org/spar/fabio/Workflow> ;
    rdfs:comment "This method uses Llama2-7B as a baseline for zero-shot graph reasoning by converting KG queries and subgraphs into textual questions. The LLM attempts to infer missing facts directly from the textual representation for KG completion." ;
    rdfs:label "Llama2 for KG Reasoning" ;
    <https://neverblink.eu/ontologies/llm-kg/hasTopCategory> <https://neverblink.eu/ontologies/llm-kg/top-categories#LLMAugmentedKG> .
  <https://neverblink.eu/ontologies/llm-kg/methods#Prolink> dct:subject <https://neverblink.eu/ontologies/llm-kg/categories#LLMAugmentedKGCompletion> ;
    a <http://purl.org/spar/fabio/Workflow> ;
    rdfs:comment "PROLINK is a novel framework designed for low-resource inductive reasoning across arbitrary KGs. It utilizes a pre-trained LLM to generate a graph-structural prompt from relation semantics. This prompt graph is then calibrated and injected into the KG's relation graph to enhance a GNN-based reasoner, thereby improving the inference of missing facts (KG completion)." ;
    rdfs:label "PROLINK" ;
    <https://neverblink.eu/ontologies/llm-kg/hasTopCategory> <https://neverblink.eu/ontologies/llm-kg/top-categories#LLMAugmentedKG> .
  <https://neverblink.eu/ontologies/llm-kg/methods#Ultra> a <http://purl.org/spar/fabio/Workflow> ;
    rdfs:label "ULTRA" .
}

sub:provenance {
sub:assertion prov:wasAttributedTo <https://neverblink.eu/ontologies/llm-kg/agent> ;
prov:wasDerivedFrom <https://doi.org/10.48550/arXiv.2402.11804> .
}

sub:pubinfo {
  this: dct:created "2026-02-26T15:42:35.147Z"^^xsd:dateTime ;
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    npx:hasNanopubType <https://neverblink.eu/ontologies/llm-kg/PaperAssessmentResult> ;
    rdfs:label "LLM-KG assessment for paper 10.48550/arXiv.2402.11804" .
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