@prefix this: . @prefix sub: . @prefix np: . @prefix dct: . @prefix rdf: . @prefix nt: . @prefix npx: . @prefix xsd: . @prefix rdfs: . @prefix orcid: . @prefix prov: . @prefix foaf: . sub:Head { this: np:hasAssertion sub:assertion; np:hasProvenance sub:provenance; np:hasPublicationInfo sub:pubinfo; a np:Nanopublication . } sub:assertion { sub:KGEnhancedLLMInference rdfs:label "KG-enhanced LLM inference" . sub:KGEnhancedLLMInterpretability rdfs:label "KG-enhanced LLM interpretability" . sub:KGEnhancedLLMPretraining rdfs:label "KG-enhanced LLM pre-training" . sub:LLMAugmentedKGCompletion rdfs:label "LLM-augmented KG completion" . sub:LLMAugmentedKGConstruction rdfs:label "LLM-augmented KG construction" . sub:LLMAugmentedKGEmbedding rdfs:label "LLM-augmented KG embedding" . sub:LLMAugmentedKGQuestionAnswering rdfs:label "LLM-augmented KG question answering" . sub:LLMAugmentedKGToTextGeneration rdfs:label "LLM-augmented KG to text generation" . sub:SynergizedKnowledgeRepresentation rdfs:label "Synergized Knowledge Representation" . sub:SynergizedReasoning rdfs:label "Synergized Reasoning" . sub:assertion dct:description "This template allows you to annotate research papers with large language models(LLMs) and knowledge graphs(KGs) integration categories based on the Pan et al. (2024) roadmap (DOI: https://doi.org/10.48550/arXiv.2306.08302). This template includes the paper's DOI, its specific integration category, and the contributor who made the categorization."; a nt:AssertionTemplate; rdfs:label "Annotating paper with LLMs+KGs integration category"; nt:hasNanopubLabelPattern "LLMs+KGs integration category: ${category} for ${paper}"; nt:hasStatement sub:st1; nt:hasTag "Annotations" . sub:category a nt:RestrictedChoicePlaceholder; nt:hasPrefix "https://neverblink.eu/ontologies/llm-kg/categories#"; nt:hasPrefixLabel "llm-kg"; nt:possibleValue sub:KGEnhancedLLMInference, sub:KGEnhancedLLMInterpretability, sub:KGEnhancedLLMPretraining, sub:LLMAugmentedKGCompletion, sub:LLMAugmentedKGConstruction, sub:LLMAugmentedKGEmbedding, sub:LLMAugmentedKGQuestionAnswering, sub:LLMAugmentedKGToTextGeneration, sub:SynergizedKnowledgeRepresentation, sub:SynergizedReasoning . sub:paper a nt:UriPlaceholder; nt:hasPrefix "https://doi.org/"; nt:hasPrefixLabel "the paper with DOI"; nt:hasRegex "10.(\\d)+/(\\S)+" . sub:st1 rdf:object sub:category; rdf:predicate dct:subject; rdf:subject sub:paper; a nt:RepeatableStatement . } sub:provenance { sub:assertion prov:wasAttributedTo orcid:0000-0002-3080-0303 . } sub:pubinfo { orcid:0000-0002-3080-0303 foaf:name "Anastasiya Danilenka" . this: dct:created "2026-01-20T08:45:25.576Z"^^xsd:dateTime; dct:creator orcid:0000-0002-3080-0303; dct:license ; npx:supersedes ; npx:wasCreatedAt ; rdfs:label "Annotating paper with LLMs+KGs integration category"; nt:wasCreatedFromProvenanceTemplate ; nt:wasCreatedFromPubinfoTemplate , , ; nt:wasCreatedFromTemplate . sub:sig npx:hasAlgorithm "RSA"; npx:hasPublicKey "MIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEAnosJSn16QpO5H1VxOxrwMH/H/b4lqyVo+/w5ri059ZaXR4GFN2l7rDusHTzgbyZ3Ifq2eEntFfnS3XrygI+AoIxoEob8jM1lEJstaCpSi3Kv+v9uD+s61HWL/4J7DyaVgycDcDFG7mOyemtUIU94hV9x5z2kXdFPfoffAlF8BRxKymOBMaCx/uOouxS/CCR4brlG6gXfU2d+13y/4PbiM3SxXdSKVAYaeSEA83ohAgJFhH3oZtZeuPhyENllRGxT5PVzqx59YVr10UV1VudiGIkqKjkcvGbfOoifZB38+uNN5DVBnLN4NcnoqqCAweoODWYUFOsjHTpobqA0+Ss0VwIDAQAB"; npx:hasSignature "CJ7zdX/Agg8jqqA75HfX3XazEikbkJZQ4tsPMwfXoKWduuhmMCgwoJ6esUu3c2gUDpUgZdYRkcK2nfYSDBze87pWnejiWT7KDgLJXjyepBm5+FMQurHyr5GSQyvZ2vuxweW2fCi2Va9rBSW/RxtzXluOVSO87FYbVJxDm0pZOcY4GC+rDfSvbFmcuAmZYSTdC30+avNZclvxHN/g7IN/TjSRYW0QgPegA5IYx3CeRx9LOk8hAnpNkSDtEqmV3PsQRJgs9SD1vLxzwFI3udb7GGkv2wkdJHx7j6UHBHCXYHf5QxUiP3KIDVHPRcOmFWaIDEeXDgG2by+as4RjXYHFDA=="; npx:hasSignatureTarget this:; npx:signedBy orcid:0000-0002-3080-0303 . }