[ {
  "@graph" : [ {
    "@id" : "https://w3id.org/np/RA_6CsM56gRUw5F1G7StJvgSiaBjwqwa4vg4dp4Pez6fs",
    "@type" : [ "http://www.nanopub.org/nschema#Nanopublication" ],
    "http://www.nanopub.org/nschema#hasAssertion" : [ {
      "@id" : "https://w3id.org/np/RA_6CsM56gRUw5F1G7StJvgSiaBjwqwa4vg4dp4Pez6fs/assertion"
    } ],
    "http://www.nanopub.org/nschema#hasProvenance" : [ {
      "@id" : "https://w3id.org/np/RA_6CsM56gRUw5F1G7StJvgSiaBjwqwa4vg4dp4Pez6fs/provenance"
    } ],
    "http://www.nanopub.org/nschema#hasPublicationInfo" : [ {
      "@id" : "https://w3id.org/np/RA_6CsM56gRUw5F1G7StJvgSiaBjwqwa4vg4dp4Pez6fs/pubinfo"
    } ]
  } ],
  "@id" : "https://w3id.org/np/RA_6CsM56gRUw5F1G7StJvgSiaBjwqwa4vg4dp4Pez6fs/Head"
}, {
  "@graph" : [ {
    "@id" : "https://doi.org/10.48550/arXiv.2402.06764",
    "@type" : [ "http://www.w3.org/ns/prov#Entity" ],
    "http://purl.org/dc/terms/title" : [ {
      "@value" : "GLaM: Fine-Tuning Large Language Models for Domain Knowledge Graph Alignment via Neighborhood Partitioning and Generative Subgraph Encoding"
    } ],
    "http://purl.org/spar/cito/describes" : [ {
      "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#GLaMLLMSummarization"
    }, {
      "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#GLaMNodeDescriptorsAdjacencySummarization"
    }, {
      "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#GLaMRelationalGrouping"
    }, {
      "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#GLaMTriples"
    } ],
    "http://purl.org/spar/cito/discusses" : [ {
      "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#FewShotPrompting"
    }, {
      "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#GNNLLMJointModelCoupling"
    }, {
      "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#GNNLLMSoftPrompting"
    }, {
      "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#RetrievalAugmentedGeneration"
    } ]
  }, {
    "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#FewShotPrompting",
    "@type" : [ "http://purl.org/spar/fabio/Workflow" ],
    "http://www.w3.org/2000/01/rdf-schema#label" : [ {
      "@value" : "Few-Shot Prompting"
    } ]
  }, {
    "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#GLaMLLMSummarization",
    "@type" : [ "http://purl.org/spar/fabio/Workflow" ],
    "http://purl.org/dc/terms/subject" : [ {
      "@id" : "https://neverblink.eu/ontologies/llm-kg/categories#KGEnhancedLLMPretraining"
    } ],
    "http://www.w3.org/2000/01/rdf-schema#comment" : [ {
      "@value" : "This method leverages the LLM's generative capabilities to rewrite or summarize the encoded graph statements into more coherent representations for fine-tuning. The goal is to enhance semantic alignment between the KG and the LLM's vocabulary, thereby improving the LLM's factual recall and multi-hop reasoning after training."
    } ],
    "http://www.w3.org/2000/01/rdf-schema#label" : [ {
      "@value" : "GLaM (LLM Summarization)"
    } ],
    "https://neverblink.eu/ontologies/llm-kg/hasTopCategory" : [ {
      "@id" : "https://neverblink.eu/ontologies/llm-kg/top-categories#KGEnhancedLLM"
    } ]
  }, {
    "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#GLaMNodeDescriptorsAdjacencySummarization",
    "@type" : [ "http://purl.org/spar/fabio/Workflow" ],
    "http://purl.org/dc/terms/subject" : [ {
      "@id" : "https://neverblink.eu/ontologies/llm-kg/categories#KGEnhancedLLMPretraining"
    } ],
    "http://www.w3.org/2000/01/rdf-schema#comment" : [ {
      "@value" : "This method combines multiple encoding strategies, specifically using LLM's zero-shot capabilities to create text-based node descriptors from the k-hop context subgraph, utilizing adjacency lists, and performing summarization. This comprehensive approach aims to instill robust graph-based reasoning capabilities into the LLM via fine-tuning."
    } ],
    "http://www.w3.org/2000/01/rdf-schema#label" : [ {
      "@value" : "GLaM (Node Descriptors, Adjacency Lists, and Summarization Combination)"
    } ],
    "https://neverblink.eu/ontologies/llm-kg/hasTopCategory" : [ {
      "@id" : "https://neverblink.eu/ontologies/llm-kg/top-categories#KGEnhancedLLM"
    } ]
  }, {
    "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#GLaMRelationalGrouping",
    "@type" : [ "http://purl.org/spar/fabio/Workflow" ],
    "http://purl.org/dc/terms/subject" : [ {
      "@id" : "https://neverblink.eu/ontologies/llm-kg/categories#KGEnhancedLLMPretraining"
    } ],
    "http://www.w3.org/2000/01/rdf-schema#comment" : [ {
      "@value" : "This GLaM variant encodes the neighborhood subgraph by including the entire adjacency list of the central node or partitioning neighbors based on relation types. This strategy is used to fine-tune the LLM to better understand graph structure for improved knowledge expression."
    } ],
    "http://www.w3.org/2000/01/rdf-schema#label" : [ {
      "@value" : "GLaM (Relational Grouping)"
    } ],
    "https://neverblink.eu/ontologies/llm-kg/hasTopCategory" : [ {
      "@id" : "https://neverblink.eu/ontologies/llm-kg/top-categories#KGEnhancedLLM"
    } ]
  }, {
    "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#GLaMTriples",
    "@type" : [ "http://purl.org/spar/fabio/Workflow" ],
    "http://purl.org/dc/terms/subject" : [ {
      "@id" : "https://neverblink.eu/ontologies/llm-kg/categories#KGEnhancedLLMPretraining"
    } ],
    "http://www.w3.org/2000/01/rdf-schema#comment" : [ {
      "@value" : "This method is a specific implementation within the GLaM framework where the neighborhood subgraph is encoded into (source, relation, target) triples for fine-tuning. It aims to improve the LLM's factual reasoning by embedding graph knowledge directly into its parameters during the training phase."
    } ],
    "http://www.w3.org/2000/01/rdf-schema#label" : [ {
      "@value" : "GLaM (Triples)"
    } ],
    "https://neverblink.eu/ontologies/llm-kg/hasTopCategory" : [ {
      "@id" : "https://neverblink.eu/ontologies/llm-kg/top-categories#KGEnhancedLLM"
    } ]
  }, {
    "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#GNNLLMJointModelCoupling",
    "@type" : [ "http://purl.org/spar/fabio/Workflow" ],
    "http://www.w3.org/2000/01/rdf-schema#label" : [ {
      "@value" : "GNN-LLM Joint Model Coupling"
    } ]
  }, {
    "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#GNNLLMSoftPrompting",
    "@type" : [ "http://purl.org/spar/fabio/Workflow" ],
    "http://www.w3.org/2000/01/rdf-schema#label" : [ {
      "@value" : "GNN-LLM Soft Prompting"
    } ]
  }, {
    "@id" : "https://neverblink.eu/ontologies/llm-kg/methods#RetrievalAugmentedGeneration",
    "@type" : [ "http://purl.org/spar/fabio/Workflow" ],
    "http://www.w3.org/2000/01/rdf-schema#label" : [ {
      "@value" : "Retrieval Augmented Generation (RAG)"
    } ]
  } ],
  "@id" : "https://w3id.org/np/RA_6CsM56gRUw5F1G7StJvgSiaBjwqwa4vg4dp4Pez6fs/assertion"
}, {
  "@graph" : [ {
    "@id" : "https://w3id.org/np/RA_6CsM56gRUw5F1G7StJvgSiaBjwqwa4vg4dp4Pez6fs/assertion",
    "http://www.w3.org/ns/prov#wasAttributedTo" : [ {
      "@id" : "https://neverblink.eu/ontologies/llm-kg/agent"
    } ],
    "http://www.w3.org/ns/prov#wasDerivedFrom" : [ {
      "@id" : "https://doi.org/10.48550/arXiv.2402.06764"
    } ]
  } ],
  "@id" : "https://w3id.org/np/RA_6CsM56gRUw5F1G7StJvgSiaBjwqwa4vg4dp4Pez6fs/provenance"
}, {
  "@graph" : [ {
    "@id" : "https://w3id.org/np/RA_6CsM56gRUw5F1G7StJvgSiaBjwqwa4vg4dp4Pez6fs",
    "http://purl.org/dc/terms/created" : [ {
      "@type" : "http://www.w3.org/2001/XMLSchema#dateTime",
      "@value" : "2026-02-26T15:57:20.083Z"
    } ],
    "http://purl.org/dc/terms/creator" : [ {
      "@id" : "https://neverblink.eu/ontologies/llm-kg/agent"
    } ],
    "http://purl.org/nanopub/x/hasNanopubType" : [ {
      "@id" : "https://neverblink.eu/ontologies/llm-kg/PaperAssessmentResult"
    } ],
    "http://www.w3.org/2000/01/rdf-schema#label" : [ {
      "@value" : "LLM-KG assessment for paper 10.48550/arXiv.2402.06764"
    } ]
  }, {
    "@id" : "https://w3id.org/np/RA_6CsM56gRUw5F1G7StJvgSiaBjwqwa4vg4dp4Pez6fs/sig",
    "http://purl.org/nanopub/x/hasAlgorithm" : [ {
      "@value" : "RSA"
    } ],
    "http://purl.org/nanopub/x/hasPublicKey" : [ {
      "@value" : "MIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEAwNz2QK3SEifno78S7+48zUB0xpTex3mAzW73ZimHqNcdEMU5/apslrGrTHGFAt/Chocgo++r6JQp5ygY7NyJHGWdaIqnt85pjX4PbNfLAvapyUO00qZP34fY61w4eZ9UMtleWEsmZKRtQPyJ8ODl46i/rfPuZlcJGpM9Nmy5mpGWuepqIEvF4a/t7pLVeCEDFSYXT+yaiygt6ynIK5f7TtEDhZpeUf/Q74WhMPJXm4yTU/hqOX4IW+50kWHNArGGZwUaXwzyG6M3Zd6UMModryGkLqS4H/MSE3ZA1Ylnms7BfWLEXhMWlaKi6HRV4nGRDLhxVSi9LSRi3LWKLhNIIQIDAQAB"
    } ],
    "http://purl.org/nanopub/x/hasSignature" : [ {
      "@value" : "u6dPlUuTUn1QedW6Fo7ljSYw2G4COewda0DpI0s95BWkF2vMzjoMKMokBVugNbLAF7WgBfWLNdwTqbnSBYf9xRted+aca4PBWgEF/7gswieTkJn0cmbIkRP85Fl+j9VWoAgVzb4c5Zu8KcI3cXo5W7LLfNx6yCW1fgamArf4JmksrxJIsftt9gcgHTJKFMt3XsI0WBTmVF3hcrJqj4tf/vAOIiuEnHkcMK2hOk4+0BAjf9MXAKG1b5ufatAxOHCQxqwe4dTz7da/ClVar+D0yMszjGQHpWfsEPcVvWz6hxmK2/0PueA/cKu4mrpSyACehPyNjjEwIqWSKn/XqMqzCg=="
    } ],
    "http://purl.org/nanopub/x/hasSignatureTarget" : [ {
      "@id" : "https://w3id.org/np/RA_6CsM56gRUw5F1G7StJvgSiaBjwqwa4vg4dp4Pez6fs"
    } ],
    "http://purl.org/nanopub/x/signedBy" : [ {
      "@id" : "https://neverblink.eu/ontologies/llm-kg/agent"
    } ]
  } ],
  "@id" : "https://w3id.org/np/RA_6CsM56gRUw5F1G7StJvgSiaBjwqwa4vg4dp4Pez6fs/pubinfo"
} ]