@prefix this: . @prefix sub: . @prefix np: . @prefix dct: . @prefix xsd: . @prefix rdfs: . @prefix prov: . @prefix npx: . sub:Head { this: np:hasAssertion sub:assertion; np:hasProvenance sub:provenance; np:hasPublicationInfo sub:pubinfo; a np:Nanopublication . } sub:assertion { dct:title "Knowledge Graph Large Language Model (KG-LLM) for Link Prediction"; ; , , , , , , , ; a prov:Entity . a ; rdfs:comment "Analogy is a knowledge graph embedding model designed to capture graph structures. It is used as a baseline for comparison against the KG-LLM framework in multi-hop link prediction tasks."; rdfs:label "Analogy" . a ; rdfs:comment "CompleX utilizes complex embeddings for entities and relations to capture asymmetric relationships in knowledge graphs. It is used as a baseline for comparison against the KG-LLM framework in multi-hop link prediction tasks."; rdfs:label "CompleX" . a ; rdfs:comment "ConGLR is a GNN-based model that leverages context-aware graph representation learning and logical reasoning for improved inductive relation prediction. It is used as a baseline for comparison against the KG-LLM framework."; rdfs:label "ConGLR" . a ; rdfs:comment "ConvRot integrates convolutional networks and rotational embeddings to enhance link prediction performance in knowledge graphs. It is used as a GNN-based baseline for comparison against the KG-LLM framework."; rdfs:label "ConvRot" . a ; rdfs:comment "DistMult represents relations as diagonal matrices for simplicity and efficiency in knowledge graph embedding. It is used as a baseline for comparison against the KG-LLM framework in multi-hop link prediction tasks."; rdfs:label "DistMult" . dct:subject ; a ; rdfs:comment "The KG-LLM framework proposes a novel approach that converts multi-hop knowledge graph paths into structured natural language Chain-of-Thought prompts. These prompts are then used to instruction fine-tune large language models, incorporating In-Context Learning to enhance their performance in multi-hop link prediction and multi-hop relation prediction tasks, leveraging LLMs to complete missing facts within KGs."; rdfs:label "Knowledge Graph Large Language Model (KG-LLM)"; . a ; rdfs:comment "RESCAL is a tensor factorization method used for knowledge graph embedding that captures rich interactions between entities and relations. It is used as a baseline for comparison against the KG-LLM framework in multi-hop link prediction tasks."; rdfs:label "RESCAL" . a ; rdfs:comment "TransE is a traditional knowledge graph embedding model that represents relationships as translations in the embedding space. It is used as a baseline for comparison against the KG-LLM framework in multi-hop link prediction tasks."; rdfs:label "TransE" . a ; rdfs:comment "wsGAT is a graph attention network model that uses weighted self-attention mechanisms to perform various knowledge graph tasks, including link prediction. It is used as a GNN-based baseline for comparison against the KG-LLM framework."; rdfs:label "wsGAT" . } sub:provenance { sub:assertion prov:wasAttributedTo ; prov:wasDerivedFrom . } sub:pubinfo { this: dct:created "2026-03-13T16:03:07.317Z"^^xsd:dateTime; dct:creator ; npx:hasNanopubType ; npx:supersedes ; rdfs:label "LLM-KG assessment for paper 10.48550/arXiv.2403.07311" . sub:sig npx:hasAlgorithm "RSA"; npx:hasPublicKey "MIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEAwNz2QK3SEifno78S7+48zUB0xpTex3mAzW73ZimHqNcdEMU5/apslrGrTHGFAt/Chocgo++r6JQp5ygY7NyJHGWdaIqnt85pjX4PbNfLAvapyUO00qZP34fY61w4eZ9UMtleWEsmZKRtQPyJ8ODl46i/rfPuZlcJGpM9Nmy5mpGWuepqIEvF4a/t7pLVeCEDFSYXT+yaiygt6ynIK5f7TtEDhZpeUf/Q74WhMPJXm4yTU/hqOX4IW+50kWHNArGGZwUaXwzyG6M3Zd6UMModryGkLqS4H/MSE3ZA1Ylnms7BfWLEXhMWlaKi6HRV4nGRDLhxVSi9LSRi3LWKLhNIIQIDAQAB"; npx:hasSignature "M8A86QxaelEblRjE6EJVb/G181uD5Mr5emikye+XbhLXhmpxa/59PdgCAIpnXlJ5g0iwsfFkcaJQnPsyr+8w7kCG/pll0z1V12nxSRBjWL+zhRSWNdqtuXcEgFfHAlxGhYkg49OI7pNLjwtakobWrRmFfoXD4GodW7vFyMwS3GyBGeUlfmO4D4giKTP/ZRQueUldq5qVBIFSaTc7sEbZV7BeJfFsZMZ2aaQVnjcV6k6SYd6sk2Ml6Y1crMoXuaO93e9/MnyGWiwPvoNAo2PmiR8pMHO42BSg8BYLpoN8wa7bfg0UatTJb++KWzwmrKTuALfNR2cKMrnC921loiVDbg=="; npx:hasSignatureTarget this:; npx:signedBy . }