Matches in Nanopublications for { ?s ?p ?o <https://w3id.org/np/RAQKBbEQ--W2vSHDaZ0LrgiFnCkSkeH3JX7ZrENSNnS4c/assertion>. }
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- arXiv.2403.07311 type Entity assertion.
- Analogy type Workflow assertion.
- ConvRot type Workflow assertion.
- DistMult type Workflow assertion.
- TransE type Workflow assertion.
- CompleX type Workflow assertion.
- ConGLR type Workflow assertion.
- KnowledgeGraphLargeLanguageModel type Workflow assertion.
- RESCAL type Workflow assertion.
- WsGAT type Workflow assertion.
- Analogy label "Analogy" assertion.
- ConvRot label "ConvRot" assertion.
- DistMult label "DistMult" assertion.
- TransE label "TransE" assertion.
- CompleX label "CompleX" assertion.
- ConGLR label "ConGLR" assertion.
- KnowledgeGraphLargeLanguageModel label "Knowledge Graph Large Language Model (KG-LLM)" assertion.
- RESCAL label "RESCAL" assertion.
- WsGAT label "wsGAT" assertion.
- Analogy 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." assertion.
- ConvRot 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." assertion.
- DistMult 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." assertion.
- TransE 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." assertion.
- CompleX 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." assertion.
- ConGLR 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." assertion.
- KnowledgeGraphLargeLanguageModel 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." assertion.
- RESCAL 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." assertion.
- WsGAT 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." assertion.
- KnowledgeGraphLargeLanguageModel subject LLMAugmentedKGCompletion assertion.
- arXiv.2403.07311 title "Knowledge Graph Large Language Model (KG-LLM) for Link Prediction" assertion.
- arXiv.2403.07311 describes KnowledgeGraphLargeLanguageModel assertion.
- arXiv.2403.07311 discusses Analogy assertion.
- arXiv.2403.07311 discusses ConvRot assertion.
- arXiv.2403.07311 discusses DistMult assertion.
- arXiv.2403.07311 discusses TransE assertion.
- arXiv.2403.07311 discusses CompleX assertion.
- arXiv.2403.07311 discusses ConGLR assertion.
- arXiv.2403.07311 discusses RESCAL assertion.
- arXiv.2403.07311 discusses WsGAT assertion.
- KnowledgeGraphLargeLanguageModel hasTopCategory LLMAugmentedKG assertion.