SOTAVerified

Triple Classification

Triple classification aims to judge whether a given triple (h, r, t) is correct or not with respect to the knowledge graph.

Papers

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Showing 11–20 of 45 papers

TitleStatusHype
Self-supervised Quantized Representation for Seamlessly Integrating Knowledge Graphs with Large Language Models—0
Efficient Relational Context Perception for Knowledge Graph Completion—0
Structural damage detection via hierarchical damage information with volumetric assessment—0
Progressive Knowledge Graph CompletionCode0
Embedding Ontologies via Incorporating Extensional and Intensional KnowledgeCode0
A Study on Knowledge Graph Embeddings and Graph Neural Networks for Web Of ThingsCode0
Leveraging Pre-trained Language Models for Time Interval Prediction in Text-Enhanced Temporal Knowledge GraphsCode0
Iteratively Learning Representations for Unseen Entities with Inter-Rule CorrelationsCode0
Using Knowledge Graphs for Performance Prediction of Modular Optimization Algorithms—0
Knowledge Graph Refinement based on Triplet BERT-NetworksCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TransC (bern)Accuracy93.8—Unverified