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 1–10 of 45 papers

TitleStatusHype
On Large-scale Evaluation of Embedding Models for Knowledge Graph Completion—0
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
Exploring Large Language Models for Knowledge Graph CompletionCode1
Iteratively Learning Representations for Unseen Entities with Inter-Rule CorrelationsCode0
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Benchmark Results

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