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
Structure Pretraining and Prompt Tuning for Knowledge Graph TransferCode1
Using Knowledge Graphs for Performance Prediction of Modular Optimization Algorithms—0
Knowledge Graph Refinement based on Triplet BERT-NetworksCode0
Repurposing Knowledge Graph Embeddings for Triple Representation via Weak SupervisionCode0
GreenKGC: A Lightweight Knowledge Graph Completion MethodCode1
Language Models as Knowledge EmbeddingsCode1
OneRel:Joint Entity and Relation Extraction with One Module in One Step—0
Improving Knowledge Graph Representation Learning by Structure Contextual Pre-training—0
Triple Classification for Scholarly Knowledge Graph Completion—0
Pre-training Language Model Incorporating Domain-specific Heterogeneous Knowledge into A Unified Representation—0
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Benchmark Results

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