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 31–40 of 45 papers

TitleStatusHype
On Large-scale Evaluation of Embedding Models for Knowledge Graph Completion—0
Accurate Text-Enhanced Knowledge Graph Representation Learning—0
Probabilistic Reasoning via Deep Learning: Neural Association Models—0
Using Knowledge Graphs for Performance Prediction of Modular Optimization Algorithms—0
Debate Dynamics for Human-comprehensible Fact-checking on Knowledge Graphs—0
Pre-training Language Model Incorporating Domain-specific Heterogeneous Knowledge into A Unified Representation—0
Improving Knowledge Graph Representation Learning by Structure Contextual Pre-training—0
Triple Classification for Scholarly Knowledge Graph Completion—0
Revisiting Evaluation of Knowledge Base Completion Models—0
Self-supervised Quantized Representation for Seamlessly Integrating Knowledge Graphs with Large Language Models—0
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Benchmark Results

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