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 26–45 of 45 papers

TitleStatusHype
On the Role of Conceptualization in Commonsense Knowledge Graph ConstructionCode1
Revisiting Evaluation of Knowledge Base Completion Models—0
Debate Dynamics for Human-comprehensible Fact-checking on Knowledge Graphs—0
Reasoning on Knowledge Graphs with Debate DynamicsCode1
KG-BERT: BERT for Knowledge Graph CompletionCode0
A Relational Memory-based Embedding Model for Triple Classification and Search PersonalizationCode0
Neural Markov Logic Networks—0
Logic Rules Powered Knowledge Graph Embedding—0
Knowledge Representation Learning: A Quantitative ReviewCode2
Differentiating Concepts and Instances for Knowledge Graph EmbeddingCode0
DOLORES: Deep Contextualized Knowledge Graph Embeddings—0
A Multimodal Translation-Based Approach for Knowledge Graph Representation Learning—0
Accurate Text-Enhanced Knowledge Graph Representation Learning—0
Does William Shakespeare REALLY Write Hamlet? Knowledge Representation Learning with ConfidenceCode0
Knowledge Representation via Joint Learning of Sequential Text and Knowledge Graphs—0
Image-embodied Knowledge Representation LearningCode0
Neighborhood Mixture Model for Knowledge Base Completion—0
Probabilistic Reasoning via Deep Learning: Neural Association Models—0
Knowlege Graph Embedding by Flexible Translation—0
Learning Entity and Relation Embeddings for Knowledge Graph CompletionCode0
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Benchmark Results

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