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 1–45 of 45 papers

TitleStatusHype
Knowledge Representation Learning: A Quantitative ReviewCode2
Exploring Large Language Models for Knowledge Graph CompletionCode1
Differentially Private Federated Knowledge Graphs EmbeddingCode1
GreenKGC: A Lightweight Knowledge Graph Completion MethodCode1
Reasoning on Knowledge Graphs with Debate DynamicsCode1
On the Role of Conceptualization in Commonsense Knowledge Graph ConstructionCode1
CoDEx: A Comprehensive Knowledge Graph Completion BenchmarkCode1
Language Models as Knowledge EmbeddingsCode1
Structure Pretraining and Prompt Tuning for Knowledge Graph TransferCode1
Accurate Text-Enhanced Knowledge Graph Representation Learning—0
A Multimodal Translation-Based Approach for Knowledge Graph Representation Learning—0
Debate Dynamics for Human-comprehensible Fact-checking on Knowledge Graphs—0
DOLORES: Deep Contextualized Knowledge Graph Embeddings—0
Efficient Relational Context Perception for Knowledge Graph Completion—0
Improving Knowledge Graph Representation Learning by Structure Contextual Pre-training—0
Learning Structured Embeddings of Knowledge Graphs with Adversarial Learning Framework—0
Logic Rules Powered Knowledge Graph Embedding—0
Membership Inference Attacks on Knowledge Graphs—0
Neighborhood Mixture Model for Knowledge Base Completion—0
Neural Markov Logic Networks—0
OneRel:Joint Entity and Relation Extraction with One Module in One Step—0
On Large-scale Evaluation of Embedding Models for Knowledge Graph Completion—0
Probabilistic Reasoning via Deep Learning: Neural Association Models—0
Revisiting Evaluation of Knowledge Base Completion Models—0
Self-supervised Quantized Representation for Seamlessly Integrating Knowledge Graphs with Large Language Models—0
Structural damage detection via hierarchical damage information with volumetric assessment—0
Pre-training Language Model Incorporating Domain-specific Heterogeneous Knowledge into A Unified Representation—0
Triple Classification for Scholarly Knowledge Graph Completion—0
Using Knowledge Graphs for Performance Prediction of Modular Optimization Algorithms—0
Knowledge Representation via Joint Learning of Sequential Text and Knowledge Graphs—0
Knowlege Graph Embedding by Flexible Translation—0
Iteratively Learning Representations for Unseen Entities with Inter-Rule CorrelationsCode0
KG-BERT: BERT for Knowledge Graph CompletionCode0
Knowledge Graph Refinement based on Triplet BERT-NetworksCode0
Image-embodied Knowledge Representation LearningCode0
Repurposing Knowledge Graph Embeddings for Triple Representation via Weak SupervisionCode0
TransINT: Embedding Implication Rules in Knowledge Graphs with Isomorphic Intersections of Linear SubspacesCode0
Embedding Ontologies via Incorporating Extensional and Intensional KnowledgeCode0
Learning Entity and Relation Embeddings for Knowledge Graph CompletionCode0
Does William Shakespeare REALLY Write Hamlet? Knowledge Representation Learning with ConfidenceCode0
Leveraging Pre-trained Language Models for Time Interval Prediction in Text-Enhanced Temporal Knowledge GraphsCode0
A Study on Knowledge Graph Embeddings and Graph Neural Networks for Web Of ThingsCode0
Progressive Knowledge Graph CompletionCode0
Differentiating Concepts and Instances for Knowledge Graph EmbeddingCode0
A Relational Memory-based Embedding Model for Triple Classification and Search PersonalizationCode0
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Benchmark Results

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