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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–45 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
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
Differentially Private Federated Knowledge Graphs EmbeddingCode1
Membership Inference Attacks on Knowledge Graphs—0
CoDEx: A Comprehensive Knowledge Graph Completion BenchmarkCode1
TransINT: Embedding Implication Rules in Knowledge Graphs with Isomorphic Intersections of Linear SubspacesCode0
Learning Structured Embeddings of Knowledge Graphs with Adversarial Learning Framework—0
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
Show:102550

Benchmark Results

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