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 21–30 of 45 papers

TitleStatusHype
A Relational Memory-based Embedding Model for Triple Classification and Search PersonalizationCode0
Repurposing Knowledge Graph Embeddings for Triple Representation via Weak SupervisionCode0
TransINT: Embedding Implication Rules in Knowledge Graphs with Isomorphic Intersections of Linear SubspacesCode0
Learning Structured Embeddings of Knowledge Graphs with Adversarial Learning Framework—0
A Multimodal Translation-Based Approach for Knowledge Graph Representation Learning—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
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Benchmark Results

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