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
Repurposing Knowledge Graph Embeddings for Triple Representation via Weak SupervisionCode0
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
Membership Inference Attacks on Knowledge Graphs—0
TransINT: Embedding Implication Rules in Knowledge Graphs with Isomorphic Intersections of Linear SubspacesCode0
Learning Structured Embeddings of Knowledge Graphs with Adversarial Learning Framework—0
Revisiting Evaluation of Knowledge Base Completion Models—0
Debate Dynamics for Human-comprehensible Fact-checking on Knowledge Graphs—0
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Benchmark Results

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