SOTAVerified

Relation Classification

Relation Classification is the task of identifying the semantic relation holding between two nominal entities in text.

Source: Structure Regularized Neural Network for Entity Relation Classification for Chinese Literature Text

Papers

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Showing 1–10 of 445 papers

TitleStatusHype
Comparative Analysis of AI Agent Architectures for Entity Relationship ClassificationCode0
Towards a More Generalized Approach in Open Relation ExtractionCode0
Towards Rehearsal-Free Continual Relation Extraction: Capturing Within-Task Variance with Adaptive PromptingCode0
Probing LLMs for Multilingual Discourse Generalization Through a Unified Label SetCode0
HFGCN:Hypergraph Fusion Graph Convolutional Networks for Skeleton-Based Action Recognition—0
Facial Dynamics in Video: Instruction Tuning for Improved Facial Expression Perception and Contextual AwarenessCode1
GLiREL -- Generalist Model for Zero-Shot Relation ExtractionCode3
AmalREC: A Dataset for Relation Extraction and Classification Leveraging Amalgamation of Large Language Models—0
Annotations for Exploring Food Tweets From Multiple AspectsCode0
Diversity Over Quantity: A Lesson From Few Shot Relation Classification—0
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All datasetsTACREDSemEval-2010 Task-8FewRelAbstRCT - NeoplasmCDCPDiscoveryDRI CorpusMATRES

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ResAttArgMacro F170.92—Unverified