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

Showing 276–300 of 445 papers

TitleStatusHype
Zero-shot Event Causality Identification with Question Answering—0
Zero-shot Relation Classification as Textual Entailment—0
Few-Shot Text Classification with Edge-Labeling Graph Neural Network-Based Prototypical Network—0
From Learning-to-Match to Learning-to-Discriminate:Global Prototype Learning for Few-shot Relation Classification—0
Frowning Frodo, Wincing Leia, and a Seriously Great Friendship: Learning to Classify Emotional Relationships of Fictional Characters—0
Function-words Enhanced Attention Networks for Few-Shot Inverse Relation Classification—0
Generate Triggers in Neural Relation Extraction—0
Generative Prompt Tuning for Relation Classification—0
Global Context for improving recognition of Online Handwritten Mathematical Expressions—0
Global Normalization of Convolutional Neural Networks for Joint Entity and Relation Classification—0
Gorynych Transformer at SemEval-2020 Task 6: Multi-task Learning for Definition Extraction—0
Hands-on Learning to Search for Structured Prediction—0
HFGCN:Hypergraph Fusion Graph Convolutional Networks for Skeleton-Based Action Recognition—0
HOSE-Net: Higher Order Structure Embedded Network for Scene Graph Generation—0
Human brain activity for machine attention—0
Implicit Discourse Relation Classification via Multi-Task Neural Networks—0
Implicit Discourse Relation Classification For Nigerian Pidgin—0
Implicit Discourse Relation Classification: We Need to Talk about Evaluation—0
Improved Relation Classification by Deep Recurrent Neural Networks with Data Augmentation—0
Improved Temporal Relation Classification using Dependency Parses and Selective Crowdsourced Annotations—0
Improving Event Temporal Relation Classification via Auxiliary Label-Aware Contrastive Learning—0
Improving Few-Shot Relation Classification by Prototypical Representation Learning with Definition Text—0
Improving Implicit Discourse Relation Classification by Modeling Inter-dependencies of Discourse Units in a Paragraph—0
Improving Relation Classification by Entity Pair Graph—0
Improving Scholarly Knowledge Representation: Evaluating BERT-based Models for Scientific Relation Classification—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepEx (zero-shot top-10)F176.4—Unverified
2DeepStruct multi-taskF174.9—Unverified
3LUKE 483MF172.7—Unverified
4K-AdapterF172—Unverified
5KnowBERTF171.5—Unverified
6MTB Baldini Soares et al. (2019)F171.5—Unverified
7RoBERTaF171.3—Unverified
8SpanBERTF170.8—Unverified
9ERNIEF168—Unverified
10ERNIEF167.97—Unverified
#ModelMetricClaimedVerifiedStatus
1BRCNNF186.3—Unverified
2DRNNsF186.1—Unverified
3depLCNN + NSF185.6—Unverified
4SDP-LSTMF183.7—Unverified
5DepNNF183.6—Unverified
6MVRNNF182.4—Unverified
#ModelMetricClaimedVerifiedStatus
1DeepStruct multi-task w/ finetuneF1 (10-way 1-shot)97.8—Unverified
2DeepEx (zero-shot top-10)F192.9—Unverified
3DeepStruct multi-taskF1 (10-way 1-shot)92.2—Unverified
4Deepstruct zero-shotF1 (10-way 1-shot)67.6—Unverified
5DeepEx (zero-shot top-1)F148.8—Unverified
#ModelMetricClaimedVerifiedStatus
1ResAttArgMacro F170.92—Unverified
#ModelMetricClaimedVerifiedStatus
1ResAttArgMacro F142.95—Unverified
#ModelMetricClaimedVerifiedStatus
1BERT1:1 Accuracy20.6—Unverified
#ModelMetricClaimedVerifiedStatus
1ResAttArgMacro F137.72—Unverified
#ModelMetricClaimedVerifiedStatus
1SCS-EEREF10.83—Unverified