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Relation Classification
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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
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Discourse Relation Embeddings: Representing the Relations between Discourse Segments in Social Media
Incremental Few-shot Text Classification with Multi-round New Classes: Formulation, Dataset and System
Extracting Temporal Event Relation with Syntax-guided Graph Transformer
Revisiting Few-shot Relation Classification: Evaluation Data and Classification Schemes
Multi-Task Attentive Residual Networks for Argument Mining
"Laughing at you or with you": The Role of Sarcasm in Shaping the Disagreement Space
Structured Prediction as Translation between Augmented Natural Languages
Adaptive Prototypical Networks with Label Words and Joint Representation Learning for Few-Shot Relation Classification
Syntax-Enhanced Pre-trained Model
Towards Incorporating Entity-specific Knowledge Graph Information in Predicting Drug-Drug Interactions
Document-Level Relation Extraction with Reconstruction
R$^2$-Net: Relation of Relation Learning Network for Sentence Semantic Matching
DDRel: A New Dataset for Interpersonal Relation Classification in Dyadic Dialogues
Joint Extraction of Entity and Relation with Information Redundancy Elimination
Entity Recognition and Relation Extraction from Scientific and Technical Texts in Russian
Zero-shot Relation Classification from Side Information
CODER: Knowledge infused cross-lingual medical term embedding for term normalization
Investigation of BERT Model on Biomedical Relation Extraction Based on Revised Fine-tuning Mechanism
Logic-guided Semantic Representation Learning for Zero-Shot Relation Classification
RH-Net: Improving Neural Relation Extraction via Reinforcement Learning and Hierarchical Relational Searching
Meta-Learning for Neural Relation Classification with Distant Supervision
Learning to Decouple Relations: Few-Shot Relation Classification with Entity-Guided Attention and Confusion-Aware Training
The RELX Dataset and Matching the Multilingual Blanks for Cross-Lingual Relation Classification
TDRE: A Tensor Decomposition Based Approach for Relation Extraction
Relation Classification as Two-way Span-Prediction
Semi-supervised Relation Extraction via Incremental Meta Self-Training
LUKE: Deep Contextualized Entity Representations with Entity-aware Self-attention
AutoRC: Improving BERT Based Relation Classification Models via Architecture Search
The Devil is the Classifier: Investigating Long Tail Relation Classification with Decoupling Analysis
Semantic Relations and Deep Learning
UPB at SemEval-2020 Task 6: Pretrained Language Models for Definition Extraction
HOSE-Net: Higher Order Structure Embedded Network for Scene Graph Generation
NLPContributions: An Annotation Scheme for Machine Reading of Scholarly Contributions in Natural Language Processing Literature
Human brain activity for machine attention
A Data-driven Approach for Noise Reduction in Distantly Supervised Biomedical Relation Extraction
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