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Aspect Sentiment Triplet Extraction

Aspect Sentiment Triplet Extraction (ASTE) is the task of extracting the triplets of target entities, their associated sentiment, and opinion spans explaining the reason for the sentiment.

Papers

Showing 110 of 52 papers

TitleStatusHype
Grid Tagging Scheme for Aspect-oriented Fine-grained Opinion ExtractionCode1
Bidirectional Machine Reading Comprehension for Aspect Sentiment Triplet ExtractionCode1
Enhanced Multi-Channel Graph Convolutional Network for Aspect Sentiment Triplet ExtractionCode1
A Multi-task Learning Framework for Opinion Triplet ExtractionCode1
A Unified Generative Framework for Aspect-Based Sentiment AnalysisCode1
A Robustly Optimized BMRC for Aspect Sentiment Triplet ExtractionCode1
A semantically enhanced dual encoder for aspect sentiment triplet extractionCode1
CONTRASTE: Supervised Contrastive Pre-training With Aspect-based Prompts For Aspect Sentiment Triplet ExtractionCode1
Aspect Sentiment Triplet Extraction Using Reinforcement LearningCode1
Inheriting the Wisdom of Predecessors: A Multiplex Cascade Framework for Unified Aspect-based Sentiment AnalysisCode1
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