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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

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Showing 21–30 of 52 papers

TitleStatusHype
Domain-Expanded ASTE: Rethinking Generalization in Aspect Sentiment Triplet ExtractionCode0
MvP: Multi-view Prompting Improves Aspect Sentiment Tuple PredictionCode1
A Weak Supervision Approach for Few-Shot Aspect Based Sentiment—0
Improving Span-based Aspect Sentiment Triplet Extraction with Abundant Syntax KnowledgeCode0
A Better Choice: Entire-space Datasets for Aspect Sentiment Triplet ExtractionCode0
STAGE: Span Tagging and Greedy Inference Scheme for Aspect Sentiment Triplet ExtractionCode1
UnifiedABSA: A Unified ABSA Framework Based on Multi-task Instruction Tuning—0
A Multi-Task Dual-Tree Network for Aspect Sentiment Triplet Extraction—0
Structural Bias for Aspect Sentiment Triplet ExtractionCode1
Pretrained Language Encoders are Natural Tagging Frameworks for Aspect Sentiment Triplet Extraction—0
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