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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 41–50 of 52 papers

TitleStatusHype
A Better Choice: Entire-space Datasets for Aspect Sentiment Triplet ExtractionCode0
UnifiedABSA: A Unified ABSA Framework Based on Multi-task Instruction Tuning—0
A Multi-Task Dual-Tree Network for Aspect Sentiment Triplet Extraction—0
Pretrained Language Encoders are Natural Tagging Frameworks for Aspect Sentiment Triplet Extraction—0
Nonautoregressive Encoder-Decoder Neural Framework for End-to-End Aspect-Based Sentiment Triplet Extraction—0
SAMBERT: Improve Aspect Sentiment Triplet Extraction by Segmenting the Attention Maps of BERT—0
Aspect-Sentiment-Multiple-Opinion Triplet ExtractionCode0
Explicit Interaction Network for Aspect Sentiment Triplet Extraction—0
Semantic and Syntactic Enhanced Aspect Sentiment Triplet Extraction—0
Tell Me Why You Feel That Way: Processing Compositional Dependency for Tree-LSTM Aspect Sentiment Triplet Extraction (TASTE)—0
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