Aspect Sentiment Triplet Extraction
25 papers with code • 3 benchmarks • 1 datasets
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.
ASTE-Data-V2
Most implemented papers
Aspect-Sentiment-Multiple-Opinion Triplet Extraction
Aspect Sentiment Triplet Extraction (ASTE) aims to extract aspect term (aspect), sentiment and opinion term (opinion) triplets from sentences and can tell a complete story, i. e., the discussed aspect, the sentiment toward the aspect, and the cause of the sentiment.
A Span-level Bidirectional Network for Aspect Sentiment Triplet Extraction
Aspect Sentiment Triplet Extraction (ASTE) is a new fine-grained sentiment analysis task that aims to extract triplets of aspect terms, sentiments, and opinion terms from review sentences.
Inheriting the Wisdom of Predecessors: A Multiplex Cascade Framework for Unified Aspect-based Sentiment Analysis
scofield7419/UABSA-SyMux
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Conference 2022
So far, aspect-based sentiment analysis (ABSA) has involved with total seven subtasks, in which, however the interactions among them have been left unexplored sufficiently.
Structural Bias for Aspect Sentiment Triplet Extraction
genezc/structbias
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COLING 2022
Thus, a natural question arises: Is structural bias still a necessity in the context of PLMs?
STAGE: Span Tagging and Greedy Inference Scheme for Aspect Sentiment Triplet Extraction
cciiplab/stage
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Hence, we propose a novel approach, Span TAgging and Greedy infErence (STAGE), to extract sentiment triplets in span-level, where each span may consist of multiple words and play different roles simultaneously.
A Better Choice: Entire-space Datasets for Aspect Sentiment Triplet Extraction
l294265421/entire-space-aste
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Aspect sentiment triplet extraction (ASTE) aims to extract aspect term, sentiment and opinion term triplets from sentences.
Improving Span-based Aspect Sentiment Triplet Extraction with Abundant Syntax Knowledge
2023-MindSpore-4/Code12
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journal 2022
Aspect sentiment triplet extraction is a subtask of aspect based sentiment analysis, which has attracted considerable attention in recent years.
MvP: Multi-view Prompting Improves Aspect Sentiment Tuple Prediction
ZubinGou/multi-view-prompting
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Generative methods greatly promote aspect-based sentiment analysis via generating a sequence of sentiment elements in a specified format.
Measuring Your ASTE Models in The Wild: A Diversified Multi-domain Dataset For Aspect Sentiment Triplet Extraction
njunlp/dmaste
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In this paper, we introduce a new dataset, named DMASTE, which is manually annotated to better fit real-world scenarios by providing more diverse and realistic reviews for the task.
A semantically enhanced dual encoder for aspect sentiment triplet extraction
baosir529/dual-encoder4aste
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Aspect sentiment triplet extraction (ASTE) is a crucial subtask of aspect-based sentiment analysis (ABSA) that aims to comprehensively identify sentiment triplets.
