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
Knowing What, How and Why: A Near Complete Solution for Aspect-based Sentiment Analysis
In this paper, we introduce a new subtask under ABSA, named aspect sentiment triplet extraction (ASTE).
Position-Aware Tagging for Aspect Sentiment Triplet Extraction
Our observation is that the three elements within a triplet are highly related to each other, and this motivates us to build a joint model to extract such triplets using a sequence tagging approach.
A Multi-task Learning Framework for Opinion Triplet Extraction
GeneZC/OTE-MTL
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Findings of the Association for Computational Linguistics 2020
The state-of-the-art Aspect-based Sentiment Analysis (ABSA) approaches are mainly based on either detecting aspect terms and their corresponding sentiment polarities, or co-extracting aspect and opinion terms.
Grid Tagging Scheme for Aspect-oriented Fine-grained Opinion Extraction
NJUNLP/GTS
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Findings of the Association for Computational Linguistics 2020
To validate the feasibility and compatibility of GTS, we implement three different GTS models respectively based on CNN, BiLSTM, and BERT, and conduct experiments on the aspect-oriented opinion pair extraction and opinion triplet extraction datasets.
A Unified Generative Framework for Aspect-Based Sentiment Analysis
Aspect-based Sentiment Analysis (ABSA) aims to identify the aspect terms, their corresponding sentiment polarities, and the opinion terms.
Bidirectional Machine Reading Comprehension for Aspect Sentiment Triplet Extraction
NKU-IIPLab/BMRC
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Aspect sentiment triplet extraction (ASTE), which aims to identify aspects from review sentences along with their corresponding opinion expressions and sentiments, is an emerging task in fine-grained opinion mining.
Learning Span-Level Interactions for Aspect Sentiment Triplet Extraction
chiayewken/Span-ASTE
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ACL 2021
Aspect Sentiment Triplet Extraction (ASTE) is the most recent subtask of ABSA which outputs triplets of an aspect target, its associated sentiment, and the corresponding opinion term.
Towards Generative Aspect-Based Sentiment Analysis
IsakZhang/Generative-ABSA
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ACL 2021
Aspect-based sentiment analysis (ABSA) has received increasing attention recently.
Aspect Sentiment Triplet Extraction Using Reinforcement Learning
We first focus on sentiments expressed in a sentence, then identify the target aspect and opinion terms for that sentiment.
PASTE: A Tagging-Free Decoding Framework Using Pointer Networks for Aspect Sentiment Triplet Extraction
rajdeep345/paste
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EMNLP 2021
Aspect Sentiment Triplet Extraction (ASTE) deals with extracting opinion triplets, consisting of an opinion target or aspect, its associated sentiment, and the corresponding opinion term/span explaining the rationale behind the sentiment.
