Aspect Sentiment Triplet Extraction

27 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.

Most implemented papers

Knowing What, How and Why: A Near Complete Solution for Aspect-based Sentiment Analysis

xuuuluuu/SemEval-Triplet-data 5 Nov 2019

In this paper, we introduce a new subtask under ABSA, named aspect sentiment triplet extraction (ASTE).

Position-Aware Tagging for Aspect Sentiment Triplet Extraction

xuuuluuu/SemEval-Triplet-data EMNLP 2020

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 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 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

yhcc/BARTABSA ACL 2021

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 13 Mar 2021

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 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 ACL 2021

Aspect-based sentiment analysis (ABSA) has received increasing attention recently.

Aspect Sentiment Triplet Extraction Using Reinforcement Learning

declare-lab/aste-rl 13 Aug 2021

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 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.