mlsanityData to 7 Oct 2026

A More Fine-Grained Aspect-Sentiment-Opinion Triplet Extraction Task

arXiv 2103.15255 ↗First posted 29 Mar 2021cs.CLcited by 6

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Abstract (arXiv)

Aspect Sentiment Triplet Extraction (ASTE) aims to extract aspect term, sentiment and opinion term triplets from sentences and tries to provide a complete solution for aspect-based sentiment analysis (ABSA). However, some triplets extracted by ASTE are confusing, since the sentiment in a triplet extracted by ASTE is the sentiment that the sentence expresses toward the aspect term rather than the sentiment of the aspect term and opinion term pair. In this paper, we introduce a more fine-grained Aspect-Sentiment-Opinion Triplet Extraction (ASOTE) Task. ASOTE also extracts aspect term, sentiment and opinion term triplets. However, the sentiment in a triplet extracted by ASOTE is the sentiment of the aspect term and opinion term pair. We build four datasets for ASOTE based on several popular ABSA benchmarks. We propose a Position-aware BERT-based Framework (PBF) to address this task. PBF first extracts aspect terms from sentences. For each extracted aspect term, PBF first generates aspect term-specific sentence representations considering both the meaning and the position of the aspect term, then extracts associated opinion terms and predicts the sentiments of the aspect term and opinion term pairs based on the sentence representations. Experimental results on the four datasets show the effectiveness of PBF.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 29 of its 71 references that are in the map. First posted on arXiv 29 Mar 2021.

Builds on

29 of 71 references.

References · 29

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17 more
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  2. 2019An Interactive Multi-Task Learning Network for End-to-End Aspect-Based Sentiment Analysiscited by 52
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  4. 2021Bidirectional Machine Reading Comprehension for Aspect Sentiment Triplet Extractioncited by 40
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  17. 2021Tell Me Why You Feel That Way: Processing Compositional Dependency for Tree-LSTM Aspect Sentiment Triplet Extraction (TASTE)cited by 2

Built on by

Cited by year

Citing papers per year: 2021: 1; 2022: 2; 2023: 0; 2024: 1; 2025: 2.

6 papers.

  1. 2022Survey of Aspect-based Sentiment Analysis Datasetscited by 3
  2. 2024ASTE Transformer Modelling Dependencies in Aspect-Sentiment Triplet Extractioncited by 2
  3. 2022A Better Choice: Entire-space Datasets for Aspect Sentiment Triplet Extractioncited by 1
  4. 2021Aspect-Sentiment-Multiple-Opinion Triplet Extractioncited by 0
  5. 2025Polish-ASTE: Aspect-Sentiment Triplet Extraction Datasets for Polishcited by 0
  6. 2025Multi-domain Multilingual Sentiment Analysis in Industry: Predicting Aspect-based Opinion Quadruplescited by 0