mlsanityData to 14 Oct 2026

OATS: Opinion Aspect Target Sentiment Quadruple Extraction Dataset for Aspect-Based Sentiment Analysis

arXiv 2309.13297 ↗First posted 23 Sep 2023cs.CLcited by 0

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Abstract (arXiv)

Aspect-based sentiment analysis (ABSA) delves into understanding sentiments specific to distinct elements within a user-generated review. It aims to analyze user-generated reviews to determine a) the target entity being reviewed, b) the high-level aspect to which it belongs, c) the sentiment words used to express the opinion, and d) the sentiment expressed toward the targets and the aspects. While various benchmark datasets have fostered advancements in ABSA, they often come with domain limitations and data granularity challenges. Addressing these, we introduce the OATS dataset, which encompasses three fresh domains and consists of 27,470 sentence-level quadruples and 17,092 review-level tuples. Our initiative seeks to bridge specific observed gaps: the recurrent focus on familiar domains like restaurants and laptops, limited data for intricate quadruple extraction tasks, and an occasional oversight of the synergy between sentence and review-level sentiments. Moreover, to elucidate OATS's potential and shed light on various ABSA subtasks that OATS can solve, we conducted experiments, establishing initial baselines. We hope the OATS dataset augments current resources, paving the way for an encompassing exploration of ABSA (https://github.com/RiTUAL-UH/OATS-ABSA).

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References · 18

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
  3. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
  4. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
  5. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,893
  6. 2019Knowing What, How and Why: A Near Complete Solution for Aspect-based Sentiment Analysiscited by 123
  7. 2019Utilizing BERT for Aspect-Based Sentiment Analysis via Constructing Auxiliary Sentencecited by 122
  8. 2021Aspect Sentiment Quad Prediction as Paraphrase Generationcited by 100
  9. 2021A Joint Training Dual-MRC Framework for Aspect Based Sentiment Analysiscited by 62
  10. 2021Learning Span-Level Interactions for Aspect Sentiment Triplet Extractioncited by 60
  11. 2021Bidirectional Machine Reading Comprehension for Aspect Sentiment Triplet Extractioncited by 40
  12. 2022Improving Aspect Sentiment Quad Prediction via Template-Order Data Augmentationcited by 30
6 more
  1. 2020Context-Guided BERT for Targeted Aspect-Based Sentiment Analysiscited by 18
  2. 2022Generative Aspect-Based Sentiment Analysis with Contrastive Learning and Expressive Structurecited by 13
  3. 2021Exploring Conditional Text Generation for Aspect-Based Sentiment Analysiscited by 5
  4. 2023MEMD-ABSA: A Multi-Element Multi-Domain Dataset for Aspect-Based Sentiment Analysiscited by 4
  5. 2023Domain-Expanded ASTE: Rethinking Generalization in Aspect Sentiment Triplet Extractioncited by 3
  6. 2023Measuring Your ASTE Models in The Wild: A Diversified Multi-domain Dataset For Aspect Sentiment Triplet Extractioncited by 2

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