mlsanityData to 14 Oct 2026

AnnoABSA: A Web-Based Annotation Tool for Aspect-Based Sentiment Analysis with Retrieval-Augmented Suggestions

arXiv 2603.01773 ↗First posted 2 Mar 2026cs.CLcited by 0

On the map: Retrieval-augmented generation → RAG pipeline design and evaluation

Abstract (arXiv)

We introduce AnnoABSA, the first web-based annotation tool to support the full spectrum of Aspect-Based Sentiment Analysis (ABSA) tasks. The tool is highly customizable, enabling flexible configuration of sentiment elements and task-specific requirements. Alongside manual annotation, AnnoABSA provides optional Large Language Model (LLM)-based retrieval-augmented generation (RAG) suggestions that offer context-aware assistance in a human-in-the-loop approach, keeping the human annotator in control. To improve prediction quality over time, the system retrieves the ten most similar examples that are already annotated and adds them as few-shot examples in the prompt, ensuring that suggestions become increasingly accurate as the annotation process progresses. Released as open-source software under the MIT License, AnnoABSA is freely accessible and easily extendable for research and practical applications.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in RAG pipeline design and evaluation, one of 15 directions in Retrieval-augmented generation. Builds on 13 of its 35 references that are in the map. First posted on arXiv 2 Mar 2026.

Builds on

13 of 35 references.

References · 13

  1. 2025Gemma 3 Technical Reportcited by 1,824
  2. 2023Sentiment Analysis in the Era of Large Language Models: A Reality Checkcited by 268
  3. 2021Aspect Sentiment Quad Prediction as Paraphrase Generationcited by 100
  4. 2023MvP: Multi-view Prompting Improves Aspect Sentiment Tuple Predictioncited by 50
  5. 2024MEGAnno+: A Human-LLM Collaborative Annotation Systemcited by 47
  6. 2024AFaCTA: Assisting the Annotation of Factual Claim Detection with Reliable LLM Annotatorscited by 28
  7. 2023A Zero-shot and Few-shot Study of Instruction-Finetuned Large Language Models Applied to Clinical and Biomedical Taskscited by 25
  8. 2025Just Put a Human in the Loop? Investigating LLM-Assisted Annotation for Subjective Taskscited by 21
  9. 2023Zero- and Few-Shot Prompting with LLMs: A Comparative Study with Fine-tuned Models for Bangla Sentiment Analysiscited by 20
  10. 2025Do we still need Human Annotators? Prompting Large Language Models for Aspect Sentiment Quad Predictioncited by 9
  11. 2023Is ChatGPT a Biomedical Expert? -- Exploring the Zero-Shot Performance of Current GPT Models in Biomedical Taskscited by 5
  12. 2025Hybrid Annotation for Propaganda Detection: Integrating LLM Pre-Annotations with Human Intelligencecited by 4
1 more
  1. 2025VisioFirm: Cross-Platform AI-assisted Annotation Tool for Computer Visioncited by 2

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  1. 2026Large-Scale Aspect-Based Sentiment Analysis with Reasoning-Infused LLMs
  2. 2026DanceHA: A Multi-Agent Framework for Document-Level Aspect-Based Sentiment Analysis
  3. 2025From Annotation to Adaptation: Metrics, Synthetic Data, and Aspect Extraction for Aspect-Based Sentiment Analysis with Large Language Models
  4. 2021Unified Instance and Knowledge Alignment Pretraining for Aspect-based Sentiment Analysis
  5. 2023On the Robustness of Aspect-based Sentiment Analysis: Rethinking Model, Data, and Training
  6. 2025Are You Sure You're Positive? Consolidating Chain-of-Thought Agents with Uncertainty Quantification for Aspect-Category Sentiment Analysis
  7. 2026Aspect-Based Sentiment Analysis for Future Tourism Experiences: A BERT-MoE Framework for Persian User Reviews
  8. 2025Balanced Training Data Augmentation for Aspect-Based Sentiment Analysis