ACAT: A Collaborative Platform for Efficient Aspect-Based Sentiment Dataset Annotation
Aspect-Based Sentiment Analysis (ABSA) requires high-quality datasets to train reliable models. However, existing annotation tools treat output as flat files, leaving researchers to manually consolidate multi-annotator data, reconstruct relational structures, and compute reliability metrics through custom scripts. This paper introduces ACAT (Aspect-based sentiment analysis Collaborative Annotation Tool), a web-based platform natively supporting four ABSA workflows: (1) Aspect-Category Sentiment Analysis, (2) Clause-Level Segmentation, (3) Aspect-Term Sentiment Analysis with character-level position tracking, and (4) Aspect Sentiment Triplet Extraction with dual span offset preservation. I...
| Authors | Ana-Maria Luisa Mocanu, Ciprian-Octavian Truica, Elena-Simona Apostol |
|---|---|
| Primary category | cs.CL |
| Published | 2 June 2026 |
| Last updated at source | 2 June 2026 |
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