SalAngaBhava: A Sinhala Market Dataset for Aspect-based Sentiment Analysis
Sentiment analysis has been a primary domain under Natural Language Processing (NLP) from its inception as it plays a vital role in both real-world and research applications. In high-resource languages, this has been extended a step further, and instead of predicting sentiment at the sentence level, models have been developed to detect more fine-grained sentiments at aspect level. However, in order to conduct this fine-grained Aspect-based Sentiment Analysis (ABSA), datasets annotated with aspects and sentiments toward the said aspects is required. Such datasets are lacking for low-resources languages among which, we can count Sinhala, an Indo-Aryan languages used primarily in Sri Lanka. ...
| Authors | Lakshani Galwatta, Nisansa de Silva, Sarangi Aththanayake et al. |
|---|---|
| Primary category | cs.CL |
| Published | 6 July 2026 |
| Last updated at source | 6 July 2026 |
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