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New Sinhala dataset launched for Aspect-Based Sentiment Analysis

By PulseAugur Editorial · [2 sources] ·

Researchers have introduced SalAngaBhava, a new dataset designed for Aspect-Based Sentiment Analysis (ABSA) in Sinhala, a low-resource language spoken primarily in Sri Lanka. This dataset comprises Sinhala product reviews that have been manually annotated with specific aspect terms and their corresponding sentiments (positive, negative, or neutral). The creation of SalAngaBhava aims to address the scarcity of such resources for low-resource languages, enabling further research and development in Sinhala natural language processing and sentiment analysis. AI

IMPACT Enables new research and development in Sinhala natural language processing and sentiment analysis for low-resource languages.

RANK_REASON The cluster describes the release of a new academic dataset for a specific NLP task in a low-resource language, published on arXiv.

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New Sinhala dataset launched for Aspect-Based Sentiment Analysis

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COVERAGE [2]

  1. arXiv cs.CL TIER_1 English(EN) · Lakshani Galwatta, Nisansa de Silva, Sarangi Aththanayake, Adithya Galwatta ·

    SalAngaBhava: A Sinhala Market Dataset for Aspect-based Sentiment Analysis

    arXiv:2607.05259v1 Announce Type: new Abstract: 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…

  2. arXiv cs.CL TIER_1 English(EN) · Adithya Galwatta ·

    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…

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