Summary of Nsina: a News Corpus For Sinhala, by Hansi Hettiarachchi et al.
NSINA: A News Corpus for Sinhala
by Hansi Hettiarachchi, Damith Premasiri, Lasitha Uyangodage, Tharindu Ranasinghe
First submitted to arxiv on: 25 Mar 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The introduction of large language models (LLMs) has advanced natural language processing (NLP), but their effectiveness largely depends on pre-training resources. This study addresses challenges in low-resource languages like Sinhala by introducing NSINA, a comprehensive news corpus with over 500,000 articles from popular Sinhala news websites. Three NLP tasks are also introduced: news media identification, category prediction, and headline generation. The release of NSINA aims to provide valuable resources and benchmarks for improving NLP in the Sinhala language. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This study helps improve natural language processing (NLP) by making it easier to use large language models with languages like Sinhala. Right now, Sinhala faces big challenges because there isn’t enough training data or benchmark datasets available. The researchers created NSINA, a huge news corpus with over 500,000 articles from popular Sinhala news websites, and three NLP tasks: identifying media sources, categorizing news, and generating headlines. This can help improve NLP in the Sinhala language. |
Keywords
* Artificial intelligence * Natural language processing * Nlp
