BanglaRQA: A Benchmark Dataset for Under-resourced Bangla Language Reading Comprehension-based Question Answering with Diverse Question-Answer Types (2022.findings-emnlp)
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Syed Mohammed Sartaj Ekram, Adham Arik Rahman, Md. Sajid Altaf, Mohammed Saidul Islam, Mehrab Mustafy Rahman, Md Mezbaur Rahman, Md Azam Hossain, Abu Raihan Mostofa Kamal
| Challenge: | a lack of diverse and comprehensive question-answering datasets exists in under-resourced languages like Bangla. |
| Approach: | They propose a reading comprehension-based Bangla question-answering dataset . the dataset includes answerable and unanswerable questions covering four categories of questions . |
| Outcome: | The proposed dataset shows that it performs well as a training resource in high-resource languages. |
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