Summary of Banglaquad: a Bengali Open-domain Question Answering Dataset, by Md Rashad Al Hasan Rony et al.
BanglaQuAD: A Bengali Open-domain Question Answering Dataset
by Md Rashad Al Hasan Rony, Sudipto Kumar Shaha, Rakib Al Hasan, Sumon Kanti Dey, Amzad Hossain Rafi, Amzad Hossain Rafi, Ashraf Hasan Sirajee, Jens Lehmann
First submitted to arxiv on: 14 Oct 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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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 proposed BanglaQuAD dataset is a novel attempt to create a question answering dataset for Bengali language, which is often considered a low-resource language in NLP. The dataset consists of 30,808 question-answer pairs constructed from Bengali Wikipedia articles by native speakers, addressing the limitations of existing approaches that rely on direct translation from English. The proposed annotation tool facilitates local construction of question-answering datasets, ensuring quality and relevance to the Bengali language and culture. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary BanglaQuAD is a new way to help computers understand questions and answers in Bengali, which is an important but underdeveloped task in natural language processing. Most current approaches translate English questions and answers into Bengali, but this can lead to mistakes and inaccurate sentence structures. To fix this, researchers created BanglaQuAD using Bengali Wikipedia articles and native speakers, resulting in a high-quality dataset that’s specific to the Bengali language and culture. |
Keywords
» Artificial intelligence » Natural language processing » Nlp » Question answering » Translation
