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AmQA: Amharic Question Answering Dataset

arXiv 2303.03290 ↗First posted 6 Mar 2023cs.CL cs.AI cs.IRcited by 1

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Abstract (arXiv)

Question Answering (QA) returns concise answers or answer lists from natural language text given a context document. Many resources go into curating QA datasets to advance robust models' development. There is a surge of QA datasets for languages like English, however, this is not true for Amharic. Amharic, the official language of Ethiopia, is the second most spoken Semitic language in the world. There is no published or publicly available Amharic QA dataset. Hence, to foster the research in Amharic QA, we present the first Amharic QA (AmQA) dataset. We crowdsourced 2628 question-answer pairs over 378 Wikipedia articles. Additionally, we run an XLMR Large-based baseline model to spark open-domain QA research interest. The best-performing baseline achieves an F-score of 69.58 and 71.74 in reader-retriever QA and reading comprehension settings respectively.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 16 of its 29 references that are in the map. First posted on arXiv 6 Mar 2023.

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16 of 29 references.

References · 16

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4 more
  1. 2021GermanQuAD and GermanDPR: Improving Non-English Question Answering and Passage Retrievalcited by 39
  2. 2021English Machine Reading Comprehension Datasets: A Surveycited by 26
  3. 2021Sentence Extraction-Based Machine Reading Comprehension for Vietnamesecited by 9
  4. 2021Contemporary Amharic Corpus: Automatically Morpho-Syntactically Tagged Amharic Corpuscited by 4

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