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.

为了促进阿姆哈拉语 QA ​​(AmQA) 研究，我们提供了第一个阿姆哈拉语 QA ​​(AmQA) 资料集。我们通过众包收集了 2628 个问题 - 答案对，并运行了一个基于 XLMR Large 的基线模型来激发开放域 QA 研究兴趣。最佳性能基线在阅读器 - 检索 QA 和阅读理解设置中分别达到了 69.58 和 71.74 的 F-score。