AmQA: Amharic Question Answering Dataset

Tilahun Abedissa, Ricardo Usbeck, Yaregal Assabie
3/6/2023
cs.CLcs.AIcs.IR

No official code found. Best implementation: semantic-systems/amharic-qa (15 stars, MIT, last commit 2024-05-27).

Abstract

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.

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Code Implementations(1)

MIT

AmQA - The first Amharic Open Domain Question Answering Dataset

157Jan 17, 20222 years agoMIT
amharicamharic-nlpqaquestion-answeringreading-comprehension

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Cite this paper

@article{abedissa2023amqa,
  title  = {AmQA: Amharic Question Answering Dataset},
  author = {Tilahun Abedissa and Ricardo Usbeck and Yaregal Assabie},
  year   = {2023},
  eprint = {2303.03290},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2303.03290v2}
}

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