Abstract A why question answering system is a tool designed to answer why-questions posed in natural language. Several papers have been published on the problem of answering why-questions. In particular, attempts have been made to analyze Arabic text and predict which passages are best candidates for the why-questions; employing different datasets with limited size and not publicly available. To overcome these limitations, this paper introduces the new publicly available dataset, DAWQAS: Dataset for Arabic Why Question Answering System. It consists of 3205 of why question-answer pairs that were first scraped from public Arabic websites, then texts were preprocessed and converted to feature vectors. Afterwards, why-answers were re-categorized based on their domains. Finally, the rhetorical relations’ probabilities based on discourse markers were computed for each sentence in the dataset. DAWQAS is a valuable resource for research and evaluation in language understanding. The new dataset is freely available at https://github.com/masun/DAWQAS .
[1]
Khaled Shaalan,et al.
A Review and Future Perspectives of Arabic Question Answering Systems
,
2016,
IEEE Transactions on Knowledge and Data Engineering.
[2]
Mohammad S. Khorsheed,et al.
Comparative evaluation of text classification techniques using a large diverse Arabic dataset
,
2013,
Language Resources and Evaluation.
[3]
Aqil M. Azmi,et al.
Lemaza : An Arabic why-question answering system*
,
2017,
Natural Language Engineering.
[4]
Saleh Alsaleem,et al.
Automated Arabic Text Categorization Using SVM and NB
,
2011,
Int. Arab. J. e Technol..
[5]
Kenneth Magel,et al.
QArabPro: A Rule Based Question Answering System for Reading Comprehension Tests in Arabic
,
2011
.
[6]
Fatima T. AL-Khawaldeh.
Answer Extraction for Why Arabic Questions Answering Systems: EWAQ
,
2019,
ArXiv.