Automated question generation and question answering from Turkish texts

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Date

2022-1-01

Author

Akyön, Fatih Çağatay
Çavuşoğlu, Devrim
Cengiz, Cemil
Altinuç, Sinan Onur
Temizel, Alptekin

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All rights reserved.While exam-style questions are a fundamental educational tool serving a variety of purposes, manual construction of questions is a complex process that requires training, experience and resources. Automatic question generation (QG) techniques can be utilized to satisfy the need for a continuous supply of new questions by streamlining their generation. However, compared to automatic question answering (QA), QG is a more challenging task. In this work, we fine-tune a multilingual T5 (mT5) transformer in a multitask setting for QA, QG and answer extraction tasks using Turkish QA datasets. To the best of our knowledge, this is the first academic work that performs automated text-to-text question generation from Turkish texts. Experimental evaluations show that the proposed multitask setting achieves state-of-the-art Turkish question answering and question generation performance on TQuADv1, TQuADv2 datasets and XQuAD Turkish split. The source code and the pretrained models are available at https://github.com/obss/turkish-question-generation.

Subject Keywords

answer extraction, multitask, question answering, question generation, transformer, Turkish

URI

https://hdl.handle.net/11511/101785

Journal

Turkish Journal of Electrical Engineering and Computer Sciences

DOI

https://doi.org/10.55730/1300-0632.3914

Collections

Graduate School of Informatics, Article

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Citation Formats

F. Ç. Akyön, D. Çavuşoğlu, C. Cengiz, S. O. Altinuç, and A. Temizel, “Automated question generation and question answering from Turkish texts,” Turkish Journal of Electrical Engineering and Computer Sciences, vol. 30, no. 5, pp. 1931–1940, 2022, Accessed: 00, 2023. [Online]. Available: https://hdl.handle.net/11511/101785.