Turkish Journal of Electrical Engineering and Computer Sciences
DOI
10.55730/1300-0632.3914
Abstract
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.
Keywords
Turkish, question answering, question generation, answer extraction, multitask, transformer
First Page
1931
Last Page
1940
Recommended Citation
AKYÖN, FATİH ÇAĞATAY; ÇAVUŞOĞLU, ALİ DEVRİM EKİN; CENGİZ, CEMİL; ALTINUÇ, SİNAN ONUR; and TEMİZEL, ALPTEKİN
(2022)
"Automated question generation and question answering from Turkish texts,"
Turkish Journal of Electrical Engineering and Computer Sciences: Vol. 30:
No.
5, Article 17.
https://doi.org/10.55730/1300-0632.3914
Available at:
https://journals.tubitak.gov.tr/elektrik/vol30/iss5/17
Included in
Computer Engineering Commons, Computer Sciences Commons, Electrical and Computer Engineering Commons