Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/9590
Title: Rule-based automatic question generation using semantic role labeling
Authors: Keklik, Onur
Tuğlular, Tuğkan
Tekir, Selma
Keklik, Onur
Tuğlular, Tuğkan
Tekir, Selma
Izmir Institute of Technology. Computer Engineering
Keywords: question generation
rule-based
semantic role labeling
METEOR
Issue Date: 2019
Publisher: Institute of Electronics, Information and Communication Engineers
Abstract: This paper proposes a new rule-based approach to automatic question generation. The proposed approach focuses on analysis of both syntactic and semantic structure of a sentence. Although the primary objective of the designed system is question generation from sentences, automatic evaluation results shows that, it also achieves great performance on reading comprehension datasets, which focus on question generation from paragraphs. Especially, with respect to METEOR metric, the designed system significantly outperforms all other systems in automatic evaluation. As for human evaluation, the designed system exhibits similar performance by generating the most natural (human-like) questions.
Description: Tuğlular, Tuğkan/0000-0001-6797-3913
WOS: 000473257700015
URI: https://doi.org/10.1587/transinf.2018EDP7199
https://hdl.handle.net/11147/9590
ISSN: 1745-1361
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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