Quinductor: a multilingual data-driven method for generating reading-comprehension questions using Universal Dependencies

• URL: http://arxiv.org/abs/2103.10121v3
• Date: Fri, 12 May 2023 18:57:33 GMT
• Title: Quinductor: a multilingual data-driven method for generating reading-comprehension questions using Universal Dependencies
• Authors: Dmytro Kalpakchi and Johan Boye
• Abstract summary: We propose a multilingual data-driven method for generating reading comprehension questions using dependency trees. Our method provides a strong, mostly deterministic, and inexpensive-to-train baseline for less-resourced languages.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: We propose a multilingual data-driven method for generating reading comprehension questions using dependency trees. Our method provides a strong, mostly deterministic, and inexpensive-to-train baseline for less-resourced languages. While a language-specific corpus is still required, its size is nowhere near those required by modern neural question generation (QG) architectures. Our method surpasses QG baselines previously reported in the literature and shows a good performance in terms of human evaluation.

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