Abstract
We investigate the difficulty levels of questions in
reading comprehension datasets such as SQuAD,
and propose a new question generation setting,
named Difficulty-controllable Question Generation
(DQG). Taking as input a sentence in the reading comprehension paragraph and some of its text
fragments (i.e., answers) that we want to ask questions about, a DQG method needs to generate questions each of which has a given text fragment as
its answer, and meanwhile the generation is under
the control of specified difficulty labels—the output
questions should satisfy the specified difficulty as
much as possible. To solve this task, we propose an
end-to-end framework to generate questions of designated difficulty levels by exploring a few important intuitions. For evaluation, we prepared the first
dataset of reading comprehension questions with
difficulty labels. The results show that the question
generated by our framework not only have better
quality under the metrics like BLEU, but also comply with the specified difficulty labels