@inproceedings{desai-etal-2018-generating,
    title = "Generating Questions for Reading Comprehension using Coherence Relations",
    author = "Desai, Takshak  and
      Dakle, Parag  and
      Moldovan, Dan",
    editor = "Tseng, Yuen-Hsien  and
      Chen, Hsin-Hsi  and
      Ng, Vincent  and
      Komachi, Mamoru",
    booktitle = "Proceedings of the 5th Workshop on Natural Language Processing Techniques for Educational Applications",
    month = jul,
    year = "2018",
    address = "Melbourne, Australia",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/W18-3701",
    doi = "10.18653/v1/W18-3701",
    pages = "1--10",
    abstract = "In this paper, we have proposed a technique for generating complex reading comprehension questions from a discourse that are more useful than factual ones derived from assertions. Our system produces a set of general-level questions using coherence relations and a set of well-defined syntactic transformations on the input text. Generated questions evaluate comprehension abilities like a comprehensive analysis of the text and its structure, correct identification of the author{'}s intent, a thorough evaluation of stated arguments; and a deduction of the high-level semantic relations that hold between text spans. Experiments performed on the RST-DT corpus allow us to conclude that our system possesses a strong aptitude for generating intricate questions. These questions are capable of effectively assessing a student{'}s interpretation of the text.",
}