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Therefore, we have confined ourselves to generate the questions from only simple sentences.
Feminist science is not defined by its content, but rather by the pragmatic interests that generate the questions it asks.
In order to generate the questions, the system first extracts a set of informative sentences from the given input corpus.
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Next, we have performed identification of answer-key to generate the question from the selected sentence.
Therefore, we have omitted Jaya Bhaduri in the sentence to generate the question and identified Jaya Bhaduri as the answer-key.
We further qualitatively analyzed each question to extract the knowledge type of the prior knowledge used to generate the question, knowledge type of the unfolded knowledge for any question, concept (topic/sub-topic) unfolded by any question.
Unlike these past attempts, the automatic question generation system used in this work utilises Web texts from the Internet as well as information from WordNet to generate the question components (Susanti et al. 2015).
To create a clinical trial, it is still important to generate the question, write a protocol and seek funding for the trial.
In the automatic question generation system used in this study, the website for the sources of the reading passage is decided before the system generates the questions.
Clearly, not all of this data is available, but generating the questions is the way to start getting at the facts.
Another possibility is that fewer students liked generating the questions, because that took more effort than simply answering questions.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com