TASK DEFINITION: In this task, you will be presented with a context from an academic paper and a question based on the context. You have to classify the questions into "Extractive", "Abstractive", or "Yes-no" questions. Extractive questions can be answered by concatenating extracts taken from a context into a summary while answering abstractive questions involves paraphrasing the context using novel sentences. Yes-no question is a question whose expected answer is one of two choices, one that affirms the question and one that denies the question. Typically, the choices are either yes or no.
PROBLEM: What similarities and/or differences do these topics have with non-violent, non-Islamic religious material addressed specifically to women? As these questions suggest, to understand what, if anything, makes extremist appeals distinctive, we need a point of comparison in terms of the outreach efforts to women from a mainstream, non-violent religious group. For this purpose, we rely on an online Catholic women's forum. Comparison between Catholic material and the content of ISIS' online magazines allows for novel insight into the distinctiveness of extremist rhetoric when targeted towards the female population. To accomplish this task, we employ topic modeling and an unsupervised emotion detection method. 
 Question: How are similarities and differences between the texts from violent and non-violent religious groups analyzed?

SOLUTION: Abstractive

PROBLEM: The question generation model provides each candidate answer with a score by measuring semantic relevance between the question and the generated question based on the semantics of the candidate answer.  
 Question: Where is a question generation model used?

SOLUTION: Extractive

PROBLEM: Performing the Welch's t-test, both changes after weGAN training are statistically significant at a INLINEFORM0 significance level.  
 Question: Do they evaluate grammaticality of generated text?

SOLUTION:
Yes-no