In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.

Example Input: Following previous work BIBREF13, BIBREF12, BIBREF10, BIBREF17, BIBREF9, BIBREF7, we choose SemCor3.0 as training corpus, which is the largest corpus manually annotated with WordNet sense for WSD.
Example Output: Is SemCor3.0 reflective of English language data in general?

Example Input: But we also showed that in some cases the saliency maps seem to not capture the important input features.  The second observation we can make is that the saliency map doesn't seem to highlight the right things in the input for the summary it generates
Example Output: Is the explanation from saliency map correct?

Example Input: We develop a null model to determine how much variation in binomial orderings we might expect across communities and across time, if binomial orderings were randomly ordered according to global asymmetry values. 
Example Output:
What new model is proposed for binomial lists?