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: The E2E NLG challenge dataset BIBREF21 is utilized in our experiments, which is a crowd-sourced dataset of 50k instances in the restaurant domain. Our models are trained on the official training set and verified on the official testing set. 
Example Output: What datasets did they use?

Example Input: The baseline classifier uses a linear Support Vector Machine BIBREF7 , which is suited for a high number of features. 
Example Output: What baseline is used?

Example Input: Outlier Detection. The Outlier Detection task BIBREF0 is to determine which word in a list INLINEFORM0 of INLINEFORM1 words is unrelated to the other INLINEFORM2 which were chosen to be related. For each INLINEFORM3 , one can compute its compactness score INLINEFORM4 , which is the compactness of INLINEFORM5 . Sentiment analysis. We also consider sentiment analysis as described by BIBREF31 .
Example Output:
Do they test their word embeddings on downstream tasks?