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 task is set up to mimic (albeit, in an oversimplified manner) the input-output symbol alignments and local syntactic properties that models must learn in many natural language tasks, such as translation, tagging and summarization.
Example Output: Why does the proposed task a good proxy for the general-purpose sequence to sequence tasks?

Example Input: Manual verification of Twitter profiles: We verified each profile discovered manually by examining the profile picture, profile background image, recent tweets, and recent pictures posted by a user.
Example Output: How is gang membership verified?

Example Input: Table TABREF14 shows the effectiveness of our model (multi-task transformer) over the baseline transformer BIBREF8 .
Example Output:
what are the baselines?