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: We compare the above model to a similar model, where rather than explicitly represent $K$ features as input, we have $K$ features in the form of a genre embedding, i.e. we learn a genre specific embedding for each of the gothic, scifi, and philosophy genres, as studied in BIBREF8 and BIBREF7.
Example Output: Is this style generator compared to some baseline?

Example Input: The crowdworkers were located in the US and hired on the BIBREF22 platform.
Example Output: Who are the crowdworkers?

Example Input: In the first scenario we equip the decoder with an additional morphology table including target-side affixes.
Example Output:
What type of morphological information is contained in the "morphology table"?