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 MCD splits achieve a significantly higher compound divergence at a similar atom divergence when compared to the other experiments.
Example Output: What are results of comparison between novel method to other approaches for creating compositional generalization benchmarks?

Example Input: We adopt a DNN-based acoustic model BIBREF0 with 11 hidden layers and the alignment used to train the model is derived from a HMM-GMM model trained with SAT criterion.
Example Output: What are the deep learning architectures used in the task?

Example Input: We used Amazon Mechanical Turk (AMT) for our annotations, restricting the task to workers in five English-speaking countries (USA, UK, Canada, New Zealand, and Australia), more than 1000 finished HITs and at least a 95% acceptance rate.
Example Output:
What crowdsourcing platform did they use?