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: (2) Different from LEM and DPEMM, AEM uses a generator network to capture the event-related patterns and is able to mine events from different text sources (short and long). Moreover, unlike traditional inference procedure, such as Gibbs sampling used in LEM and DPEMM, AEM could extract the events more efficiently due to the CUDA acceleration;
Example Output: What alternative to Gibbs sampling is used?

Example Input: This study assumes that a robot does not have any vocabularies in advance but can recognize syllables or phonemes.
Example Output: Does their model start with any prior knowledge of words?

Example Input: Using our annotation software, we automatically extracted landmarks of 2000 images from the UOttawa database BIBREF14 had been annotated for image segmentation tasks. 
Example Output:
How big are datasets used in experiments?