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.

[EX Q]: We consider 5 major profile attributes for further analysis. These attributes are username, display name, profile image, location and description respectively.
[EX A]: What profile metadata is used for this analysis?

[EX Q]: We compare our model with two sets of baselines:

MemN2N BIBREF12 is an end-to-end trainable version of memory networks BIBREF9 . Attentive and Impatient Readers BIBREF6 use bidirectional LSTMs to encode question and evidence, and do classification over a large vocabulary based on these two encodings.
[EX A]: What are the baselines?

[EX Q]: Active learning sharply increases the performance of iteratively trained machine learning models by selectively determining which unlabeled samples should be annotated. 
[EX A]:
What is active learning?