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 two main data sets that we will use to evaluate our architecture are the 2014 i2b2 de-identification challenge data set BIBREF2 and the nursing notes corpus BIBREF3 .
Example Output: Which two datasets is the system tested on?

Example Input: For the datasets, we use Karpathy and Fei-Fei's split for MS-COCO dataset BIBREF10 .
Example Output: What dataset/corpus is this work evaluated over?

Example Input: For generating a poem from images we use an existing actor-critic architecture BIBREF1. For Shakespearizing modern English texts, we experimented with various types of sequence to sequence models. We use a sequence-to-sequence model which consists of a single layer unidrectional LSTM encoder and a single layer LSTM decoder and pre-trained retrofitted word embeddings shared between source and target sentences. Since a pair of corresponding Shakespeare and modern English sentences have significant vocabulary overlap we extend the sequence-to-sequence model mentioned above using pointer networks BIBREF11 that provide location based attention and have been used to enable copying of tokens directly from the input.
Example Output:
What models are used for painting embedding and what for language style transfer?