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]: Task: given a caption and a paired image (if used), the goal is to label every token in a caption in BIO scheme (B: beginning, I: inside, O: outside) BIBREF27 .
[EX A]: Can named entities in SnapCaptions be discontigious?

[EX Q]: The model consists of one layer of LSTM followed by three dense layers. The LSTM layer uses a dropout value of 0.2.
[EX A]: Do they use dropout?

[EX Q]: It includes a total 708 hours of French (Fr), German (De), Dutch (Nl), Russian (Ru), Spanish (Es), Italian (It), Turkish (Tr), Persian (Fa), Swedish (Sv), Mongolian (Mn) and Chinese (Zh) speeches, with French and German ones having the largest durations among existing public corpora.
[EX A]:
Which languages are part of the corpus?