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.

[Q]: CFQ contains 239,357 English question-answer pairs that are answerable using the public Freebase data.
[A]: How big is new question answering dataset?

[Q]: Evaluating FastText, GloVe and word2vec, we show that compared to other word representation learning algorithms, the FastText performs best.
[A]: What do you use to calculate word/sub-word embeddings

[Q]: However, no prior work has explored the target of the offensive language, which is important in many scenarios, e.g., when studying hate speech with respect to a specific target.
[A]:
What are the differences between this dataset and pre-existing ones?