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 Input:
The News Category Dataset BIBREF11 is a collection of headlines published by HuffPost BIBREF12 between 2012 and 2018, and was obtained online from Kaggle BIBREF13. The full dataset contains 200k news headlines with category labels, publication dates, and short text descriptions.

Ex Output:
What news dataset was used?


Ex Input:
The task is set up to mimic (albeit, in an oversimplified manner) the input-output symbol alignments and local syntactic properties that models must learn in many natural language tasks, such as translation, tagging and summarization.

Ex Output:
Why does the proposed task a good proxy for the general-purpose sequence to sequence tasks?


Ex Input:
The NLG model is a seq2seq model with attention as described in section SECREF2.

Ex Output:

Do they use attention?