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:
We focus primarily on the smaller data set of 645 hand-labeled articles provided to task participants, both for training and for validation. We pre-trained BERT-base on the 600,000 articles without labels by using the same Cloze task BIBREF5 that BERT had originally used for pre-training.

Ex Output:
How long is the dataset?

Ex Input:
This paper explores the potential of predicting a user's industry the aggregate of enterprises in a particular field by identifying industry indicative text in social media.

Ex Output:
What do they mean by a person's industry?

Ex Input:
They annotated 7.8K verbs, reporting an average of 2.4 QA pairs per predicate. Even though multiple annotators were shown to produce greater coverage, their released dataset was produced using only a single annotator per verb.

Ex Output:
How was coverage measured?