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]: We published a survey on Reddit asking Danish speaking users to suggest offensive, sexist, and racist terms for a lexicon. Language and user behaviour varies between platforms, so the goal is to capture platform-specific terms. This gave 113 offensive and hateful terms which were used to find offensive comments. The remainder of comments in the corpus were shuffled and a subset of this corpus was then used to fill the remainder of the final dataset. The resulting dataset contains 3600 user-generated comments, 800 from Ekstra Bladet on Facebook, 1400 from r/DANMAG and 1400 from r/Denmark.
[EX A]: How large was the dataset of Danish comments?

[EX Q]: The crowdworkers were located in the US and hired on the BIBREF22 platform.
[EX A]: Who are the crowdworkers?

[EX Q]: We apply the Generative Pre-trained Transformer (GPT) BIBREF2 as our pre-trained language model. 
[EX A]:
What pretrained LM is used?