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.

Example Input: Finally, the decoder task, which predicts the target sequence probability at time INLINEFORM3 based on previous output and context information INLINEFORM4 , can be formulated as: DISPLAYFORM0
Example Output: How does their decoder generate text?

Example Input: We design the word-level refine decoder because this process is similar to the cloze task in BERT's pre-train process, therefore by using the ability of the contextual language model the decoder can generate more fluent and natural sequences.
Example Output: Why masking words in the decoder is helpful?

Example Input: A data collection process involving location neutral keywords used by gang members, with an expanded search of their retweet, friends and follower networks, led to identifying 400 authentic gang member profiles on Twitter. Our study discovered that the text in their tweets and profile descriptions, their emoji use, their profile images, and music interests embodied by links to YouTube music videos, can help a classifier distinguish between gang and non-gang member profiles.
Example Output:
How is the ground truth of gang membership established in this dataset?