In this task, you will be presented with a context from an academic paper and a question separated with a 
. You have to answer the question based on the context.

Q: The primary feed for the analysis collected INLINEFORM0 million tweets containing the keywords `breast' AND `cancer'.  
 Question: How were breast cancer related posts compiled from the Twitter streaming API?

A: By using  keywords `breast' AND `cancer' in tweet collecting process. 

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Q: 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. 
 Question: Why masking words in the decoder is helpful?

A: ecause 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.
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Q: We introduce a new crowdsourced dataset of 23,700 queries, including 22,500 in-scope queries covering 150 intents, which can be grouped into 10 general domains.  
 Question: Where does the data come from?

A:
crowsourcing platform
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