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.

Q:  In terms of this, rather than starting from Twitter API Search, we look into the archived snapshots of two major news websites (CNN, NBC), and then extract the tweet blocks that are embedded in the news articles.

A: How do they determine if tweets have been used by journalists?
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Q: Each training sample is generated by three steps: align, mask and select, which we call as AMS method. Each sample in the dataset consists of a question and several candidate answers, which has the same form as the CommonsenseQA dataset.

A: How do they select answer candidates for their QA task?
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Q: Controls are calculated heuristically. All words found in the control word lists are then removed from the reference sentence. The remaining words, which represent the content, are used as input into the model, along with their POS tags and lemmas.

In this way we encourage models to construct a sentence using content and style independently.

A:
How they know what are content words?
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