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.
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Question: . We address various different challenges: dialogue act annotated data is not available for customer service on Twitter, the task of dialogue act annotation is subjective, existing taxonomies do not capture the fine-grained information we believe is valuable to our task, and tweets, although concise in nature, often consist of overlapping dialogue acts to characterize their full intent.

Answer: Which dialogue acts are more suited to the twitter domain?

Question: The theorem is proven constructively by selecting the parameters of the multi-head self-attention layer so that the latter acts like a convolutional layer.

Answer: How they prove that multi-head self-attention is at least as powerful as convolution layer?

Question: We obtained 1260 unique utterances having commands to AMIE from our in-cabin data-set. We expanded this data-set via Amazon Mechanical Turk and ended up with 3347 utterances having intents. The annotations for intents and slots are obtained on the transcribed utterances by majority voting of 3 annotators.

Answer:
What is the size of their collected dataset?