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.

Input: Consider Input: The contributions of this work are:
Question: Do they look for inconsistencies between different UD treebanks?

Output: Yes

Input: Consider Input: Our dataset is annotated based on Chinese pathology reports provided by the Department of Gastrointestinal Surgery, Ruijin Hospital. It contains 17,833 sentences, 826,987 characters and 2,714 question-answer pairs.
Question: How big is QA-CTS task dataset?

Output: 17,833 sentences, 826,987 characters and 2,714 question-answer pairs

Input: Consider Input: 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.
Question: How they prove that multi-head self-attention is at least as powerful as convolution layer?
Output: constructively by selecting the parameters of the multi-head self-attention layer so that the latter acts like a convolutional layer