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: Paraphrase Identification (PI) is the task of determining whether two sentences are paraphrase or not. We have implemented the cross-lingual variant of kernel functions for PI and RE tasks as described in section SECREF3 and measured the accuracy of models by testing them on the parallel data set.
Example Output: What classification task was used to evaluate the cross-lingual adaptation method described in this work?

Example Input: The best baseline model is NO-MOVE, reaching an accuracy of 30.3% on single sentences and 0.3 on complete paragraphs.
Example Output: How well did the baseline perform?

Example Input: In this paper, we propose the first large-scale dataset for QA over social media data.   Table TABREF3 gives an example from our TweetQA dataset. The dataset now includes 10,898 articles, 17,794 tweets, and 13,757 crowdsourced question-answer pairs
Example Output:
What is the size of this dataset?