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: Here I would use Informap algorithm BIBREF12. To make a comparison to this method, I am using CCM and SCA for distance measurement in this experiment, too. UPGMA algorithm would be used accordingly in these two cases.
Example Output: Is the proposed method compared to previous methods?

Example Input: The dataset (composed of 2.6 GB of raw text) includes $421\,829\,960$ words divided into $17\,305\,401$ sentences.
Example Output: How big is dataset used to train Word2Vec for the Italian Language?

Example Input: Results in Table TABREF64 show the correctness rates of these scenarios. User correctness score is superior to that of the baseline parser by 7.5% (from 37.1% to 44.6%), while the hybrid approach outscores both with a correctness of 48.7% improving the baseline by 11.6%.
Example Output:
Which query explanation method was preffered by the users in terms of correctness?