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: The incomplete dataset used for training is composed of lower-cased incomplete data obtained by manipulating the original corpora.
Example Output: Do they test their approach on a dataset without incomplete data?

Example Input: In this study, we investigate the performance of our proposed models on WSJ BIBREF5 . 
Example Output: Which dataset do they use?

Example Input: The log-likelihood of a Plackett-Luce model is not a strict upper bound of the BLEU score, however, it correlates with BLEU well in the case of rich features. The concept of “rich” is actually qualitative, and obscure to define in different applications. We empirically provide a formula to measure the richness in the scenario of machine translation. The greater, the richer. In practice, we find a rough threshold of r is 5
Example Output:
How they measure robustness in experiments?