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: In our experiments, we use as input the 2210 tokenized sentences of the Stanford Sentiment Treebank test set BIBREF2 , preprocessing them by lowercasing as was done in BIBREF8 .
Example Output: Which datasets are used for evaluation?

Example Input: In order to fully leverage gloss information, we propose GlossBERT to construct context-gloss pairs from all possible senses of the target word in WordNet, thus treating WSD task as a sentence-pair classification problem.
Example Output: Do they incoprorate WordNet into the model?

Example Input: Both the distributional hypothesis itself and Tugendhat's interpretation of Frege's work are examples of holistic approaches to meaning, where the meaning of the whole determines the meaning of parts.
Example Output:
How does Frege's holistic and functional approach to meaning relates to general distributional hypothesis?