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.

Q: For training data, 3 million webpages from this corpus were processed with a CCG parser to produce logical forms BIBREF10 . We also used the test set created by Krishnamurthy and Mitchell, which contains 220 queries generated in the same fashion as the training data from a separate section of ClueWeb. However, as they did not release a development set with their data, we used this set as a development set. This final test set contains 307 queries.

A: How big is their dataset?
****
Q: We use the existing large-scale antonym and synonym pairs previously used by Nguyen:16. Originally, the data pairs were collected from WordNet BIBREF9 and Wordnik.

A: What dataset do they use to evaluate their method?
****
Q: In contrast, our models are trained only on the 76K questions in the training set.

A:
Do the authors also try the model on other datasets?
****