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.

Input: Consider Input: We evaluate with all commonly-used metrics in question generation BIBREF13: BLEU-1 (B1), BLEU-2 (B2), BLEU-3 (B3), BLEU-4 (B4) BIBREF17, METEOR (MET) BIBREF18 and ROUGE-L (R-L) BIBREF19. We use the evaluation script released by Chen2015MicrosoftCC.

Output: What metrics do they use?


Input: Consider Input: Trinomials are likely to appear in exactly one order, and when they appear in more than one order the last word is almost always the same across all instances. 

Output: Are there any new finding in analasys of trinomials that was not present binomials?


Input: Consider Input: To show the effectiveness of our approach, we show results on the SICK dataset BIBREF1, a common benchmark for logic-based NLI, and find MonaLog to be competitive with more complicated logic-based approaches (many of which require full semantic parsing and more complex logical machinery).


Output: Do they beat current state-of-the-art on SICK?