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.

Ex Input:
To create training data for unanswerable question generation, we use (plausible) answer spans in paragraphs as pivots to align pairs of answerable questions and unanswerable questions. In this way, we obtain the data with which the models can learn to ask unanswerable questions by editing answerable ones with word exchanges, negations, etc.

Ex Output:
How do they ensure the generated questions are unanswerable?


Ex Input:
The attention function BIBREF11 is used to compute the similarity score between passages and questions as: INLINEFORM2

Ex Output:
Do they use attention?


Ex Input:
To identify the most suitable classifier for classifying the scalars associated with each text, we perform evaluations using the stochastic gradient descent, naive bayes, decision tree, and random forest classifiers.

Ex Output:

What was the baseline?