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:
We evaluate the TN topic model quantitatively with standard topic model measures such as test-set perplexity, likelihood convergence and clustering measures. Qualitatively, we evaluate the model by visualizing the topic summaries, authors' topic distributions and by performing an automatic labeling task.

Ex Output:
What are the measures of "performance" used in this paper?


Ex Input:
CFQ contains 239,357 English question-answer pairs that are answerable using the public Freebase data.

Ex Output:
How big is new question answering dataset?


Ex Input:
We use micro-averaged F1 score on all labels as the evaluation metric.

Ex Output:

What metris are used for evaluation?