TASK DEFINITION: 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.
PROBLEM: To simplify the task, we set up a binary classification: candidates who have been liked or shortlisted are considered part of the hirable class and others part of the not hirable class.

SOLUTION: How is "hirability" defined?

PROBLEM: 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.

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

PROBLEM: We start by crawling the content of a few notable debating websites: idebate.com, debatewise.org, procon.org.

SOLUTION:
What debate websites did they look at?