In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.

[EX Q]: We collect three years of online news articles from June 2016 to June 2019.
Question: What unlabeled corpus did they use?
[EX A]: three years of online news articles from June 2016 to June 2019

[EX Q]: The results indicate that most performance gains come from words embeddings, style, and morality features. Other features (emotion and sentiment) show lower importance: nevertheless, they still improve the overall system performance (on average 0.35% Macro-F$_1$ improvement)
Question: Based on this paper, what is the more predictive set of features to detect fake news?
[EX A]: words embeddings, style, and morality features

[EX Q]: machine comprehension Nelufar
Question: What MC abbreviate for?
[EX A]:
machine comprehension