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.

The input for both tasks consists of news articles in free-text format, collected from 36 propagandist and 12 non-propagandist news outlets and then annotated by professional annotators.  
 Question: What dataset was used?
 news articles in free-text format

To evaluate the usefulness of our corpus for SMT purposes, we used it to train an automatic translator with Moses BIBREF8 . 
 Question: What SMT models did they look at?
automatic translator with Moses

We experimented with four different classifiers, namely, support vector machine BIBREF18 , random forest, extra tree and naive bayes classifier BIBREF19 . Chi square feature selection algorithm is applied to reduces the size of our feature vector. For training our system classifier, we used Scikit-learn BIBREF19 . 
 Question: What type of system does the baseline classification use?

support vector machine BIBREF18 , random forest, extra tree and naive bayes classifier BIBREF19