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.

Example Input:  Models include both neural nets (e.g. RNNs, CNNs) and standard machine learning tools (e.g. Naive Bayes with Laplace Smoothing, k-clustering, SVM with linear kernel).  
 Question: Which machine learning models are used?
Example Output: RNNs CNNs Naive Bayes with Laplace Smoothing k-clustering SVM with linear kernel

Example Input: Which events authors choose to include in their history, which they leave out, and the way the events chosen relate to the march are crucial factors in conveying bias. 
 Question: What factors contribute to interpretive biases according to this research?
Example Output: Which events authors choose to include in their history, which they leave out, and the way the events chosen relate to the march

Example Input: Most importantly, all three languages have error-corrected corpora for testing purposes, though work on their automatic grammatical error correction is extremely limited (see Section SECREF3 ). 
 Question: Do they introduce errors in the data or does the data already contain them?
Example Output:
 all three languages have error-corrected corpora for testing purposes

