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: 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?
Example Output: automatic translator with Moses

Example Input: An acoustic word embedding is a function that takes as input a speech segment corresponding to a word, INLINEFORM0 , where each INLINEFORM1 is a vector of frame-level acoustic features, and outputs a fixed-dimensional vector representing the segment, INLINEFORM2 . 
 Question: How do they represent input features of their model to train embeddings?
Example Output: a vector of frame-level acoustic features

Example Input: Since we were also interested in whether argumentation differs across registers, we included four different registers — namely (1) user comments to newswire articles or to blog posts, (2) posts in discussion forums (forum posts), (3) blog posts, and (4) newswire articles.  
 Question: How is the data in the new corpus come sourced?
Example Output:
user comments to newswire articles or to blog posts forum posts blog posts newswire articles