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 Input:
word embedding, input encoder, alignment, aggregation, and prediction 
 Question: what is the architecture of the baseline model?

Ex Output:
word embedding, input encoder, alignment, aggregation, and prediction.


Ex Input:
We focus here on the Europarl domain, for which we have ample data in several languages, and use as in-domain training data the Europarl corpus BIBREF5 for two translation directions: English INLINEFORM0 German and English INLINEFORM1 French.  
 Question: what language is the data in?

Ex Output:
English  German French


Ex Input:
As a first baseline we use Bag-of-Words, a well-known and robust text representations used in various domains BIBREF21 , combined with a standard shallow classifier, namely, a Support Vector Machine with linear kernel. We used LIBSVM implementation of SVM. 
 Question: Which shallow approaches did they experiment with?

Ex Output:

SVM