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 seq2seq model with global attention gives the best results with an average target BLEU score of 29.65 on the style transfer dataset, compared with an average target BLEU score of 26.97 using the seq2seq model with pointer networks. 
 Question: What is best BLEU score of language style transfer authors got?
seq2seq model with global attention gives the best results with an average target BLEU score of 29.65

SVMRank is a modification to SVM that assigns scores to each data point and allows the results to be ranked ( BIBREF26 ). We use SVMRank in the experiments below.  
 Question: what is the supervised model they developed?
SVMRank

 Result for BLEU score for our model and Google's Neural Machine Translation is compared in table TABREF19 
 Question: What is their baseline?

Google's Neural Machine Translation