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:
 For a fair comparison with previous work, we train the baseline MT system on the data released by BIBREF11.  
 Question: what was the baseline?

Ex Output:
 MT system on the data released by BIBREF11


Ex Input:
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?

Ex Output:
seq2seq model with global attention gives the best results with an average target BLEU score of 29.65


Ex Input:
To further demonstrate the effectiveness of the additional task-specific BiRNN layers in our architecture, we conducted an ablation study using the CoNLL04 dataset. We trained and evaluated in the same manner described above, using the same hyperparameters, with the following exceptions:

We used either (i) zero NER-specific BiRNN layers, (ii) zero RE-specific BiRNN layers, or (iii) zero task-specific BiRNN layers of any kind.

We increased the number of shared BiRNN layers to keep the total number of model parameters consistent with the number of parameters in the baseline model.

We average the results for each set of hyperparameter across three trials with random weight initializations. 
 Question: What were the variables in the ablation study?

Ex Output:

(i) zero NER-specific BiRNN layers, (ii) zero RE-specific BiRNN layers, or (iii) zero task-specific BiRNN layers of any kind