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:
Compared with 2015, our QA-SRL gold yielded 1593 annotations, with 989 core and 604 adjuncts, while theirs yielded 1315 annotations, 979 core and 336 adjuncts.  
 Question: How much more coverage is in the new dataset?

Ex Output:
278 more annotations


Ex Input:
Results show that the CJFA encoder obtains significantly better phone classification accuracy than the VAE baseline and also than the CJFS encoder. These results are replicated for speaker recognition tasks. 
 Question: Which approach out of two proposed in the paper performed better in experiments?

Ex Output:
CJFA encoder 


Ex Input:
We adapted BERTNLU from ConvLab-2.  We implemented a rule-based model (RuleDST) and adapted TRADE (Transferable Dialogue State Generator) BIBREF19 in this experiment.  We adapted a vanilla policy trained in a supervised fashion from ConvLab-2 (SL policy).  
 Question: What are the benchmark models?

Ex Output:

BERTNLU from ConvLab-2 a rule-based model (RuleDST)  TRADE (Transferable Dialogue State Generator)  a vanilla policy trained in a supervised fashion from ConvLab-2 (SL policy)