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:
We also run a manual evaluation which shows for the En-It task a slight quality degradation in exchange of a statistically significant reduction in the average length ratio, from 1.05 to 1.01. 
 Question: Do they conduct any human evaluation?

Ex Output:
Yes


Ex Input:
Our Pointer-Gen+ARL-SEN model achieves the best performance of 60.8%. This is an absolute improvement of 18.2% over the Pointer-Gen baseline. 
 Question: What is this method improvement over the best performing state-of-the-art?

Ex Output:
absolute improvement of 18.2% over the Pointer-Gen baseline


Ex Input:
We train a single layer LSTM with a 150-dimensional hidden state for hate / not hate classification. The input dimensionality is set to 100 and GloVe BIBREF26 embeddings are used as word input representations. 
 Question: What unimodal detection models were used?

Ex Output:

 single layer LSTM with a 150-dimensional hidden state for hate / not hate classification