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.

Q: We evaluate the generations with the ROUGE BIBREF29 and METEOR BIBREF30 metrics using the true sentences as targets. 
 Question: What metrics are used for evaluation?

A: ROUGE BIBREF29 and METEOR BIBREF30
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Q: Pre-trained English NER model We construct the English NER system following BIBREF7 . This system uses a bidirectional LSTM as a character-level language model to take context information for word embedding generation.  For pre-trained English NER system, we use the default NER model of Flair. 
 Question: Which pre-trained English NER model do they use?

A: Bidirectional LSTM based NER model of Flair
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Q: We have observed that the number of epochs is an important parameter and its increase leads to results that rank our two worst models almost equal, or even better than others. 
 Question: How does different parameter settings impact the performance and semantic capacity of resulting model?

A:
number of epochs is an important parameter and its increase leads to results that rank our two worst models almost equal, or even better than others
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