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]: Table TABREF46 shows that our Open model achieves more than 3 points of f1-score than the state-of-the-art result, and RelAwe with DepPath&RelPath achieves the best in both Closed and Open settings. 
 Question: How big is improvement over the old  state-of-the-art performance on CoNLL-2009 dataset?
[A]: our Open model achieves more than 3 points of f1-score than the state-of-the-art result


[Q]: In this work, we develop a technique to rapidly transfer an existing pre-trained model from English to other languages in an energy efficient way BIBREF8.  
 Question: How much training data from the non-English language is used by the system?
[A]: No data. Pretrained model is used.


[Q]: For testing, we also applied the TongueNet on the UBC database BIBREF14 without any training to see the generalization ability of the model. 
 Question: What previously annotated databases are available?
[A]:
the UBC database BIBREF14