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 Q]: . Grammatically correct text is needed as the starting point for inserting artificial errors, and we used two different sources: 1) the corrected version of the same FCE training set on which the system is trained (450K tokens), and 2) example sentences extracted from the English Vocabulary Profile (270K tokens). 
 Question: Which languages are explored in this paper?
[EX A]: English 

[EX Q]: Following lebret2016neural, we used BLEU-4, NIST-4 and ROUGE-4 as the evaluation metrics. 
 Question: What metrics are used for evaluation?
[EX A]: BLEU-4 NIST-4 ROUGE-4

[EX Q]: The only remaining question is what makes two environments similar enough to infer the existence of a common category. There is, again, a large literature on this question (including the aforementioned language modeling, unsupervised parsing, and alignment work), but in the current work we will make use of a very simple criterion: fragments are interchangeable if they occur in at least one lexical environment that is exactly the same. 
 Question: How do they determine similar environments for fragments in their data augmentation scheme?
[EX A]:
fragments are interchangeable if they occur in at least one lexical environment that is exactly the same