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.

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?
fragments are interchangeable if they occur in at least one lexical environment that is exactly the same

For a word belonging to any one of the word-groups representing these concepts, the modified cost term favors an increase for the value of this word's embedding vector dimension corresponding to the concept that the particular word belongs to.  
 Question: Along which dimension do the semantically related words take larger values?
dimension corresponding to the concept that the particular word belongs to

We collected Japanese-Vietnamese parallel data from TED talks extracted from WIT3's corpus BIBREF15 .  
 Question: what japanese-vietnamese dataset do they use?

WIT3's corpus