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 SnapCaptions dataset is composed of 10K user-generated image (snap) and textual caption pairs where named entities in captions are manually labeled by expert human annotators (entity types: PER, LOC, ORG, MISC). 
 Question: How large is their MNER SnapCaptions dataset?
10K user-generated image (snap) and textual caption pairs

As we only extracted references to other judicial decisions, we obtained 471,319 references from Supreme Court decisions, 167,237 references from Supreme Administrative Court decisions and 264,463 references from Constitutional Court Decisions. These are numbers of text spans identified as references prior the further processing described in Section SECREF3. 
 Question: How big is the dataset?
903019 references

During each evaluation, target terms are masked, predicted, and then compared to the masked (known) value. 
 Question: Are the Transformers masked?

Yes