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.

A recently published dataset called SCAN BIBREF2 (Simplified version of the CommAI Navigation tasks), tests compositional generalization in a sequence-to-sequence (seq2seq) setting by systematically holding out of the training set all inputs containing a basic primitive verb ("jump"), and testing on sequences containing that verb. 
 Question: How does the SCAN dataset evaluate compositional generalization?
it systematically holds out inputs in the training set containing basic primitive verb, "jump", and tests on sequences containing that verb.

The previously mentioned datasets are all in English 
 Question: For which languages most of the existing MRC datasets are created?
English

Car-speak is abstract language that pertains to a car's physical attribute(s). In this instance the physical attributes that the term “fast” pertains to could be the horsepower, or it could be the car's form factor (how the car looks). However, we do not know exactly which attributes the term “fast” refers to. 
 Question: How does car speak pertains to a car's physical attributes?

we do not know exactly