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]: As fig:fit shows, estimated test accuracy is highly correlated with actual test accuracy for various datasets, with worst-case values $\mu <1\%$ and $\sigma <5\%$ . Note that the number of free parameters is small ($||\le 6$) compared to the number of points (42–49 model-data configurations), demonstrating the appropriateness of the proposed function for modeling the complex error landscape. 
 Question: What is proof that proposed functional form approximates well generalization error in practice?
[EX A]: estimated test accuracy is highly correlated with actual test accuracy for various datasets appropriateness of the proposed function for modeling the complex error landscape

[EX Q]: Then we define the similarity between INLINEFORM7 and INLINEFORM8 by, DISPLAYFORM0 We note that the similarity metric defined above for sentences is equally applicable for n-gram retrieval. 
 Question: Which similarity measure do they use in their n-gram retrieval approach?
[EX A]: we define the similarity between INLINEFORM7 and INLINEFORM8 by, DISPLAYFORM0

[EX Q]: Because our conversion rules are interpretable, we identify shortcomings in both resources, using each as validation for the other. We were able to find specific instances of incorrectly applied UniMorph annotation, as well as specific instances of cross-lingual inconsistency in both resources. 
 Question: Do they look for inconsistencies between different languages' annotations in UniMorph?
[EX A]:
Yes