instruction:
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.
question:
Suppose there are INLINEFORM0 mentions in documents on average, among these global models, NCEL not surprisingly has the lowest time complexity INLINEFORM1 since it only considers adjacent mentions, where INLINEFORM2 is the number of sub-GCN layers indicating the iterations until convergence. 
 Question: Do they only use adjacent entity mentions or use more than that in some cases (next to adjacent)?
answer:
NCEL considers only adjacent mentions.


question:
We only used models of dimension 300 and, for Word2Vec, Wang2Vec, and FastText, skip-gram architectured models. 
 Question: what word embedding techniques did they experiment with?
answer:
Word2Vec, Wang2Vec, and FastText


question:
We found that properties of the emerging lexicon related to the combinatoriality, namely the words length distribution, the frequency of use of the different forms and a measure for the combinatoriality itself, reflect both qualitatively and quantitatively the corresponding properties as measured in human languages, provided that the memory parameter $\tau $ is sufficiently high, that is that a sufficiently high effort is required in order to understand and learn brand new forms. 
 Question: What empirical data are the Blending Game predictions compared to?
answer:

words length distribution, the frequency of use of the different forms and a measure for the combinatoriality