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.

Example Input: 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)?
Example Output: NCEL considers only adjacent mentions.

Example Input: EmotionLines BIBREF6 is a dialogue dataset composed of two subsets, Friends and EmotionPush, according to the source of the dialogues. 
 Question: what datasets were used?
Example Output: Friends EmotionPush

Example Input: The two main data sets that we will use to evaluate our architecture are the 2014 i2b2 de-identification challenge data set BIBREF2 and the nursing notes corpus BIBREF3 . 
 Question: Which two datasets is the system tested on?
Example Output:
2014 i2b2 de-identification challenge data set BIBREF2 nursing notes corpus BIBREF3