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 Input:
As a framework, we use the sentence classifier configuration of FLAIR BIBREF46 with a biLSTM encoder/classifier architecture fed by character and word level representations composed of a concatenation of fixed 300 dimensional GloVe embeddings BIBREF47, pre-trained contextualized FLAIR word embeddings, and pre-trained contextualized character embeddings from AllenNLP BIBREF48 with FLAIR's default hyperparameters. 
 Question: Are some models evaluated using this metric, what are the findings?

Ex Output:
Yes


Ex Input:
Using the distribution of the individual words in a category, we can compile distributions for the entire category, and therefore generate maps for these word categories.  
 Question: Do they build a model to automatically detect demographic, lingustic or psycological dimensons of people?

Ex Output:
No


Ex Input:
Our official scores (column Ens Test in Table TABREF19 ) have placed us second (EI-Reg, EI-Oc), fourth (V-Reg) and fifth (V-Oc) on the SemEval AIT-2018 leaderboard. 
 Question: What were the scores of their system?

Ex Output:

column Ens Test in Table TABREF19


