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:
The De7 database used for this study was designed by Marc Schroeder as one of the first attempts of creating diphone databases for expressive speech synthesis BIBREF2. The database contains three voice qualities (modal, soft and loud) uttered by a German female speaker, with about 50 minutes of speech available for each voice quality. 
 Question: What large corpus is used for experiments?

Ex Output:
The De7 database


Ex Input:
Fenerbahçe We have decided to consider tweets about popular sports clubs as our domain for stance detection.  Hence we have determined our targets as Galatasaray (namely Target-1) and Fenerbahçe (namely, Target-2) which are two of the most popular football clubs in Turkey.  Then, we have annotated the stance information in the tweets for these targets as Favor or Against. For the purposes of the current study, we have not annotated any tweets with the Neither class. 
 Question: How were the tweets annotated?

Ex Output:
tweets are annotated with only Favor or Against for two targets - Galatasaray and Fenerbahçe


Ex Input:
Besides, we also use two of its adversarial sets, namely AddSent and AddOneSent BIBREF6 , to evaluate the robustness to noise of MRC models. The passages in the adversarial sets contain misleading sentences, which are aimed at distracting MRC models.  Specifically, we not only evaluate the performance of KAR on the development set and the test set, but also do this on the adversarial sets.  
 Question: How do the authors examine whether a model is robust to noise or not?

Ex Output:

By evaluating their model on adversarial sets containing misleading sentences