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.

[Q]: 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?
[A]: tweets are annotated with only Favor or Against for two targets - Galatasaray and Fenerbahçe


[Q]: We evaluated our models on 3 different datasets:

CSAT dataset for CSAT prediction, consisting of spoken transcripts (automatic via ASR).

20 newsgroups for topic identification task, consisting of written text;

Fisher Phase 1 corpus for topic identification task, consisting of spoken transcripts (manual); 
 Question: What datasets did they use for evaluation?
[A]: CSAT dataset 20 newsgroups Fisher Phase 1 corpus


[Q]: For the datasets, we use Karpathy and Fei-Fei's split for MS-COCO dataset BIBREF10 . 
 Question: What dataset/corpus is this work evaluated over?
[A]:
Karpathy and Fei-Fei's split for MS-COCO dataset BIBREF10