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: Most lexical resources for sentiment analysis are in English. To still be able to benefit from these sources, the lexicons in the AffectiveTweets package were translated to Spanish, using the machine translation platform Apertium BIBREF5  
 Question: How was the training data translated?

A: using the machine translation platform Apertium 
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Q: The annotator carried out all annotation. 
 Question: How many annotators tagged each tweet?

A: One
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Q: In order to evaluate the models trained on generated data, we manually annotated a named entities dataset comprising 53453 tokens and 2566 sentences selected from over 250 news texts from ilur.am. During annotation, we generally relied on categories and guidelines assembled by BBN Technologies for TREC 2002 question answering track. 
 Question: did they use a crowdsourcing platform for manual annotations?

A:
No
****