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.

Input: Consider Input: 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?

Output: CSAT dataset 20 newsgroups Fisher Phase 1 corpus


Input: Consider Input: We collect data by using the Twitter API for saved data, available for public use. For our experiments we collect 3200 tweets filtered by keywords like “fire”, “earthquake”, “theft”, “robbery”, “drunk driving”, “drunk driving accident” etc.  
 Question: Do the tweets come from any individual?

Output: Yes


Input: Consider Input: In this chapter, we apply an ensemble of deep learning and linguistics to tackle both the problem of aspect extraction and subjectivity detection. 
 Question: How are aspects identified in aspect extraction?


Output: apply an ensemble of deep learning and linguistics t