TASK DEFINITION: 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.
PROBLEM: The primary feed for the analysis collected INLINEFORM0 million tweets containing the keywords `breast' AND `cancer'.  
 Question: How were breast cancer related posts compiled from the Twitter streaming API?

SOLUTION: By using  keywords `breast' AND `cancer' in tweet collecting process. 


PROBLEM: Similarly the agents utterances can be clustered to identify system responses. However, we argue that rather than treating user utterances and agents responses in an isolated manner, there is merit in jointly clustering them. There is adjacency information of these utterances that can be utilized to identify better user intents and system responses. 
 Question: Do they study frequent user responses to help automate modelling of those?

SOLUTION: Yes

PROBLEM: As a benchmark, we will use the results of the systems by Burckhardt et al. BIBREF22 , Liu et al. BIBREF18 , Dernoncourt et al. BIBREF9 and Yang et al. BIBREF10 on the i2b2 dataset and the performance of Burckhardt et al. on the nursing corpus. 
 Question: What is their baseline?

SOLUTION:
Burckhardt et al. BIBREF22 Liu et al. BIBREF18 Dernoncourt et al. BIBREF9 Yang et al. BIBREF10