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.

Example Input: As previous systems collect relevant data from knowledge bases after observing questions during evaluation BIBREF24 , BIBREF25 , we also explore using this option. Namely, we build a customized text corpus based on questions in commonsense reasoning tasks.
Question: Do they fine-tune their model on the end task?
Example Output: Yes

Example Input: We also measure the usage of words related to people's core values as reported by Boyd et al. boyd2015. The sets of words, or themes, were excavated using the Meaning Extraction Method (MEM) BIBREF10 .
Question: How do they obtain psychological dimensions of people?
Example Output: using the Meaning Extraction Method

Example Input: Following previous studies BIBREF1, we collect event-related microposts from Twitter using 11 and 8 seed events (see Section SECREF2) for CyberAttack and PoliticianDeath, respectively. Unlabeled microposts are collected by using the keyword 'hack' for CyberAttack, while for PoliticianDeath, we use a set of keywords related to 'politician' and 'death' (such as 'bureaucrat', 'dead' etc.)
Question: Do they report results only on English data?
Example Output:
Yes