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: Although techniques for constructing this knowledge base are outside the scope of this paper, we briefly mention them. Tables were constructed using a mixture of manual and semi-automatic techniques
Question: How is the semi-structured knowledge base created?

Output: using a mixture of manual and semi-automatic techniques

Input: Consider Input: Fenerbahce 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 Fenerbahce (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?

Output: tweets are annotated with only Favor or Against for two targets - Galatasaray and Fenerbahce

Input: Consider Input: We thus adapt an off-the-shelf reward learning algorithm BIBREF7 to the supervised setting for automated data manipulation.
Question: What off-the-shelf reward learning algorithm from RL for joint data manipulation learning and model training is adapted?
Output: BIBREF7