In this task, you will be presented with a context from an academic paper and a question based on the context. You have to classify the questions into "Extractive", "Abstractive", or "Yes-no" questions. Extractive questions can be answered by concatenating extracts taken from a context into a summary while answering abstractive questions involves paraphrasing the context using novel sentences. Yes-no question is a question whose expected answer is one of two choices, one that affirms the question and one that denies the question. Typically, the choices are either yes or no.

Q: The CreateDebate dataset was collected from an English online debate forum discussing four topics: abortion (ABO), gay rights (GAY), Obama (OBA), and marijuana (MAR).  
 Question: What topics are included in the debate data?

A: Extractive
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Q: 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?

A: Extractive
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Q: We also explored clustering 12742 STRENGTH sentences directly using CLUTO BIBREF19 and Carrot2 Lingo BIBREF20 clustering algorithms.  
 Question: What clustering algorithms were used?

A:
Extractive
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