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: We evaluate the sequence-to-sequence QRNN architecture described in SECREF5 on a challenging neural machine translation task, IWSLT German-English spoken-domain translation, applying fully character-level segmentation.  
 Question: What languages pairs are used in machine translation?

A: Extractive
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Q: The baseline classifier uses a linear Support Vector Machine BIBREF7 , which is suited for a high number of features.  
 Question: What baseline is used?

A: Abstractive
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Q: We introduce a new crowdsourced dataset of 23,700 queries, including 22,500 in-scope queries covering 150 intents, which can be grouped into 10 general domains.  
 Question: Where does the data come from?

A:
Abstractive
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