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 task of humor identification in social media texts is analyzed as a classification problem and several machine learning classification models are used. 
 Question: What experiments were carried out on the corpus?

A: Extractive
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Q: We evaluated our attention transformations on three language pairs. We use the IWSLT 2014 corpus for De-En, the KFTT corpus for Ja-En BIBREF19 , and the WMT 2016 dataset for Ro-En. 
 Question: What are the language pairs explored in this paper?

A: Extractive
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Q: o sufficiently utilize the large dataset $\mathcal {A}$ and $\mathcal {M}$, the model is pre-trained on CTC-based ASR task and MT task in the pre-training stage. 
 Question: What is the attention module pretrained on?

A:
Extractive
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