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.

[EX Q]: To collect article-level labels, we utilized a platform in the company that has been used by the market research team to collect surveys from the subscribers of different news publishers. The survey works as follows: The user is first presented with a set of selected pages (usually 4 pages and around 20 articles) from the print paper the day before. The user can select an article each time that he or she has read, and answer some questions about it. We added 3 questions to the existing survey that asked the level of partisanship, the polarity of partisanship, and which pro- or anti- entities the article presents. We also asked the political standpoint of the user. The complete survey can be found in Appendices. 
 Question: Did they crowdsource the annotations?
[EX A]: Yes-no

[EX Q]: We use the following cheap ways to generate pseudo-source texts:

copy: in this setting, the source side is a mere copy of the target-side data. copy-marked: another way to integrate copies without having to deal with OOVs is to augment the source vocabulary with a copy of the target vocabulary.  copy-dummies: instead of using actual copies, we replace each word with “dummy” tokens.  
 Question: what data simulation techniques were introduced?
[EX A]: Extractive

[EX Q]: While $\beta $-VAE offers regularizing the ELBO via an additional coefficient $\beta \in {\rm I\!R}^+$, a simple extension BIBREF16 of its objective function incorporates an additional hyperparameter $C$ to explicitly control the magnitude of the KL term,

where $C\!\! \in \!\! {\rm I\!R}^+$ and $| . |$ denotes the absolute value. 
 Question: How does explicit constraint on the KL divergence term that authors propose looks like?
[EX A]:
Abstractive