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.

The question generation model provides each candidate answer with a score by measuring semantic relevance between the question and the generated question based on the semantics of the candidate answer.  
 Question: Where is a question generation model used?
Extractive

Visual Question Generation (VQG) is another emerging topic which aims to ask questions given an image. Motivated by this, BIBREF10 proposed open-ended VQG that aims to generate natural and engaging questions about an image. 
 Question: Do they survey visual question generation work?
Yes-no

We compare the performance of translation approaches based on four metrics:

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As in BIBREF20 , EM is 1 if a predicted plan matches exactly the ground truth; otherwise it is 0.

The harmonic average of the precision and recall over all the test set BIBREF26 .

The minimum number of insertions, deletions or swap operations required to transform a predicted sequence of behaviors into the ground truth sequence BIBREF27 .

GM is 1 if a predicted plan reaches the ground truth destination (even if the full sequence of behaviors does not match exactly the ground truth). Otherwise, GM is 0. 
 Question: What evaluation metrics are used?

Abstractive