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]: This allows Macaw to support multi-modal interactions, such as text, speech, image, click, etc. 
 Question: What modalities are supported by Macaw?
[A]: Extractive


[Q]: So, we can impose the constraint that our model's representation of the input's syntax cannot contain this context-invariant information. This regularization is strictly preferable to allowing all aspects of word meaning to propagate into the input's syntax representation. Without such a constraint, all inputs could, in principle, be given their own syntactic categories. 
 Question: Does having constrained neural units imply word meanings are fixed across different context?
[A]: Yes-no


[Q]: Internally, the ASR system maintains a rich hypothesis space in the form of speech lattices or confusion networks (cnets). 
 Question: What is a word confusion network?
[A]:
Abstractive