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 Input:
Building Extractive CNN/Daily Mail 
 Question: What is the problem with existing metrics that they are trying to address?

Ex Output:
Abstractive


Ex Input:
Our conversational agent uses two architectures to simulate a specialized reminiscence therapist. The block in charge of generating questions is based on the work Show, Attend and Tell BIBREF13. This work generates descriptions from pictures, also known as image captioning. 
 Question: Is machine learning system underneath similar to image caption ML systems?

Ex Output:
Yes-no


Ex Input:
The Style baseline achieves an Accuracy of 83%, LDA features 89% and a combination of the two gets 90%. However, training on full poems reduces this to 42—52%. 
 Question: Is the outcome of the LDA analysis evaluated in any way?

Ex Output:

Yes-no