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.

Input: Consider Input: As detailed before, we adapted the cluster-linking dataset from rupnik2016news to evaluate our online crosslingual clustering approach. 
 Question: What are the sources of the datasets?

Output: Extractive


Input: Consider Input: The baseline system for the SLC task is a very simple logistic regression classifier with default parameters, where we represent the input instances with a single feature: the length of the sentence.  The baseline for the FLC task generates spans and selects one of the 18 techniques randomly.  
 Question: What was the baseline for this task?

Output: Abstractive


Input: Consider Input: we apply our domain adaptation method to a neural captioning model and show performance improvement over other standard methods on several datasets and metrics.  
 Question: Did they only experiment with captioning task?


Output: Yes-no