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.

Example input: We build a dataset of Twitter accounts based on two lists annotated in previous works. For the non-factual accounts, we rely on a list of 180 Twitter accounts from BIBREF1. On the other hand, for the factual accounts, we use a list with another 32 Twitter accounts from BIBREF19 that are considered trustworthy by independent third parties. 
 Question: How did they obtain the dataset?
Example output: Extractive
Example explanation: The answer to this question has been explicitly mentioned in the context, so the question is extractive.
Q: We compare the performance of translation approaches based on four metrics:

[align=left,leftmargin=0em,labelsep=0.4em,font=]

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?
A:
Abstractive