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]: Python package twitterscraper is used to scrap tweets from twitter. 10,478 tweets from the past two years from domains like `sports', `politics', `entertainment' were extracted. 
 Question: Where did the texts in the corpus come from?
[A]: Extractive


[Q]: We initialized the embeddings of these words with 300 dimensional Glove embeddings BIBREF31 .  
 Question: Do they use pretrained embeddings?
[A]: Yes-no


[Q]: However, we found that explicitly initializing these embeddings with vectors pre-trained over a large collection of unlabeled data significantly improved performance (see Section "Effects of initialized embeddings and corrupt-sampling schemes" ). 
 Question: What is the new initialization method proposed in this paper?
[A]:
Abstractive