instruction:
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.
question:
In this section, we propose new simple disentanglement models that perform better than prior methods, and re-examine prior work. 
 Question: Did they experiment with the corpus?
answer:
Yes-no


question:
  In a second step, we will train a neural monolingual translation system, that translates from the output of the PBMT system INLINEFORM0 to a better target sentence INLINEFORM1 . 
 Question: Do they train the NMT model on PBMT outputs?
answer:
Yes-no


question:
Our system learns Perceptron models BIBREF37 using the Machine Learning machinery provided by the Apache OpenNLP project with our own customized (local and clustering) features.  The local features constitute our baseline system on top of which the clustering features are added. 
 Question: what are the baselines?
answer:

Abstractive