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.
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Question: Firstly, LastStateRNN is the classic RNN model, where the last state passes through an MLP and then the LR Layer estimates the corresponding probability. In contrast, in the AvgRNN model we consider the average vector of all states that come out of the cells. The AttentionRNN model is the one that it has been presented in BIBREF9. 
 Question: What was the baseline?

Answer: Extractive


Question: We conduct experiments on the SQuAD dataset BIBREF3. 
 Question: On what datasets are experiments performed?

Answer: Extractive


Question: The baseline model BIBREF3 is implemented with a recurrent neural network based encoder-decoder framework. 
 Question: Do they compare against Noraset et al. 2017?

Answer:
Yes-no