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:
We use a benchmark dataset created by ceccarelli2013learning from the CoNLL 2003 data.  
 Question: What is the benchmark dataset?
answer:
Extractive


question:
We thus adapt an off-the-shelf reward learning algorithm BIBREF7 to the supervised setting for automated data manipulation. 
 Question: What off-the-shelf reward learning algorithm from RL for joint data manipulation learning and model training is adapted?
answer:
Extractive


question:
Named Entity Recognition (NER) in the Biomedical domain usually includes recognition of entities such as proteins, genes, diseases, treatments, drugs, etc.  
 Question: What is NER?
answer:

Extractive