In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.

Q: The Title-to-Story system is a baseline, which generates directly from topic.

A: What are the baselines?
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Q: We incorporate typing information by concatenating to the embedding vector of each input symbol one of three embedding vectors, S, E or R, where S is concatenated to structural elements (opening and closing brackets), E to entity symbols and R to relation symbol

A: How are typing hints suggested?
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Q: BIBREF5 adopt a machine learning approach for NER. Their NER system extracts medical problems, tests and treatments from discharge summaries and progress notes. The dataset used is the i2b2 2010 challenge dataset. 

A:
Does the paper explore extraction from electronic health records?
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