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.

Example Input: 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
Example Output: How are typing hints suggested?

Example Input: The BioNLP 2009 Shared Task BIBREF195 was based on the GENIA corpus BIBREF196 which contains PubMed abstracts of articles on transcription factors in human blood cells.
Example Output: Which datasets are used in this work?

Example Input: Deep convolutional neural networks (CNNs) with 2D convolutions and small kernels BIBREF1, have achieved state-of-the-art results for several speech recognition tasks BIBREF2, BIBREF3, BIBREF4, BIBREF5, BIBREF6. r Models: Our baseline CNN model BIBREF21 consists of 15 convolutional and one fully-connected layer.
Example Output:
Is model compared against state of the art models on these datasets?