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 use the annotations from experts for an abstract if it exists otherwise use crowd annotations. 
Example Output: How do they match annotators to instances?

Example Input: We cluster the embeddings with INLINEFORM0 -Means. 
Example Output: How were the cluster extracted? 

Example Input: Specifically, we group the models based on the objective function it optimizes. We believe this work can aid the understanding of the existing literature.  We believe that the performance of these models is highly dependent on the objective function it optimizes – predicting adjacent word (within-tweet relationships), adjacent tweet (inter-tweet relationships), the tweet itself (autoencoder), modeling from structured resources like paraphrase databases and weak supervision. 
Example Output:
How do they encourage understanding of literature as part of their objective function?