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.

[EX Q]: In this work, we look at a wide range of attributes and report prediction results on 62 demographic attributes.
[EX A]: How many demographic attributes they try to predict?

[EX Q]: We manually reviewed 1,177 pairs of entities and referring expressions generated by the system. Overall, 73.3% of the non-first mentions of entities were replaced with suitable shorter and more fluent expressions.
[EX A]: How is fluency of generated text evaluated?

[EX Q]: Clustering was performed separately for each specialty of doctors. We also examined the distribution of doctors' IDs in the obtained clusters. It turned out that some clusters covered almost exactly descriptions written by one doctor. This situation took place in the specialties where clusters are separated with large margins (e.g. psychiatry, pediatrics, cardiology).
[EX A]:
Do they explore similarity of texts across different doctors?