  Question generation from a knowledge base (KB) is the task of generating
questions related to the domain of the input KB. We propose a system for
generating fluent and natural questions from a KB, which significantly reduces
the human effort by leveraging massive web resources. In more detail, a seed
question set is first generated by applying a small number of hand-crafted
templates on the input KB, then more questions are retrieved by iteratively
forming already obtained questions as search queries into a standard search
engine, before finally questions are selected by estimating their fluency and
domain relevance. Evaluated by human graders on 500 random-selected triples
from Freebase, questions generated by our system are judged to be more fluent
than those of \newcite{serban-EtAl:2016:P16-1} by human graders.
