  In this paper, we propose a method for automatically constructing a
passage-to-summary dataset by mining the Wikipedia page revision histories. In
particular, the method mines the main body passages and the introduction
sentences which are added to the pages simultaneously. The constructed dataset
contains more than one hundred thousand passage-summary pairs. The quality
analysis shows that it is promising that the dataset can be used as a training
and validation set for passage summarization. We validate and analyze the
performance of various summarization systems on the proposed dataset. The
dataset will be available online at https://res.qyzhou.me.
