  With the increasing popularity of mobile devices and the wide adoption of
mobile Apps, an increasing concern of privacy issues is raised. Privacy policy
is identified as a proper medium to indicate the legal terms, such as GDPR, and
to bind legal agreement between service providers and users. However, privacy
policies are usually long and vague for end users to read and understand. It is
thus important to be able to automatically analyze the document structures of
privacy policies to assist user understanding. In this work we create a
manually labelled corpus containing $167$ privacy policies (of more than $447$K
words and $5,276$ annotated paragraphs). We report the annotation process and
details of the annotated corpus. We also benchmark our data corpus with $4$
document classification models, thoroughly analyze the results and discuss
challenges and opportunities for the research committee to use the corpus. We
release our labelled corpus as well as the classification models for public
access.
