  The determination of the reading sequence of text is fundamental to document
understanding. This problem is easily solved in pages where the text is
organized into a sequence of lines and vertical alignment runs the height of
the page (producing multiple columns which can be read from left to right). We
present a situation -- the directory page parsing problem -- where information
is presented on the page in an irregular, visually-organized, two-dimensional
format. Directory pages are fairly common in financial prospectuses and carry
information about organizations, their addresses and relationships that is key
to business tasks in client onboarding. Interestingly, directory pages
sometimes have hierarchical structure, motivating the need to generalize the
reading sequence to a reading tree. We present solutions to the problem of
identifying directory pages and constructing the reading tree, using (learnt)
classifiers for text segments and a bottom-up (right to left, bottom-to-top)
traversal of segments. The solution is a key part of a production service
supporting automatic extraction of organization, address and relationship
information from client onboarding documents.
