  Pinterest is a popular Web application that has over 250 million active
users. It is a visual discovery engine for finding ideas for recipes, fashion,
weddings, home decoration, and much more. In the last year, the company adopted
Semantic Web technologies to create a knowledge graph that aims to represent
the vast amount of content and users on Pinterest, to help both content
recommendation and ads targeting. In this paper, we present the engineering of
an OWL ontology---the Pinterest Taxonomy---that forms the core of Pinterest's
knowledge graph, the Pinterest Taste Graph. We describe modeling choices and
enhancements to WebProt\'eg\'e that we used for the creation of the ontology.
In two months, eight Pinterest engineers, without prior experience of OWL and
WebProt\'eg\'e, revamped an existing taxonomy of noisy terms into an OWL
ontology. We share our experience and present the key aspects of our work that
we believe will be useful for others working in this area.
