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 decided 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 talk, we present the engineering of an ontology--the Pinterest Taxonomy--that forms the core of Pinterest's knowledge graph, the Pinterest Taste Graph. We describe modeling choices and enhancements to the cloud-based WebProtégé tool that we used for the creation of the ontology. In two months, eight Pinterest engineers, without prior experience of ontologies, knowledge graphs, and WebProtégé, revamped an existing taxonomy of noisy terms into an OWL ontology, which they then combine with additional structured information and machinery to form the Pinterest Taste Graph. We share our experience and present the key aspects of our work that we believe will be useful for others working in this area.