Discovering the appropriate type of an entity in the Web of Data is still considered an open challenge, given the complexity of the many tasks it entails. Among them, the most notable is the definition of a generic and cross-domain ontology. While the ontologies proposed in the past function mostly as schemata for knowledge bases of different sizes, an ontology for entity typing requires a rich, accurate and easily-traversable type hierarchy. Likewise, it is desirable that the hierarchy contains thousands of nodes and multiple levels, contrary to what a manually curated ontology can offer. Such level of detail is required to describe all the possible environments in which an entity exists in. Furthermore, the generation of the ontology must follow an automated fashion, combining the most widely used data sources and following the speed of the Web. In this paper we propose deepschema.org, the first ontology that combines two well-known ontological resources, Wikidata and schema.org, to obtain a highly-accurate, generic type ontology which is at the same time a first-class citizen in the Web of Data. We describe the automated procedure we used for extracting a class hierarchy from Wikidata and analyze the main characteristics of this hierarchy. We also provide a novel technique for integrating the extracted hierarchy with schema.org, which exploits external dictionary corpora and is based on word embeddings. Finally, we present a crowdsourcing evaluation which showcases the three main aspects of our ontology, namely the accuracy, the traversability and the genericity. The outcome of this paper is published under the portal: http://deepschema.github.io.