We study the problem of entity salience by proposing the design and implementation of Swat, a system that identifies the salient Wikipedia entities occurring in an input document. Swat consists of several modules that are able to detect and classify on‐the‐fly Wikipedia entities as salient or not, based on a large number of syntactic, semantic, and latent features properly extracted via a supervised process, which has been trained over millions of examples drawn from the New York Times corpus. The validation process is performed through a large experimental assessment, eventually showing that Swat improves known solutions over all publicly available datasets. We release Swat via an API that we describe and comment in the paper to ease its use in other software.