  Controllable summarization aims to provide summaries that take into account
user-specified aspects and preferences to better assist them with their
information need, as opposed to the standard summarization setup which build a
single generic summary of a document. We introduce a human-annotated data set
EntSUM for controllable summarization with a focus on named entities as the
aspects to control. We conduct an extensive quantitative analysis to motivate
the task of entity-centric summarization and show that existing methods for
controllable summarization fail to generate entity-centric summaries. We
propose extensions to state-of-the-art summarization approaches that achieve
substantially better results on our data set. Our analysis and results show the
challenging nature of this task and of the proposed data set.
