  The similarity between the question and indexed documents is a crucial factor
in document retrieval for retrieval-augmented question answering. Although this
is typically the only method for obtaining the relevant documents, it is not
the sole approach when dealing with entity-centric questions. In this study, we
propose Entity Retrieval, a novel retrieval method which rather than relying on
question-document similarity, depends on the salient entities within the
question to identify the retrieval documents. We conduct an in-depth analysis
of the performance of both dense and sparse retrieval methods in comparison to
Entity Retrieval. Our findings reveal that our method not only leads to more
accurate answers to entity-centric questions but also operates more
efficiently.
