  In this paper we look beyond metrics-based evaluation of Information
Retrieval systems, to explore the reasons behind ranking results. We present
the content-focused Neural-IR-Explorer, which empowers users to browse through
retrieval results and inspect the inner workings and fine-grained results of
neural re-ranking models. The explorer includes a categorized overview of the
available queries, as well as an individual query result view with various
options to highlight semantic connections between query-document pairs. The
Neural-IR-Explorer is available at: https://neural-ir-explorer.ec.tuwien.ac.at/
