  The Bloomberg Terminal has been a leading source of financial data and
analytics for over 30 years. Through its thousands of functions, the Terminal
allows its users to query and run analytics over a large array of data sources,
including structured, semi-structured, and unstructured data; as well as plot
charts, set up event-driven alerts and triggers, create interactive maps,
exchange information via instant and email-style messages, and so on. To
improve user experience, we have been building question answering systems that
can understand a wide range of natural language constructions for various
domains that are of fundamental interest to our users. Such natural language
interfaces, while exceedingly helpful to users, introduce a number of usability
challenges of their own. We tackle some of these challenges through
auto-completion for query formulation. A distinguishing mark of our
auto-complete systems is that they are based on and guided by corresponding
semantic parsing systems. We describe the auto-complete problem as it arises in
this setting, the novel algorithms that we use to solve it, and report on the
quality of the results and the efficiency of our approach.
