  Efficiently finding doctors and locations is an important search problem for
patients in the healthcare domain, for which traditional information retrieval
methods tend not to work optimally. In the last ten years, knowledge graphs
(KGs) have emerged as a powerful way to combine the benefits of gleaning
insights from semi-structured data using semantic modeling, natural language
processing techniques like information extraction, and robust querying using
structured query languages like SPARQL and Cypher. In this short paper, we
present a KG-based search engine architecture for robustly finding doctors and
locations in the healthcare domain. Early results demonstrate that our approach
can lead to significantly higher coverage for complex queries without degrading
quality.
