  Large amounts of geospatial data have been made available recently on the
linked open data cloud and the portals of many national cartographic agencies
(e.g., OpenStreetMap data, administrative geographies of various countries, or
land cover/land use data sets). These datasets use various geospatial
vocabularies and can be queried using SPARQL or its OGC-standardized extension
GeoSPARQL. In this paper, we go beyond these approaches to offer a
question-answering engine for natural language questions on top of linked
geospatial data sources. Our system has been implemented as re-usable
components of the Frankenstein question answering architecture. We give a
detailed description of the system's architecture, its underlying algorithms,
and its evaluation using a set of 201 natural language questions. The set of
questions is offered to the research community as a gold standard dataset for
the comparative evaluation of future geospatial question answering engines.
