Using Spatial Reference Frames to Generate Grounded Textual Summaries of Georeferenced Data

Summarising georeferenced (can be identified according to it's location) data in natural language is challenging because it requires linking events describing its non-geographic attributes to their underlying geography. This mapping is not straightforward as often the only explicit geographic information such data contains is latitude and longitude. In this paper we present an approach to generating textual summaries of georeferenced data based on spatial reference frames. This approach has been implemented in a data-to-text system we have deployed in the weather forecasting domain.

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