SpaBERT: A Pretrained Language Model from Geographic Data for Geo-Entity Representation

Understand

Named geographic entities (geo-entities for short) are the building blocks of many geographic datasets.

• Characterizing geo-entities is integral to various application domains, such as geo-intelligence and map comprehension, while a key challenge is to capture the spatial-varying context of an entity.
• We hypothesize that we shall know the characteristics of a geo-entity by its surrounding entities, similar to knowing word meanings by their linguistic context.
• Accordingly, we propose a novel spatial language model, SpaBERT, which provides a general-purpose geo-entity representation based on neighboring entities in geospatial data.