scope:

The automatic recognition of spatial information in natural language is currently an area of considerable attention in computational linguistics and artificial intelligence. The development of algorithms that exhibit "spatial awareness'' promises to add needed functionality to NLP systems, from named entity recognition to question answering and text-based inference. In order for such systems to reason spatially, however, they require the enrichment of textual data with the annotation of spatial information in language. This involves a large range of linguistic constructions, including spatially anchoring events, descriptions of objects in motion, viewer-relative descriptions of scenes, and absolute spatial descriptions of locations, and many other constructions. This specification provides a framework for encoding a broad range of spatial information, as well as spatiotemporal information relating to motion, as expressed in natural language texts. The standard includes reference to locations, general spatial entities, spatial relations involving topological, orientational, and metric values, dimensional information, motion events, and paths.