Textgeographic

Textgeographic is a field that focuses on extracting and interpreting geographic information contained in natural language text. It covers the identification of geographic references (toponyms), the resolution of these references to precise coordinates, and the integration of that information into geographic information systems and retrieval systems. The central tasks include geoparsing, named-entity recognition for locations, toponym disambiguation, and geocoding to map references to coordinates using gazetteers such as GeoNames, OpenStreetMap, or national databases. It often combines natural language processing with geographic information system methods to analyze spatial relationships and geographic distribution in text.

Applications of textgeographic include analyzing news reports for event locations, processing social media posts during disasters, enriching digital archives with place metadata, and supporting location-based search and recommendation systems. In academia, it intersects computational linguistics, information retrieval, and geography, sometimes under the broader umbrellas of spatial text mining or geographic information retrieval.

Data sources commonly used are news articles, travel writing, blogs, and social media. Techniques address cross-lingual toponymy, temporal aspects, and ambiguity resolution, since many places share names across regions. Challenges include toponym ambiguity, multilingual and multi-script issues, variation in place names, evolving administrative boundaries, and privacy considerations when handling user-generated content. Ongoing work seeks to improve accuracy through richer gazetteers, context-aware disambiguation, and closer integration with map-based visualization. See also geoparsing, geotagging, spatial information retrieval, and spatial text mining.