A vast amount of location information exists in unstructured texts, such as social media
posts, news stories, scientific articles, web pages, travel blogs, and historical archives …

Semantic annotation is a crucial part of achieving the vision of the Semantic Web and has
long been a research topic among various communities. The most challenging problem in …

Natural language texts, such as tweets and news, contain a vast amount of geospatial
information, which can be extracted by first recognizing toponyms in texts (toponym …

Empirical methods in geoparsing have thus far lacked a standard evaluation framework
describing the task, metrics and data used to compare state-of-the-art systems. Evaluation is …

Geocoding is the task of converting location mentions in text into structured data that
encodes the geospatial semantics. We propose a new architecture for geocoding, GeoNorm …

Geoparsing, the task of extracting toponyms from texts and associating them with
geographic locations, has witnessed remarkable progress over the past years. However …

Geocoding aims to assign unambiguous locations (ie, geographic coordinates) to place
names (ie, toponyms) referenced within documents (eg, within spreadsheet tables or textual …

A rich amount of geographic information exists in unstructured texts, such as web pages,
social media posts, housing advertisements, and historical archives. Geoparsers are useful …

Toponym resolution is crucial for extracting geographic information from natural language
texts, such as social media posts and news articles. Despite the advancements in current …

Geoparsing is a fundamental technique for analyzing geo-entity information in text. We focus
on document-level geoparsing, which considers geographic relatedness among geo-entity …