Title
Adapting The Edinburgh Geoparser For Historical Georeferencing
Abstract
Place name mentions in text may have more than one potential referent (e.g. Peru, the country vs. Peru, the city in Indiana). The Edinburgh Language Technology Group (LTG) has developed the Edinburgh Geoparser, a system that can automatically recognise place name mentions in text and disambiguate them with respect to a gazetteer. The recognition step is required to identify location mentions in a given piece of text. The subsequent disambiguation step, generally referred to as georesolution, grounds location mentions to their corresponding gazetteer entries with latitude and longitude values, for example, to visualise them on a map. Geoparsing is not only useful for mapping purposes but also for making document collections more accessible as it can provide additional metadata about the geographical content of documents. Combined with other information mined from text such as person names and date expressions, complex relations between such pieces of information can be identified. The Edinburgh Geoparser can be used with several gazetteers including Unlock and GeoNames to process a variety of input texts. The original version of the Geoparser was a demonstrator configured for modern text. Since then, it has been adapted to georeference historic and ancient text collections as well as modern-day newspaper text. 1,2,3,4 Currently, the LTG is involved in three research projects applying the Geoparser to historical text collections of very different types and for a variety of end-user applications. This paper discusses the ways in which we have customised the Geoparser for specific datasets and applications relevant to each project.
Year
DOI
Venue
2015
10.3366/ijhac.2015.0136
INTERNATIONAL JOURNAL OF HUMANITIES AND ARTS COMPUTING-A JOURNAL OF DIGITAL HUMANITIES
Keywords
Field
DocType
Georeferencing, georesolution, text mining, domain adaptation
Metadata,World Wide Web,Information retrieval,Domain adaptation,Georeference,Geographic coordinate system,Geoparsing,Referent,Multimedia,Geography,Language technology
Journal
Volume
Issue
ISSN
9
1
1753-8548
Citations 
PageRank 
References 
9
0.72
6
Authors
4
Name
Order
Citations
PageRank
Beatrice Alex123725.59
Kate Byrne2594.36
Claire Grover3729100.15
Richard Tobin414514.83