The problem of automatic toponym resolution, or computing the mapping from occurrences of names for places as found in a text to an unambiguous spatial footprint of the location referred to, such as a geographic latitude/longitude centroid is difficult to automate due to insufficient and error-prone geographic databases, and a large degree of place name ambiguity: common words need to be distinguished from proper names (geo/non-geo ambiguity), and the mapping between names and locations is ambiguous (London can refer to the capital of the UK or to London, Ontario, Canada, or to about forty other Londons on earth). This thesis investigates how referentially ambiguous spatial named entities can be grounded, or resolved, with respect to an extensional coordinate model robustly on open-domain news text by collecting a repertoire of linguistic heuristics and extra-linguistic knowledge sources such as population. I then investigate how to combine these sources of evidence to obtain a...

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