The invention relates to cross-document entity co-reference systems in which naturally occurring entity mentions in a document corpus are analyzed and transformed into name clusters that represent global entities. In a first aspect of the invention, a name variation module analyzes naturally occurring names of entities extracted from the document corpus and provides an initial set of equivalent names that could refer to the same real world entity. In a second aspect of the invention, a disambiguation module takes the initial set of equivalent names and uses an agglomerative clustering algorithm to disambiguate the potentially co-referent named entities.
Confidence links between name entities in disparate documents