Improving Toponym Extraction and Disambiguation Using Feedback Loop

Mena B. Habib, Maurice van Keulen

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review


This paper addresses two problems with toponym extraction and disambiguation. First, almost no existing works examine the extraction and disambiguation interdependency. Second, existing disambiguation techniques mostly take as input extracted toponyms without considering the uncertainty and imperfection of the extraction is the aim of this paper to investigate both avenues and to show that explicit handling of the uncertainty of annotation has much potential for making both extraction and disambiguation more robust.keywordshide markov modelconditional random fieldproperty descriptionextraction modelentity extractionthese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Original languageEnglish
Title of host publicationProceedings of the 12th International Conference on Web Engineering (ICWE 2012), Berlin, Germany
Place of PublicationBerlin
PublisherSpringer Verlag
Number of pages5
Publication statusPublished - 1 Jul 2012
Externally publishedYes

Publication series

SeriesLecture Notes in Computer Science

Cite this