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Concepticons vs. lexicons: An architecture for multilingual information extraction

  • Robert Gaizauskas
  • Kevin Humphreys
  • Saliha Azzam
  • Yorick Wilks
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1299)

Abstract

Given an information extraction (IE) system that performs an extraction task against texts in one language, it is natural to consider how to modify the system to perform the same task against texts in a different language. More generally, there may be a requirement to do the extraction task against texts in an arbitrary number of different languages and to present results to a user who has no knowledge of the source language from which the information has been extracted. To minimise the language-specific alterations that need to be made in extending the system to a new language, it is important to separate the task-specific conceptual knowledge the system uses, which may be assumed to be language independent, from the language-dependent lexical knowledge the system requires, which unavoidably must be extended for each new language. In this paper we describe how the architecture of the LaSIE system, an IE system designed to do monolingual extraction from English texts, has been modified to support a clean separation between conceptual and lexical information. This separation allows hard-to-acquire, domain-specific conceptual knowledge to be represented only once, and hence to be reused in extracting information from texts in multiple languages, while standard lexical resources can be used to extend language coverage. Preliminary experiments with extending the system to French are described.

Keywords

Machine Translation Information Extraction Target Language Word Sense English Text 
These 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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Robert Gaizauskas
    • 1
  • Kevin Humphreys
    • 1
  • Saliha Azzam
    • 1
  • Yorick Wilks
    • 1
  1. 1.Department of Computer ScienceUniversity of SheffieldUSA

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