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You Don’t Have to Think Twice if You Carefully Tokenize

  • Stefan Klatt
  • Bernd Bohnet
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3248)

Abstract

Most of the currently used tokenizers only segment a text into tokens and combine them to sentences. But this is not the way, we think a tokenizer should work. We believe that a tokenizer should support the following analysis components in the best way it can.

We present a tokenizer with a high focus on transparency. First, the tokenizer decisions are encoded in such a way that the original text can be reconstructed. This supports the identification of typical errors and – as a consequence – a faster creation of better tokenizer versions. Second, all detected relevant information that might be important for subsequent analysis components are made transparent by XML-tags and special information codes for each token. Third, doubtful decisions are also marked by XML-tags. This is helpful for off-line applications like corpora building, where it seems to be more appropriate to check doubtful decisions in a few minutes manually than working with incorrect data over years.

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References

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Stefan Klatt
    • 1
  • Bernd Bohnet
    • 1
  1. 1.Institute for Intelligent SystemsUniversity of StuttgartStuttgart

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