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SuperCAT: The (New and Improved) Corpus Analysis Toolkit.

K Bretonnel Cohen1, William A Baumgartner1, Irina Temnikova2

  • 1University of Colorado School of Medicine, Aurora, Colorado, USA.

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Summary

SuperCAT is a new corpus analysis toolkit that extends previous methods to analyze language data. It quantifies lexical distributions in corpora, distinguishing between open and closed language samples.

Keywords:
corpusrepresentativenesssublanguagetoolkit

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Area of Science:

  • Computational Linguistics
  • Corpus Linguistics
  • Quantitative Linguistics

Background:

  • Existing tools like SubCAT focused on sublanguage analysis.
  • Corpus analysis requires methods applicable to general language samples, not just sublanguages.
  • Representative corpora exhibit open-ended characteristics, unlike finite non-representative corpora.

Purpose of the Study:

  • To introduce SuperCAT, a corpus analysis toolkit.
  • To extend corpus analysis capabilities beyond sublanguage analysis.
  • To provide general quantitative techniques for corpus description, focusing on lexical distributions.

Main Methods:

  • SuperCAT is a radical extension of the SubCAT architecture.
  • Focuses on quantitative description of corpus characteristics.
  • Analyzes lexical distributions and corpus closure tendencies.

Main Results:

  • SuperCAT provides general techniques for corpus analysis.
  • It differentiates corpora based on their tendency towards closure (finiteness vs. infinity).
  • The toolkit features a re-engineered architecture for enhanced functionality.

Conclusions:

  • SuperCAT offers a robust framework for general corpus analysis.
  • The toolkit is valuable for understanding lexical distributions in diverse language samples.
  • It advances the quantitative description of linguistic corpora.