Learning rules and categorization networks for language standardization

  • Authors:
  • Gerhard B. van Huyssteen;Marelie H. Davel

  • Affiliations:
  • Human Language Technology Group, Pretoria, South Africa;Human Language Technology Group, Pretoria, South Africa

  • Venue:
  • EUCCL '10 Proceedings of the NAACL HLT Workshop on Extracting and Using Constructions in Computational Linguistics
  • Year:
  • 2010

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Abstract

In this research, we use machine learning techniques to provide solutions for descriptive linguists in the domain of language standardization. With regard to the personal name construction in Afrikaans, we perform function learning from word pairs using the Default & Refine algorithm. We demonstrate how the extracted rules can be used to identify irregularities in previously standardized constructions and to predict new forms of unseen words. In addition, we define a generic, automated process that allows us to extract constructional schemas and present these visually as categorization networks, similar to what is often being used in Cognitive Grammar. We conclude that computational modeling of constructions can contribute to new descriptive linguistic insights, and to practical language solutions.