• DocumentCode
    3714225
  • Title

    Introducing XGL - a lexicalised probabilistic graphical lemmatiser for isiXhosa

  • Author

    Lulamile Mzamo;Albert Helberg;Sonja Bosch

  • Author_Institution
    Faculty of Engineering, North-West University, Potchefstroom, South Africa
  • fYear
    2015
  • Firstpage
    142
  • Lastpage
    147
  • Abstract
    In this paper, a lexicalized probabilistic graphical lemmatiser for isiXhosa, XGL, is presented. An overview of isiXhosa lemmatisation issues is given, followed by a discussion on previous work in automated lemmatisation for isiXhosa. The paper continues to motivate for a machine learning lemmatiser for isiXhosa. IsiXhosa data used to train the lemmatiser is analyzed and the best features are identified from the analysis. The inner workings of XGL are detailed and evaluation results presented. XGL is shown to have achieved accuracy rates of 83.19% on a gold standard of word-lemma pairs, thereby outperforming similar lemmatisers such as LemmaGen´s 80.6% and 73.13% from the CST lemmatiser when trained with 35000 word-lemma pairs.
  • Keywords
    Transforms
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition Association of South Africa and Robotics and Mechatronics International Conference (PRASA-RobMech), 2015
  • Type

    conf

  • DOI
    10.1109/RoboMech.2015.7359513
  • Filename
    7359513