A Mixed Method Lemmatization Algorithm Using a Hierarchy of Linguistic Identities (HOLI)

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5221)


We present a new mixed method lemmatizer for Icelandic, Lemmald, which achieves good performance by relying on IceTagger [1] for tagging and The Icelandic Frequency Dictionary [2] corpus for training. We combine the advantages of data-driven machine learning with linguistic insights to maximize performance. To achieve this, we make use of a novel approach: Hierarchy of Linguistic Identities (HOLI), which involves organizing features and feature structures for the machine learning based on linguistic knowledge. Accuracy of the lemmatization is further improved using an add-on which connects to the Database of Modern Icelandic Inflections [3]. Given correct tagging, our system lemmatizes Icelandic text with an accuracy of 99.55%. We believe our method can be fruitfully adapted to other morphologically rich languages.


lemma lemmatization normalization machine learning BLARK Icelandic Lemmald IceTagger 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  1. 1.Department of IcelandicUniversity of IcelandReykjavikIceland
  2. 2.The Árni Magnusson Institute for Icelandic StudiesReykjavikIceland
  3. 3.School of Computer ScienceReykjavik UniversityReykjavikIceland

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