Tagging a Morphologically Complex Language Using an Averaged Perceptron Tagger: The Case of Icelandic
Hrafn Loftsson, Robert Östling · DSpace repository (University of Tartu) · 2013
In this paper, we experiment with using Stagger, an open-source implementation of an Averaged Perceptron tagger, to tag Icelandic, a morphologically complex language.By adding languagespecific linguistic features and using IceMorphy, an unknown word guesser, we obtain stateof-the-art tagging accuracy of 92.82%.Furthermore, by adding data from a morphological database, and word embeddings induced from an unannotated corpus, the accuracy increases to 93.84%.This is equivalent to an error reduction of 5.5%, compared to the previously best tagger for Icelandic, consisting of linguistic rules and a Hidden Markov Model.