Tagging a Morphologically Complex Language Using an Averaged Perceptron Tagger: The Case of Icelandic

• Main Author: Östling, Robert
• Format: Others
• Language: English
• Published: Stockholms universitet, Avdelningen för datorlingvistik 2013
• Subjects: part of speech tagging; pos tagging; icelandic
• Online Access: http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-90304

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 state-of- 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.