Abstract
We describe our linguistic rule-based tagger IceTagger, and compare its tagging accuracy to the TnT tagger, a state-of-theart statistical tagger, when tagging Icelandic, a morphologically complex language. Evaluation shows that the average tagging accuracy is 91.54% and 90.44%, obtained by IceTagger and TnT, respectively. When tag profile gaps in the lexicon, used by the TnT tagger, are filled with tags produced by our morphological analyser IceMorphy, TnT's tagging accuracy increases to 91.18%.
Cite
CITATION STYLE
Loftsson, H. (2007). Tagging Icelandic text using a linguistic and a statistical tagger. In NAACL-HLT 2007 - Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics, Companion Volume: Short Papers (pp. 105–108). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1614108.1614135
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