Abstract
We describe and evaluate heuristics, a collection of algorithmic procedures, which have been developed as a part of a linguistic rule-based tagger, IceTagger, for POS tagging Icelandic text. The purpose of the heuristics is to mark grammatical functions and prepositional phrases, and use this information to force feature agreement where appropriate. The heuristics are run after the application of local rules, i.e. rules which perform initial disambiguation based on a local context. Evaluation shows that the accuracy of two of the heuristics, which guess subjects and objects of verbs, is relatively high when compared to the results of parsing-based systems. Similar heuristics could be used for POS tagging texts in other morphologically complex languages.
The author would like to thank Professor Yorick Wilks for valuable comments and suggestions in the preparation of this paper. Additionally, the Institute of Lexicography at the University of Iceland receives gratitude, for kindly providing access to the IFD corpus used in this research.
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Loftsson, H. (2006). Tagging a Morphologically Complex Language Using Heuristics. In: Salakoski, T., Ginter, F., Pyysalo, S., Pahikkala, T. (eds) Advances in Natural Language Processing. FinTAL 2006. Lecture Notes in Computer Science(), vol 4139. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11816508_64
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DOI: https://doi.org/10.1007/11816508_64
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