TnT: a statistical part-of-speech tagger
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
A simple rule-based part of speech tagger
ANLC '92 Proceedings of the third conference on Applied natural language processing
Tagging French: comparing a statistical and a constraint-based method
EACL '95 Proceedings of the seventh conference on European chapter of the Association for Computational Linguistics
A syntax-based part-of-speech analyser
EACL '95 Proceedings of the seventh conference on European chapter of the Association for Computational Linguistics
Comparing a linguistic and a stochastic tagger
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Constraint grammar as a framework for parsing running text
COLING '90 Proceedings of the 13th conference on Computational linguistics - Volume 3
Transformation-based learning in the fast lane
NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
Annotating grammatical functions for German using finite-state cascades
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Tagging Icelandic text using a linguistic and a statistical tagger
NAACL-Short '07 Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers
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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.