In this paper Brill's rule-based PoS tagger is tested and adapted for Hungarian. It is shown that the present system does not obtain as high accuracy for Hungarian as it does for English (and other Germanic languages) because of the structural difference between these languages. Hungarian, unlike English, has rich morphology, is agglutinative with some inflectional characteristics and has fairly free word order. The tagger has the greatest difficulties with parts-of-speech belonging to open classes because of their complicated morphological structure. It is shown that the accuracy of tagging can be increased from approximately 83% to 97% by simply changing the rule generating mechanisms, namely the lexical templates in the lexical training module.
REF has used Brill's POS tagger with extended lexical templates to Hungarian.
Improving Brill's POS Tagger For An Agglutinative Language
Joint SIGDAT Conference On Empirical Methods In Natural Language Processing And Very Large Corpora
Computer Science