Morphological tagging: data vs. dictionaries
Jan Hajič · 2000
POS tagging for English seems to have reached the the human levels of error, but full morphological tagging for inectionally rich languages, such as Romanian, Czech, or Hungarian, is still an open problem, and the results are far from being satisfactory. This paper presents results obtained by using an universalized exponential feature-based model for ve such languages. It focuses on the data sparseness issue, which is especially severe for such languages (the more so that there are no extensive annotated data for those languages). In conclusion, we argue strongly that the use of an independent morphological dictionary is the preferred choice to more annotated data under such circumstances. 1 Full Morphological Tagging English Part of Speech (POS) tagging has been widely described in the recent past, starting with the (Church, 1988) paper, followed by numerous others using various methods: neural networks (Julian Benello and Anderson, 1989), HMM tagging (Merialdo, 1992), decision t...