1998 TaggingInflectiveLanguagesPredi

Subject Headings: Morphological Analysis Task; Morphological Parsing Task

Notes

The major obstacle in morphological (sometimes called morpho-syntactic, or extended POS) tagging of highly inflective languages, such as Czech or Russian, is - given the resources possibly available - the tagset size. Typically, it is in the order of thousands. Our method uses an exponential probabilistic model based on automatically selected features. The parameters of the model are computed using simple estimates (which makes training much faster than when one uses Maximum Entropy) to directly minimize the error rate on training data. The results obtained so far not only show good performance on disambiguation of most of the individual morphological categories, but they also show a significant improvement on the overall prediction of the resulting combined tag over a HMM-based tag n-gram model, using even substantially less training data.

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
1998 TaggingInflectiveLanguagesPredi	Jan Hajič Barbora Hladká			Tagging Inflective Languages: Prediction of Morphological Categories for a Rich, Structured Tagset				10.3115/980845.980927		1998