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- W2003458432 abstract "This paper presents results for a maximum-entropy-based part of speech tagger, which achieves superior performance principally by enriching the information sources used for tagging. In particular, we get improved results by incorporating these features: (i) more extensive treatment of capitalization for unknown words; (ii) features for the disambiguation of the tense forms of verbs; (iii) features for disambiguating particles from prepositions and adverbs. The best resulting accuracy for the tagger on the Penn Treebank is 96.86% overall, and 86.91% on previously unseen words." @default.
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- W2003458432 modified "2023-10-13" @default.
- W2003458432 title "Enriching the knowledge sources used in a maximum entropy part-of-speech tagger" @default.
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- W2003458432 doi "https://doi.org/10.3115/1117794.1117802" @default.
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