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- W1995235220 abstract "Statistical methods for PP attachment fall into two classes according to the training material used: first, unsupervised methods trained on raw text corpora and second, supervised methods trained on manually disambiguated examples. Usually supervised methods win over unsupervised methods with regard to attachment accuracy. But what if only small sets of manually disambiguated material are available? We show that in this case it is advantageous to intertwine unsupervised and supervised methods into one disambiguation algorithm that outperforms both methods used alone." @default.
- W1995235220 created "2016-06-24" @default.
- W1995235220 creator A5055769728 @default.
- W1995235220 date "2002-01-01" @default.
- W1995235220 modified "2023-10-17" @default.
- W1995235220 title "Combining unsupervised and supervised methods for PP attachment disambiguation" @default.
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- W1995235220 doi "https://doi.org/10.3115/1072228.1072232" @default.
- W1995235220 hasPublicationYear "2002" @default.
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