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- W1877758754 abstract "In this paper we show how loglinear models can be used to cluster verbs based on their subcategorization preferences. We describe how the information about the phrases or clauses a verb goes with can be computationally learned from an automatically tagged corpus with 9,333,555 words. We will use loglinear modeling to describe the relation between the acquired counts for the part-of-speech tags co-occurring with the verbs on predetermined positions.Based on these results an unsupervised clustering algorithm will be proposed." @default.
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- W1877758754 date "1998-01-01" @default.
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- W1877758754 title "Learning verbal transitivity using loglinear models" @default.
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- W1877758754 doi "https://doi.org/10.1007/bfb0026667" @default.
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