Mining Subcategorization Information by Using Multiple Feature Loglinear Models (1999)
| Citations: | 2 - 1 self |
BibTeX
@MISC{Marques99miningsubcategorization,
author = {Nuno C. Marques and Gabriel Pereira Lopes and Carlos A. Coelho},
title = {Mining Subcategorization Information by Using Multiple Feature Loglinear Models},
year = {1999}
}
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Abstract
In this paper we show how several nonindependent features can be conjugated for loglinear statistical modeling of subcategorization information. Having this in mind we will present a method for unsupervised learning of statistical loglinear models for words with the same subcategorization frame, using huge collections of fully automatically part-of-speech tagged texts. Experiments done show that in some cases we can improve our previous approach precision (using just one feature) from 82% to 91%. 1 Introduction In this paper we show how several nonindependent features can be conjugated in order to quantitatively characterize word subcategorization frames. Elsewhere, (Marques et. al. 1998a), (Marques et. al. 1998b) we have showed that loglinear modelling (Agresti 1990) can be used for clustering verbs (and other words), based on the occurrence of a single relevant feature extracted from corpora. However, there were cases, such as subject verb (SV) order inversion, VS, that led, in Por...
Citations
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