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Title:Judging grammaticality: experiments in sentence classification
Authors:Wagner et al., 2010
Abstract: A classifier which is capable of distinguishing a syntactically well formed sentence from a syntactically ill formed one has the potential to be useful in an L2 language-learning context. In this article, we describe a classifier which classifies English sentences as either well formed or ill formed using information gleaned from three different natural language processing techniques. We describe the issues involved in acquiring data to train such a classifier and present experimental results for this classifier on a variety of ill formed sentences. We demonstrate that (a) the combination of information from a variety of linguistic sources is helpful, (b) the trade-off between accuracy on well formed sentences and accuracy on ill formed sentences can be fine tuned by training multiple classifiers in a voting scheme, and (c) the performance of the classifier is varied, with better performance on transcribed spoken sentences produced by less advanced language learners.
ICHEC Project:Parsing the British National Corpus (100M Words) with Automatically Acquired Deep probabilistic LFG Resources
URL: https://www.calico.org/memberBrowse.php?action=article&id=756
Status: Published

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