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2007

A Comparative Evaluation of Deep and Shallow Approaches to the Automatic Detection of Common Grammatical Errors

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A Comparative Evaluation of Deep and Shallow Approaches to the Automatic Detection of Common Grammatical Errors
This paper compares a deep and a shallow processing approach to the problem of classifying a sentence as grammatically wellformed or ill-formed. The deep processing approach uses the XLE LFG parser and English grammar: two versions are presented, one which uses the XLE directly to perform the classification, and another one which uses a decision tree trained on features consisting of the XLE’s output statistics. The shallow processing approach predicts grammaticality based on n-gram frequency statistics: we present two versions, one which uses frequency thresholds and one which uses a decision tree trained on the frequencies of the rarest n-grams in the input sentence. We find that the use of a decision tree improves on the basic approach only for the deep parser-based approach. We also show that combining both the shallow and deep decision tree features is effective. Our evaluation is carried out using a large test set of grammatical and ungrammatical sentences. The ungrammatical...
Joachim Wagner, Jennifer Foster, Josef van Genabit
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2007
Where EMNLP
Authors Joachim Wagner, Jennifer Foster, Josef van Genabith
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