Detection of grammatical errors involving prepositions

Published 1 January 2007Open access

Martin Chodorow, Joel Tetreault, Na-Rae Han

Citations156

TL;DR

A maximum entropy classifier combined with rule-based filters are used to detect preposition errors in a corpus of student essays to help develop an NLP application that can reliably detect these types of errors.

Abstract

This paper presents ongoing work on the detection of preposition errors of non-native speakers of English. Since prepositions account for a substantial proportion of all grammatical errors by ESL (English as a Second Language) learners, developing an NLP application that can reliably detect these types of errors will provide an invaluable learning resource to ESL students. To address this problem, we use a maximum entropy classifier combined with rule-based filters to detect preposition errors in a corpus of student essays. Although our work is preliminary, we achieve a precision of 0.8 with a recall of 0.3.

Keywords

PsychologyComputer Science

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