Detection of grammatical errors involving prepositions
Martin S. Chodorow, Joel Tetreault, Na-Rae Han · 2007
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.