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.
REF present an approach to preposition error detection which also uses a model based on a maximum entropy classifier trained on a set of contextual features, together with a rule-based filter.
Detection of Grammatical Errors Involving Prepositions
4th ACL-SIGSEM Workshop on Prepositions
Computer Science