We present an unsupervised method for detecting grammatical errors by inferring negative evidence from edited textual corpora. The system was developed and tested using essay-length responses to prompts on the Test of English as a Foreign Language (TOEFL). The errorrecognition system, ALEK, performs with about 80% precision and 20% recall.
An unsupervised method REF is employed to detect grammatical errors by inferring negative evidence from TOEFL administrated by ETS.
An Unsupervised Method For Detecting Grammatical Errors
Applied Natural Language Processing Conference And Meeting Of The North American Association For Computational Linguistics
Computer Science