Abstract
We present a method for classifying syntactic errors in learner language, namely errors whose correction alters the morphosyntactic structure of a sentence. The methodology builds on the established Universal Dependencies syntactic representation scheme, and provides complementary information to other error-classification systems. Unlike existing error classification methods, our method is applicable across languages, which we show-case by producing a detailed picture of syntactic errors in learner English and learner Rus-sian. We further demonstrate the utility of the methodology for analyzing the outputs of leading Grammatical Error Correction (GEC) systems .
| Original language | American English |
|---|---|
| Journal | arXiv e-prints |
| State | Published - 2020 |