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 showcase by producing a detailed picture of syntactic errors in learner English and learner Russian. We further demonstrate the utility of the methodology for analyzing the outputs of leading Grammatical Error Correction (GEC) systems.
@article{arxiv.2010.11032,
title = {Classifying Syntactic Errors in Learner Language},
author = {Leshem Choshen and Dmitry Nikolaev and Yevgeni Berzak and Omri Abend},
journal= {arXiv preprint arXiv:2010.11032},
year = {2020}
}