Classifying Syntactic Errors in Learner Language

• URL: http://arxiv.org/abs/2010.11032v2
• Date: Tue, 27 Oct 2020 14:58:14 GMT
• Title: Classifying Syntactic Errors in Learner Language
• Authors: Leshem Choshen, Dmitry Nikolaev, Yevgeni Berzak, Omri Abend
• Abstract summary: 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.
• Score: 32.93997096837712
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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 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.

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