Chinese Grammatical Error Diagnosis System Based on Hybrid Model

Abstract

This paper describes our system in the Chinese Grammatical Error Diagnosis (CGED) task for learning Chinese as a Foreign Language (CFL). Our work adopts a hybrid model by integrating rulebased method and n-gram statistical method to detect Chinese grammatical errors, identify the error type and point out the position of error in the input sentences. Tri-gram is applied to disorder mistake. And the rest of mistakes are solved by the conservation rules sets. Empirical evaluation results demonstrate the utility of our CGED system.