Syntactic Dependency Based N-grams in Rule Based Automatic English as Second Language Grammar Correction

In this paper, we present a system for automatic English (L2) grammatical error correction. It participated in ConLL 2013 shared tasks. The system applies a set of simple rules for correction of grammatical errors. In some cases, it uses syntactic n-grams, i.e., n-grams that are constructed in a syntactic metric: namely, by following paths in dependency trees, i.e., there is special procedure that allows obtaining syntactic n-grams. Note that in general case syntactic n-grams permit introducing syntactic information into machine learning methods, because syntactic n-grams have all properties of traditional n-grams. The system is simple, practically does not use additional linguistic resources and was constructed in two months. Due to its simplicity it does not obtain better scores as compared to more sophisticated systems that use many resources, the Internet and machine learning methods, but it can be positioned as a baseline system for the task.

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