Grammatical error correction using hybrid systems and type filtering
Mariano Felice, Zheng Yuan, Øistein E. Andersen, Helen Yannakoudakis, Ekaterina Kochmar · 2014
This paper describes our submission to the CoNLL 2014 shared task on grammatical error correction using a hybrid approach, which includes both a rule-based and an SMT system augmented by a large webbased language model.Furthermore, we demonstrate that correction type estimation can be used to remove unnecessary corrections, improving precision without harming recall.Our best hybrid system achieves state-of-the-art results, ranking first on the original test set and second on the test set with alternative annotations.