Paper: A Unified Framework for Grammar Error Correction

ACL ID W14-1713
Title A Unified Framework for Grammar Error Correction
Venue International Conference on Computational Natural Language Learning
Session shared task
Year 2014
Authors

In this paper we describe the PKU system for the CoNLL-2014 grammar error cor- rection shared task. We propose a unified framework for correcting all types of er- rors. We use unlabeled news texts instead of large amount of human annotated texts as training data. Based on these data, a tri-gram language model is used to cor- rect the replacement errors while two extra classification models are trained to correct errors related to determiners and preposi- tions. Our system achieves 25.32% in f 0.5 on the original test data and 29.10% on the revised test data.