A Nested Attention Neural Hybrid Model for Grammatical Error Correction
Table 7: Precision, Recall and F0.5 results on CoNLL-13,on the ”small changes” and “large changes” portions of the OOV segment.
['[BOLD] Model', '[BOLD] Performance P', '[BOLD] Performance R', '[BOLD] Performance  [ITALIC] F0.5']
Our hypothesis is that the additional character-level attention layer is particularly useful to model edits among orthographically similar words. We can see that the gains in the “small changes” portion are indeed quite large, indicating that the fine-grained character-level attention empowers the model to more accurately correct confusions among phrases with high character-level similarity. The impact in the “large changes” portion is slightly positive in precision and slightly negative in recall. Thus most of the benefit of the additional character-level attention stems from improvements in the “small changes” portion.