Definition: In this task, you are given a part of an article. Your task is to generate headline (title) for this text. Preferred headlines are under fifteen words.
Input: Until now, error type performance for Grammatical Error Correction (GEC) systems could only be measured in terms of recall because system output is not annotated. In this paper, we overcome this problem by using a linguisticallyenhanced alignment to automatically extract the edits between parallel original and corrected sentences and then classify them using a new dataset-independent rule-based classifier. As human experts rated the predicted error types as “Good” or “Acceptable” in at least 95% of cases, we applied our approach to the system output produced in the CoNLL-2014 shared task to carry out a detailed analysis of system error type performance for the first time.

Automatic Annotation and Evaluation of Error Types for Grammatical Error Correction