Combining Off-the-shelf Grammar and Spelling Tools for the Automatic Evaluation of Scientific Writing (AESW) Shared Task 2016
René Witte, Bahar Sateli · 2016
We applied two standard, open source tools for detecting spelling and grammar errors to the AESW 2016 shared task: After the Deadline and LanguageTool.The tools' output was combined with a Maximum Entropy machine learning model to classify each input sentence as requiring or not requiring any edits.This approach yielded the second-highest precision of 64.41% in the binary estimation task at AESW 2016, but also the lowest recall of 36.85%,resulting in an F-Measure of 46.34%.