Automatic Detection of Sentence Fragments

We present and evaluate a method for automatically detecting sentence fragments in English texts written by non-native speakers. Our method combines syntactic parse tree patterns and parts-of-speech information produced by a tagger to detect this phenomenon. When evaluated on a corpus of authentic learner texts, our best model achieved a precision of 0.84 and a recall of 0.62, a statistically significant improvement over baselines using non-parse features, as well as a popular grammar checker.

• Type: Journal
• Year: 2015
• Where: ACL
• Authors: Chak Yan Yeung, John Lee
• Keywords: ACL 2015, Computational Linguistics