Paper: Detecting Errors in Automatically-Parsed Dependency Relations

ACL ID P10-1075
Title Detecting Errors in Automatically-Parsed Dependency Relations
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2010
Authors

We outline different methods to detect er- rors in automatically-parsed dependency corpora, by comparing so-called depen- dency rules to their representation in the training data and flagging anomalous ones. By comparing each new rule to every rel- evant rule from training, we can identify parts of parse trees which are likely erro- neous. Even the relatively simple methods of comparison we propose show promise for speeding up the annotation process.