Detecting Errors in Automatically-Parsed Dependency Relations

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

• Type: Journal
• Year: 2010
• Where: ACL
• Authors: Markus Dickinson
• Keywords: ACL 2010, Anomalous Ones, Automatically-parsed Dependency Corpora, Computational Linguistics, So-called Dependency Rules