Modifying Corpus Annotation to Support the Analysis of Learner Language
Issue: Vol 26 No. 3 (2009)
Journal: CALICO Journal
Subject Areas:
Abstract:
A crucial question for automatically analyzing learner language is to determine which grammatical information is relevant and useful for learner feedback. Based on knowledge about how learner language varies in its grammatical properties, we propose a framework for reusing analyses found in corpus annotation and illustrate its applicability to Korean postpositional particles. Simple transformations of the corpus annotation allow one to quickly use state-of-the-art parsing methods.
Author: Markus Dickinson, Chong Min Lee