Paper: Rapid Parser Development: A Machine Learning Approach For Korean

ACL ID A00-2016
Title Rapid Parser Development: A Machine Learning Approach For Korean
Venue Annual Conference of the North American Chapter of the Association for Computational Linguistics
Session Main Conference
Year 2000
Authors
  • Ulf Hermjakob (University of Southern California, Marina del Rey CA)

This paper demonstrates that machine learning is a suitable approach for rapid parser development. From 1000 newly treebanked Korean sentences we generate a deterministic shift-reduce parser. The quality of the treebank, particularly crucial given its small size, is supported by a consistency checker.