2000/10/11 by Alexander Yeh
Computer Science · #cs.CL
published as 38th Annual Meeting of the Association for Computational Linguistics (ACL-2000), pages 126-132, Hong Kong, October, 2000 · 7 pages, uses acl2000.sty
arxiv created 2000/10/11 · arxiv updated 2009/11/30
Grammatical relationships (GRs) form an important level of natural language processing, but different sets of GRs are useful for different purposes. Therefore, one may often only have time to obtain a small training corpus with the desired GR annotations. To boost the performance from using such a small training corpus on a transformation rule learner, we use existing systems that find related types of annotations.