2000/07/13 by Jakub Zavrel, Walter Daelemans
Computer Science · #cs.CL
published as Proceedings of the 2nd International Conference on Language Resources and Evaluation (LREC 2000), pp. 17--20 · 4 pages
arxiv created 2000/07/13 · arxiv updated 2009/11/30
This paper describes a new method, Combi-bootstrap, to exploit existing taggers and lexical resources for the annotation of corpora with new tagsets. Combi-bootstrap uses existing resources as features for a second level machine learning module, that is trained to make the mapping to the new tagset on a very small sample of annotated corpus material. Experiments show that Combi-bootstrap: i) can integrate a wide variety of existing resources, and ii) achieves much higher accuracy (up to 44.7 % error reduction) than both the best single tagger and an ensemble tagger constructed out of the same small training sample.