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Bootstrapping a Tagged Corpus through Combination of Existing Heterogeneous Taggers

Jakub Zavrel·Walter Daelemans
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Abstract

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.

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Jakub Zavrel, Walter Daelemans. 2000-07-13. Bootstrapping a Tagged Corpus through Combination of Existing Heterogeneous Taggers. https://arxiv.org/abs/cs/0007018

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