Bootstrapping a Tagged Corpus through Combination of Existing Heterogeneous Taggers

dc.creatorZavrel, Jakub
dc.creatorDaelemans, Walter
dc.date2000-07-13
dc.date.accessioned2026-07-25T16:27:36Z
dc.descriptionThis 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.
dc.description4 pages
dc.identifierhttps://arxiv.org/abs/cs/0007018
dc.identifierhttp://arxiv.org/abs/cs/0007018
dc.identifierProceedings of the 2nd International Conference on Language Resources and Evaluation (LREC 2000), pp. 17--20
dc.identifier.urihttps://dspace.dare.co.zw/handle/123456789/41527
dc.subjectComputation and Language
dc.subjectI.2.7; I.2.6
dc.titleBootstrapping a Tagged Corpus through Combination of Existing Heterogeneous Taggers
dc.typetext

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