Don Blaheta, ``Handling noisy training and testing data'', Proceedings of the 7th conference on Empirical Methods in Natural Language Processing, 2002.


In the field of empirical natural language processing, researchers constantly deal with large amounts of marked-up data; whether the markup is done by the researcher or someone else, human nature dictates that it will have errors in it. This paper will more fully characterise the problem and discuss whether and when (and how) to correct the errors. The discussion is illustrated with specific examples involving function tagging in the Penn treebank.

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BibTeX entry

  author = {Don Blaheta},
  month = {July},
  year = 2002,
  title = {Handling noisy training and testing data},
  booktitle = {Proceedings of the 7th conference on
	{E}mpirical {M}ethods in
	{N}atural {L}anguage {P}rocessing},
  pages = {111--116} }
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