Chunking with WPDV Models

@inproceedings{Halteren2000ChunkingWW,
  title={Chunking with WPDV Models},
  author={Hans van Halteren},
  booktitle={CoNLL/LLL},
  year={2000}
}
In this paper I describe the application of the WPDV algorithm to the CoNLL-2000 shared task, the identification of base chunks in English text (Tjong Kim Sang and Buchholz, 2000). For this task, I use a three-stage architecture: I first run five different base chunkers, then combine them and finally try to correct some recurring errors. Except for one base chunker, which uses the memory-based machine learning systern TiMBL, 1 all modules are based on WPDV models (van Halteren, 2000a). 
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Introduction to the CoNLL-2000 shared task: Chunking

E F Tjong, Kim Sang, S Buchholz
Proceedings of the CoNLL-2000 • 2000

The detection of inconsistency in manually tagged text

H Van Halteren
Proceedings of LINC2000 • 2000
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To appear. Improving accuracy in wordclass tagging through combination of machine learning systems

H Van Halteren, J Zavrel, W Daelemans
To appear. Improving accuracy in wordclass tagging through combination of machine learning systems

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