Difference between revisions of "NP Chunking (State of the art)"

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* data contains one word per line and each line contains six fields of which only the first three fields are relevant: the word, the part-of-speech tag assigned by the Brill tagger, and the correct IOB tag
 
* data contains one word per line and each line contains six fields of which only the first three fields are relevant: the word, the part-of-speech tag assigned by the Brill tagger, and the correct IOB tag
 
* dataset is available from [ftp://ftp.cis.upenn.edu/pub/chunker/ ftp://ftp.cis.upenn.edu/pub/chunker/]
 
* dataset is available from [ftp://ftp.cis.upenn.edu/pub/chunker/ ftp://ftp.cis.upenn.edu/pub/chunker/]
* more information is available from [http://ifarm.nl/erikt/research/np-chunking.html http://ifarm.nl/erikt/research/np-chunking.html]
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* more information is available from [http://ifarm.nl/erikt/research/np-chunking.html NP Chunking]
  
  
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KM00 -  Taku Kudo and Yuji Matsumoto. 2000b. Use of Support Vector Learning for Chunk Identification. In Proceedings of the 4th Conference on CoNLL-2000 and LLL-2000
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Kudo, T., and Matsumoto, Y. (2000). [http://acl.ldc.upenn.edu/W/W00/W00-0730.pdf Use of support vector learning for chunk identification]. ''Proceedings of the 4th Conference on CoNLL-2000 and LLL-2000'', pages 142-144, Lisbon, Portugal.
[http://citeseer.comp.nus.edu.sg/rd/0%2C394415%2C1%2C0.25%2CDownload/http://citeseer.comp.nus.edu.sg/cache/papers/cs/18905/http:zSzzSzlcg-www.uia.ac.bezSzconll2000zSzpszSz14244kud.pdf/kudoh00use.pdf]
 
  
KM01 - Taku Kudo and Yuji Matsumoto. Chunking with support vector machines. In NAACL-2001
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Kudo, T., and Matsumoto, Y. (2001). [http://acl.ldc.upenn.edu/N/N01/N01-1025.pdf Chunking with support vector machines]. ''Proceedings of NAACL-2001''.
[http://cactus.aist-nara.ac.jp/~taku-ku/publications/naacl2001.pdf]
 
  
Sarkar2005 - Hong Shen and Anoop Sarkar. Voting between Multiple Data Representations for Text Chunking. In proceedings of the Eighteenth Meeting of the Canadian Society for Computational Intelligence, Canadian AI 2005.  
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Shen, H., and Sarkar, A. (2005). [http://www.cs.sfu.ca/~anoop/papers/pdf/ai05.pdf Voting between multiple data representations for text chunking]. ''Proceedings of the Eighteenth Meeting of the Canadian Society for Computational Intelligence, Canadian AI 2005''.
[http://www.cs.sfu.ca/~anoop/papers/pdf/ai05.pdf]
 
  
 
[[Category:State of the art]]
 
[[Category:State of the art]]

Revision as of 10:58, 27 June 2007

  • Performance measure: F = 2 * Precision * Recall / (Recall + Precision)
  • Precision: percentage of NPs found by the algorithm that are correct
  • Recall: percentage of NPs defined in the corpus that were found by the chunking program
  • Training data: sections 15-18 of Wall Street Journal corpus (Ramshaw and Marcus)
  • Testing data: section 20 of Wall Street Journal corpus (Ramshaw and Marcus)
  • original data of the NP chunking experiments by Lance Ramshaw and Mitch Marcus
  • data contains one word per line and each line contains six fields of which only the first three fields are relevant: the word, the part-of-speech tag assigned by the Brill tagger, and the correct IOB tag
  • dataset is available from ftp://ftp.cis.upenn.edu/pub/chunker/
  • more information is available from NP Chunking


System name Short description Main publications Software Results (F)
KM00 B-I-O tagging using SVM classifiers with polynomial kernel Kudo and Matsumoto (2000) YAMCHA Toolkit (but models are not provided) 93.79
KM01 learning as in KM00, but voting between different representations Kudo and Matsumoto (2001) No 94.22
SS05 specialized HMM + voting between different representations Shen and Sarkar (2005) No 95.23


Kudo, T., and Matsumoto, Y. (2000). Use of support vector learning for chunk identification. Proceedings of the 4th Conference on CoNLL-2000 and LLL-2000, pages 142-144, Lisbon, Portugal.

Kudo, T., and Matsumoto, Y. (2001). Chunking with support vector machines. Proceedings of NAACL-2001.

Shen, H., and Sarkar, A. (2005). Voting between multiple data representations for text chunking. Proceedings of the Eighteenth Meeting of the Canadian Society for Computational Intelligence, Canadian AI 2005.