@inproceedings{grover-tobin-2006-rule,
title = "Rule-Based Chunking and Reusability",
author = "Grover, Claire and
Tobin, Richard",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Gangemi, Aldo and
Maegaard, Bente and
Mariani, Joseph and
Odijk, Jan and
Tapias, Daniel",
booktitle = "Proceedings of the Fifth International Conference on Language Resources and Evaluation ({LREC}{'}06)",
month = may,
year = "2006",
address = "Genoa, Italy",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2006/pdf/457_pdf.pdf",
abstract = "In this paper we discuss a rule-based approach to chunking implemented using the LT-XML2 and LT-TTT2 tools. We describe the tools and the pipeline and grammars that have been developed for the task of chunking. We show that our rule-based approach is easy to adapt to different chunking styles and that the mark-up of further linguistic information such as nominal and verbal heads can be added to the rules at little extra cost. We evaluate our chunker against the CoNLL 2000 data and discuss discrepancies between our output and the CoNLL mark-up as well as discrepancies within the CoNLL data itself. We contrast our results with the higher scores obtained using machine learning and argue that the portability and flexibility of our approach still make it a more practical solution.",
}
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<abstract>In this paper we discuss a rule-based approach to chunking implemented using the LT-XML2 and LT-TTT2 tools. We describe the tools and the pipeline and grammars that have been developed for the task of chunking. We show that our rule-based approach is easy to adapt to different chunking styles and that the mark-up of further linguistic information such as nominal and verbal heads can be added to the rules at little extra cost. We evaluate our chunker against the CoNLL 2000 data and discuss discrepancies between our output and the CoNLL mark-up as well as discrepancies within the CoNLL data itself. We contrast our results with the higher scores obtained using machine learning and argue that the portability and flexibility of our approach still make it a more practical solution.</abstract>
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%0 Conference Proceedings
%T Rule-Based Chunking and Reusability
%A Grover, Claire
%A Tobin, Richard
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Gangemi, Aldo
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Odijk, Jan
%Y Tapias, Daniel
%S Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)
%D 2006
%8 May
%I European Language Resources Association (ELRA)
%C Genoa, Italy
%F grover-tobin-2006-rule
%X In this paper we discuss a rule-based approach to chunking implemented using the LT-XML2 and LT-TTT2 tools. We describe the tools and the pipeline and grammars that have been developed for the task of chunking. We show that our rule-based approach is easy to adapt to different chunking styles and that the mark-up of further linguistic information such as nominal and verbal heads can be added to the rules at little extra cost. We evaluate our chunker against the CoNLL 2000 data and discuss discrepancies between our output and the CoNLL mark-up as well as discrepancies within the CoNLL data itself. We contrast our results with the higher scores obtained using machine learning and argue that the portability and flexibility of our approach still make it a more practical solution.
%U http://www.lrec-conf.org/proceedings/lrec2006/pdf/457_pdf.pdf
Markdown (Informal)
[Rule-Based Chunking and Reusability](http://www.lrec-conf.org/proceedings/lrec2006/pdf/457_pdf.pdf) (Grover & Tobin, LREC 2006)
ACL
- Claire Grover and Richard Tobin. 2006. Rule-Based Chunking and Reusability. In Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06), Genoa, Italy. European Language Resources Association (ELRA).