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Introduction to the CoNLL-2003 shared task: language-independent named entity recognition

Authors:

Erik F. Tjong Kim Sang,

Fien De MeulderAuthors Info & Claims

CONLL '03: Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4

Pages 142 - 147

https://doi.org/10.3115/1119176.1119195

Published: 31 May 2003 Publication History

Abstract

We describe the CoNLL-2003 shared task: language-independent named entity recognition. We give background information on the data sets (English and German) and the evaluation method, present a general overview of the systems that have taken part in the task and discuss their performance.

References

[1]

Oliver Bender, Franz Josef Och, and Hermann Ney. 2003. Maximum Entropy Models for Named Entity Recognition. In Proceedings of CoNLL-2003.

Digital Library

[2]

Andrew Borthwick. 1999. A Maximum Entropy Approach to Named Entity Recognition. PhD thesis, New York University.

Digital Library

[3]

Xavier Carreras, Lluís Màrquez, and Lluís Padró. 2003a. Learning a Perceptron-Based Named Entity Chunker via Online Recognition Feedback. In Proceedings of CoNLL-2003.

Digital Library

[4]

Xavier Carreras, Lluís Màrquez, and Lluìs Padró. 2003b. A Simple Named Entity Extractor using AdaBoost. In Proceedings of CoNLL-2003.

Digital Library

[5]

Rich Caruana and Dayne Freitag. 1994. Greedy Attribute Selection. In Proceedings of the Eleventh International Conference on Machine Learning, pages 28--36. New Brunswick, NJ, USA, Morgan Kaufman.

Digital Library

[6]

Hai Leong Chieu and Hwee Tou Ng. 2003. Named Entity Recognition with a Maximum Entropy Approach. In Proceedings of CoNLL-2003.

Digital Library

[7]

Nancy Chinchor, Erica Brown, Lisa Ferro, and Patty Robinson. 1999. 1999 Named Entity Recognition Task Definition. MITRE and SAIC.

[8]

James R. Curran and Stephen Clark. 2003. Language Independent NER using a Maximum Entropy Tagger. In Proceedings of CoNLL-2003.

Digital Library

[9]

Walter Daelemans, Jakub Zavrel, Ko van der Sloot, and Antal van den Bosch. 2002. MBT: Memory-Based Tagger, version 1.0, Reference Guide. ILK Technical Report ILK-0209, University of Tilburg, The Netherlands.

[10]

Fien De Meulder and Walter Daelemans. 2003. Memory-Based Named Entity Recognition using Unannotated Data. In Proceedings of CoNLL-2003.

Digital Library

[11]

Radu Florian, Abe Ittycheriah, Hongyan Jing, and Tong Zhang. 2003. Named Entity Recognition through Classifier Combination. In Proceedings of CoNLL-2003.

Digital Library

[12]

James Hammerton. 2003. Named Entity Recognition with Long Short-Term Memory. In Proceedings of CoNLL-2003.

Digital Library

[13]

Iris Hendrickx and Antal van den Bosch. 2003. Memory-based one-step named-entity recognition: Effects of seed list features, classifier stacking, and unannotated data. In Proceedings of CoNLL-2003.

Digital Library

[14]

Dan Klein, Joseph Smarr, Huy Nguyen, and Christopher D. Manning. 2003. Named Entity Recognition with Character-Level Models. In Proceedings of CoNLL-2003.

Digital Library

[15]

James Mayfield, Paul McNamee, and Christine Piatko. 2003. Named Entity Recognition using Hundreds of Thousands of Features. In Proceedings of CoNLL-2003.

Digital Library

[16]

Andrew McCallum and Wei Li. 2003. Early results for Named Entity Recognition with Conditional Random Fields, Feature Induction and Web-Enhanced Lexicons. In Proceedings of CoNLL-2003.

Digital Library

[17]

Robert Munro, Daren Ler, and Jon Patrick. 2003. Meta-Learning Orthographic and Contextual Models for Language Independent Named Entity Recognition. In Proceedings of CoNLL-2003.

Digital Library

[18]

Eric W. Noreen. 1989. Computer-Intensive Methods for Testing Hypotheses. John Wiley & Sons.

[19]

Lance A. Ramshaw and Mitchell P. Marcus. 1995. Text Chunking Using Transformation-Based Learning. In Proceedings of the Third ACL Workshop on Very Large Corpora, pages 82--94. Cambridge, MA, USA.

[20]

Helmut Schmid. 1995. Improvements in Part-of-Speech Tagging with an Application to German. In Proceedings of EACL-SIGDAT 1995. Dublin, Ireland.

[21]

Erik F. Tjong Kim Sang. 2002. Introduction to the CoNLL-2002 Shared Task: Language-Independent Named Entity Recognition. In Proceedings of CoNLL-2002, pages 155--158. Taipei, Taiwan.

Digital Library

[22]

C.J. van Rijsbergen. 1975. Information Retrieval. Buttersworth.

Digital Library

[23]

Casey Whitelaw and Jon Patrick. 2003. Named Entity Recognition Using a Character-based Probabilistic Approach. In Proceedings of CoNLL-2003.

Digital Library

[24]

Dekai Wu, Grace Ngai, and Marine Carpuat. 2003. A Stacked, Voted, Stacked Model for Named Entity Recognition. In Proceedings of CoNLL-2003.

Digital Library

[25]

Tong Zhang and David Johnson. 2003. A Robust Risk Minimization based Named Entity Recognition System. In Proceedings of CoNLL-2003.

Digital Library

Cited By

Xu JYu JCai YChua T(2024)Dual Contrastive Learning for Cross-Domain Named Entity RecognitionACM Transactions on Information Systems10.1145/367887942:6(1-33)Online publication date: 18-Oct-2024
https://dl.acm.org/doi/10.1145/3678879
Hou WZhao WLiu XGuo W(2024)Knowledge-Enriched Prompt for Low-Resource Named Entity RecognitionACM Transactions on Asian and Low-Resource Language Information Processing10.1145/365994823:5(1-15)Online publication date: 10-May-2024
https://dl.acm.org/doi/10.1145/3659948
Zhang XYu BCong XSu TLi QLiu TXu H(2024)Cross-Domain NER under a Divide-and-Transfer ParadigmACM Transactions on Information Systems10.1145/365561842:5(1-32)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3655618
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Information & Contributors

Information

Published In

cover image DL Hosted proceedings

CONLL '03: Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4

May 2003

213 pages

Conference Chairs:
Walter Daelemans
University of Antwerp and Tilburg University
,
Miles Osborne
University of Edinburgh

Publisher

Association for Computational Linguistics

United States

Publication History

Published: 31 May 2003

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Xu JYu JCai YChua T(2024)Dual Contrastive Learning for Cross-Domain Named Entity RecognitionACM Transactions on Information Systems10.1145/367887942:6(1-33)Online publication date: 18-Oct-2024
https://dl.acm.org/doi/10.1145/3678879
Hou WZhao WLiu XGuo W(2024)Knowledge-Enriched Prompt for Low-Resource Named Entity RecognitionACM Transactions on Asian and Low-Resource Language Information Processing10.1145/365994823:5(1-15)Online publication date: 10-May-2024
https://dl.acm.org/doi/10.1145/3659948
Zhang XYu BCong XSu TLi QLiu TXu H(2024)Cross-Domain NER under a Divide-and-Transfer ParadigmACM Transactions on Information Systems10.1145/365561842:5(1-32)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3655618
Šajina RTanković NIpšić I(2024)Multi-task peer-to-peer learning using an encoder-only transformer modelFuture Generation Computer Systems10.1016/j.future.2023.11.006152:C(170-178)Online publication date: 4-Mar-2024
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Liu HPeng WSong J(2024)RepEKShot: an evidential k-nearest neighbor classifier with repulsion loss for few-shot named entity recognitionThe Journal of Supercomputing10.1007/s11227-024-06244-080:15(22069-22098)Online publication date: 1-Oct-2024
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Koshy RElango S(2024)Applying social media in emergency response: an attention-based bidirectional deep learning system for location reference recognition in disaster tweetsApplied Intelligence10.1007/s10489-024-05462-654:7(5768-5793)Online publication date: 1-Apr-2024
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Keh SShi ZPatterson DBhagabati NDewan KGopala AIzquierdo PMallick DSharma AShrestha PFang FWilliams BChen YNeville J(2023)NewsPandaProceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence and Thirty-Fifth Conference on Innovative Applications of Artificial Intelligence and Thirteenth Symposium on Educational Advances in Artificial Intelligence10.1609/aaai.v37i13.26841(15528-15536)Online publication date: 7-Feb-2023
https://dl.acm.org/doi/10.1609/aaai.v37i13.26841
Nguyen NTan WDu LBuntine WBeare RChen CWilliams BChen YNeville J(2023)AUC maximization for low-resource named entity recognitionProceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence and Thirty-Fifth Conference on Innovative Applications of Artificial Intelligence and Thirteenth Symposium on Educational Advances in Artificial Intelligence10.1609/aaai.v37i11.26571(13389-13399)Online publication date: 7-Feb-2023
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Lou JLu YDai DJia WLin HHan XSun LWu HWilliams BChen YNeville J(2023)Universal information extraction as unified semantic matchingProceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence and Thirty-Fifth Conference on Innovative Applications of Artificial Intelligence and Thirteenth Symposium on Educational Advances in Artificial Intelligence10.1609/aaai.v37i11.26563(13318-13326)Online publication date: 7-Feb-2023
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Hu JGuo DLiu YLi ZChen ZWan XChang TWilliams BChen YNeville J(2023)A simple yet effective subsequence-enhanced approach for cross-domain NERProceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence and Thirty-Fifth Conference on Innovative Applications of Artificial Intelligence and Thirteenth Symposium on Educational Advances in Artificial Intelligence10.1609/aaai.v37i11.26515(12890-12898)Online publication date: 7-Feb-2023
https://dl.acm.org/doi/10.1609/aaai.v37i11.26515
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