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CoNLL 2003 — accepted papers

CoNLL 2003 is the 2003 edition of the Conference on Computational Natural Language Learning (CoNLL) (publisher: Association for Computational Linguistics). OpenAlex lists 35 papers of it; our library holds 4 with our summaries. Below: the most cited papers, every accepted paper, and ours with their topics, authors and institutions.

All accepted papers (35)

The most cited first; 4 with our summary link to their page here, the others to the original.

  1. A Simple Named Entity Extractor using AdaBoost ↗Xavier Carreras, Lluís Màrquez, Lluís Padró
  2. Active learning for HPSG parse selection ↗Jason Baldridge, Miles Osborne
  3. An efficient clustering algorithm for class-based language models ↗Takuya Matsuzaki, Yusuke Miyao, Jun'ichi Tsujii
  4. Bootstrapping POS-taggers using unlabelled data ↗Stephen Clark, James Curran, Miles Osborne
  5. Identifying Events using Similarity and Context ↗Dominic R. Jones, Cynthia A. Thompson
  6. Learning subjective nouns using extraction pattern bootstrappingEllen Riloff, Janyce Wiebe, Theresa Wilsonour summary
  7. Maximum Entropy Models for Named Entity Recognition ↗Oliver Bender, Franz Josef Och, Hermann Ney
  8. Named Entity Recognition through Classifier CombinationRadu Florian, Abe Ittycheriah, Hongyan Jing et al.our summary
  9. Named Entity Recognition using Hundreds of Thousands of Features ↗James Mayfield, Paul McNamee, Christine Piatko
  10. Named Entity Recognition with Character-Level Models ↗Dan Klein, Joseph Smarr, Huy Nguyen et al.

See all 35 papers in CoNLL 2003 — accepted papers →

 Papers with our summary in our library (4)

The most cited first (OpenAlex citations plus our library's).

 Top topics

Topics of its works in our library, with the number of works on each.

Named entity recognition (3)

 Fields

Arts and Humanities (4)Computer Science (3)

 Top authors

Authors with a page who published here most often: their works here, and the citations of those works.

 Top institutions

Institutions on the bylines of its works here, by the number of works.

works and citations from OpenAlex and our library.

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