2002 | 2004

Proceedings of CoNLL-2003

The Seventh Conference on Natural Language Learning (CoNLL-2003) was held on May 31 and June 1, 2003 in association with HLT-NAACL 2003 in Edmonton, Canada.

Paper copies of these proceedings can be ordered from the Association for Computational Linguistics, 75 Paterson Street, New Brunswick, NJ 08901 USA, phone: +1-732-342-9100, fax: +1-732-342-9339, e-mail: acl@aclweb.org or from Morgan Kaufman Publishers.

The editors of these proceedings are Walter Daelemans and Miles Osborne.

CoNLL-2003 Invited Paper

Understanding the Yarowsky algorithm

Steve Abney
slides: [pdf]

CoNLL-2003 Papers

A model of syntactic disambiguation based on lexicalized grammars

Yusuke Miyao and Jun'ichi Tsujii
[abstract] [ps] [ps.gz] [pdf] [bibtex]

An SVM-based voting algorithm with application to parse reranking

Libin Shen and Aravind K. Joshi
[abstract] [ps] [ps.gz] [pdf] [bibtex]

Active learning for HPSG parse selection

Jason Baldridge and Miles Osborne
[abstract] [ps] [ps.gz] [pdf] [bibtex]

Learning subjective nouns using extraction pattern bootstrapping

Ellen Riloff, Janyce Wiebe and Theresa Wilson
[abstract] [ps] [ps.gz] [pdf] [bibtex]

Unsupervised Personal Name Disambiguation

Gideon S. Mann and David Yarowsky
[abstract] [ps] [ps.gz] [pdf] [bibtex]

Unsupervised learning of word sense disambiguation rules by estimating an optimum iteration number in the EM algorithm

Hiroyuki Shinnou and Minoru Sasaki
[abstract] [ps] [ps.gz] [pdf] [bibtex]

Bootstrapping POS taggers using unlabelled data

Stephen Clark, James R. Curran and Miles Osborne
[abstract] [ps] [ps.gz] [pdf] [bibtex]

Updating an NLP system to fit new domains: an empirical study on the sentence segmentation problem

Tong Zhang, Fred Damerau and David Johnson
[abstract] [ps] [ps.gz] [pdf] [bibtex]

Exceptionality and Natural Language Learning

Mihai Rotaru and Diane J. Litman
[abstract] [ps] [ps.gz] [pdf] [bibtex]

Semi-supervised Verb Class Discovery Using Noisy Features

Suzanne Stevenson and Eric Joanis
[abstract] [ps] [ps.gz] [pdf] [bibtex]

Preposition Semantic Classification via Penn Treebank and FrameNet

Tom O'Hara and Janyce Wiebe
[abstract] [ps] [ps.gz] [pdf] [bibtex]

Phrasenet: towards context sensitive lexical semantics

Xin Li, Dan Roth and Yuancheng Tu
[abstract] [ps] [ps.gz] [pdf] [bibtex]

Confidence estimation for translation prediction

Simona Gandrabur and George Foster
[abstract] [ps] [ps.gz] [pdf] [bibtex]

Using `smart' bilingual projection to feature-tag a monolingual dictionary

Katharina Probst
[abstract] [ps] [ps.gz] [pdf] [bibtex]

Using LSA and Noun Coordination Information to Improve the Precision and Recall of Automatic Hyponymy Extraction

Scott Cederberg and Dominic Widdows
[abstract] [ps] [ps.gz] [pdf] [bibtex]

An efficient clustering algorithm for class-based language models

Takuya Matsuzaki, Yusuke Miyao and Jun'ichi Tsujii
[abstract] [ps] [ps.gz] [pdf] [bibtex]

Training a Naive Bayes Classifier via the EM Algorithm with a Class Distribution Constraint

Yoshimasa Tsuruoka and Jun'ichi Tsujii
[abstract] [ps] [ps.gz] [pdf] [bibtex]

Identifying Events using Similarity and Context

Dominic R. Jones and Cynthia A. Thompson
[abstract] [ps] [ps.gz] [pdf] [bibtex]

CoNLL-2003 Shared Task Papers

Introduction to the CoNLL-2003 Shared Task: Language-Independent Named Entity Recognition

Erik F. Tjong Kim Sang and Fien De Meulder
paper: [abstract] [ps] [ps.gz] [pdf] [bibtex] (with corrections)
slides: [ps] [ps.gz] [pdf]

Maximum Entropy Models for Named Entity Recognition

Oliver Bender, Franz Josef Och and Hermann Ney
paper: [abstract] [ps] [ps.gz] [pdf] [bibtex]
system output: [tgz] [files]

Learning a Perceptron-Based Named Entity Chunker via Online Recognition Feedback

Xavier Carreras, Lluís Màrquez, and Lluís Padró
paper: [ps] [ps.gz] [pdf] [bibtex]
system output: [tgz] [files]

A Simple Named Entity Extractor using AdaBoost

Xavier Carreras, Lluís Màrquez, and Lluís Padró
paper: [ps] [ps.gz] [pdf] [bibtex]
system output: [tgz] [files]

Named Entity Recognition with a Maximum Entropy Approach

Hai Leong Chieu and Hwee Tou Ng
paper: [ps] [ps.gz] [pdf] [bibtex]
system output: [tgz] [files]

Language Independent NER using a Maximum Entropy Tagger

James R. Curran and Stephen Clark
paper: [abstract] [ps] [ps.gz] [pdf] [bibtex]
system output: [tgz] [files]

Memory-Based Named Entity Recognition using Unannotated Data

Fien De Meulder and Walter Daelemans
paper: [abstract] [ps] [ps.gz] [pdf] [bibtex]
system output: [tgz] [files]

Named Entity Recognition through Classifier Combination

Radu Florian, Abe Ittycheriah, Hongyan Jing and Tong Zhang
paper: [abstract] [ps] [ps.gz] [pdf] [bibtex]
system output: [tgz] [files]

Named Entity Recognition with Long Short-Term Memory

James Hammerton
paper: [abstract] [ps] [ps.gz] [pdf] [bibtex]
system output: [tgz] [files]

Memory-based one-step named-entity recognition: Effects of seed list features, classifier stacking, and unannotated data

Iris Hendrickx and Antal van den Bosch
paper: [abstract] [ps] [ps.gz] [pdf] [bibtex]
system output: [tgz] [files]

Named Entity Recognition with Character-Level Models

Dan Klein, Joseph Smarr, Huy Nguyen and Christopher D. Manning
paper: [abstract] [ps] [ps.gz] [pdf] [bibtex]
system output: [tgz] [files]

Named Entity Recognition using Hundreds of Thousands of Features

James Mayfield, Paul McNamee and Christine Piatko
paper: [abstract] [ps] [ps.gz] [pdf] [bibtex]
system output: [tgz] [files]

Early results for Named Entity Recognition with Conditional Random Fields, Feature Induction and Web-Enhanced Lexicons

Andrew McCallum and Wei Li
paper: [ps] [ps.gz] [pdf] [bibtex]
system output: [tgz] [files]

Meta-Learning Orthographic and Contextual Models for Language Independent Named Entity Recognition

Robert Munro, Daren Ler, and Jon Patrick
paper: [abstract] [ps] [ps.gz] [pdf] [bibtex]
system output: [tgz] [files]

Named Entity Recognition Using a Character-based Probabilistic Approach

Casey Whitelaw and Jon Patrick
paper: [abstract] [ps] [ps.gz] [pdf] [bibtex]
system output: [tgz] [files]

A Stacked, Voted, Stacked Model for Named Entity Recognition

Dekai Wu, Grace Ngai and Marine Carpuat
paper: [abstract] [ps] [ps.gz] [pdf] [bibtex] (with corrections)
system output: [tgz] [files]

A Robust Risk Minimization based Named Entity Recognition System

Tong Zhang and David Johnson
paper: [abstract] [ps] [ps.gz] [pdf] [bibtex]
system output: [tgz] [files]