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ORCID10th CoNLL 2006: New York City, USA
- Lluís Màrquez, Dan Klein:
Proceedings of the Tenth Conference on Computational Natural Language Learning, CoNLL 2006, New York City, USA, June 8-9, 2006. ACL 2006
Invited Paper
- Walter Daelemans:
A Mission for Computational Natural Language Learning. 1-5
Main Session
- Ivan Titov, James Henderson:
Porting Statistical Parsers with Data-Defined Kernels. 6-13 - Slav Petrov, Leon Barrett, Dan Klein:
Non-Local Modeling with a Mixture of PCFGs. 14-20 - Qin Iris Wang, Colin Cherry, Daniel J. Lizotte, Dale Schuurmans:
Improved Large Margin Dependency Parsing via Local Constraints and Laplacian Regularization. 21-28 - Willem H. Zuidema:
What are the Productive Units of Natural Language Grammar? A DOP Approach to the Automatic Identification of Constructions. 29-36 - Nikesh Garera, David Yarowsky:
Resolving and Generating Definite Anaphora by Modeling Hypernymy using Unlabeled Corpora. 37-44 - Oren Glickman, Ido Dagan, Walter Daelemans, Mikaela Keller, Samy Bengio:
Investigating Lexical Substitution Scoring for Subtitle Generation. 45-52 - Jun'ichi Kazama, Kentaro Torisawa:
Semantic Role Recognition Using Kernels on Weighted Marked Ordered Labeled Trees. 53-60 - Alessandro Moschitti, Daniele Pighin, Roberto Basili:
Semantic Role Labeling via Tree Kernel Joint Inference. 61-68 - Sabine Schulte im Walde:
Can Human Verb Associations Help Identify Salient Features for Semantic Verb Classification? 69-76 - Rie Kubota Ando:
Applying Alternating Structure Optimization to Word Sense Disambiguation. 77-84 - Rens Bod:
Unsupervised Parsing with U-DOP. 85-92 - Michaela Atterer, Hinrich Schütze:
A Lattice-Based Framework for Enhancing Statistical Parsers with Information from Unlabeled Corpora. 93-100 - Maria Georgescul, Alexander Clark, Susan Armstrong:
Word Distributions for Thematic Segmentation in a Support Vector Machine Approach. 101-108 - Wei-Hao Lin, Theresa Wilson, Janyce Wiebe, Alexander G. Hauptmann:
Which Side are You on? Identifying Perspectives at the Document and Sentence Levels. 109-116 - David J. Brooks:
Unsupervised Grammar Induction by Distribution and Attachment. 117-124 - Alexander Clark, Rémi Eyraud:
Learning Auxiliary Fronting with Grammatical Inference. 125-132 - Andrew Smith, Miles Osborne:
Using Gazetteers in Discriminative Information Extraction. 133-140 - Partha Pratim Talukdar, Thorsten Brants, Mark Y. Liberman, Fernando C. N. Pereira:
A Context Pattern Induction Method for Named Entity Extraction. 141-148
Shared Task
- Sabine Buchholz, Erwin Marsi:
CoNLL-X Shared Task on Multilingual Dependency Parsing. 149-164 - Yuval Krymolowski:
The Treebanks Used in the Shared Task. 165 - Giuseppe Attardi:
Experiments with a Multilanguage Non-Projective Dependency Parser. 166-170 - Eckhard Bick:
LingPars, a Linguistically Inspired, Language-Independent Machine Learner for Dependency Treebanks. 171-175 - Sander Canisius, Toine Bogers, Antal van den Bosch, Jeroen Geertzen, Erik F. Tjong Kim Sang:
Dependency Parsing by Inference over High-recall Dependency Predictions. 176-180 - Xavier Carreras, Mihai Surdeanu, Lluís Màrquez:
Projective Dependency Parsing with Perceptron. 181-185 - Ming-Wei Chang, Quang Do, Dan Roth:
A Pipeline Model for Bottom-Up Dependency Parsing. 186-190 - Yuchang Cheng, Masayuki Asahara, Yuji Matsumoto:
Multi-lingual Dependency Parsing at NAIST. 191-195 - Simon Corston-Oliver, Anthony Aue:
Dependency Parsing with Reference to Slovene, Spanish and Swedish. 196-200 - Markus Dreyer, David A. Smith, Noah A. Smith:
Vine Parsing and Minimum Risk Reranking for Speed and Precision. 201-205 - Richard Johansson, Pierre Nugues:
Investigating Multilingual Dependency Parsing. 206-210 - Ting Liu, Jinshan Ma, Huijia Zhu, Sheng Li:
Dependency Parsing Based on Dynamic Local Optimization. 211-215 - Ryan T. McDonald, Kevin Lerman, Fernando C. N. Pereira:
Multilingual Dependency Analysis with a Two-Stage Discriminative Parser. 216-220 - Joakim Nivre, Johan Hall, Jens Nilsson, Gülsen Eryigit, Svetoslav Marinov:
Labeled Pseudo-Projective Dependency Parsing with Support Vector Machines. 221-225 - Sebastian Riedel, Ruket Çakici, Iván V. Meza-Ruíz:
Multi-lingual Dependency Parsing with Incremental Integer Linear Programming. 226-230 - Michael Schiehlen, Kristina Spranger:
Language Independent Probabilistic Context-Free Parsing Bolstered by Machine Learning. 231-235 - Nobuyuki Shimizu:
Maximum Spanning Tree Algorithm for Non-projective Labeled Dependency Parsing. 236-240 - Yu-Chieh Wu, Yue-Shi Lee, Jie-Chi Yang:
The Exploration of Deterministic and Efficient Dependency Parsing. 241-245 - Deniz Yuret:
Dependency Parsing as a Classication Problem. 246-250
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