CoNLL-X Shared Task: Multi-lingual Dependency Parsing

Tenth Conference on Computational Natural Language Learning - New York City, June 8-9, 2006

Before break
After break


Programme for the Shared Task session at CoNLL-X

See also the general CoNLL-X programme.

14:00-14:15 Introduction
1) 14:15-14:40 Experiments with a Multilanguage Non-Projective Dependency Parser
Giuseppe Attardi
14:40-14:45 A Pipeline Model for Bottom-Up Dependency Parsing
Ming-Wei Chang, Quang Do, and Dan Roth
14:45-14:50 Dependency Parsing as a Classification Problem
Deniz Yuret
2) 14:50-15:15 Labeled Pseudo-Projective Dependency Parsing with Support Vector Machines
Joakim Nivre, Johan Hall, Jens Nilsson, Gülşen Eryiğit, and Svetoslav Marinov
15:15-15:20 Multi-lingual Dependency Parsing at NAIST
Yuchang Cheng, Masayuki Asahara, and Yuji Matsumoto
15:20-15:25 The Exploration of Deterministic and Efficient Dependency Parsing
Yu-Chieh Wu, Yue-Shi Lee, and Jie-Chi Yang
15:25-15:30 Investigating Multilingual Dependency Parsing
Richard Johansson and Pierre Nugues
15:30-16:00 Coffee break
3) 16:00-16:25 Projective Dependency Parsing with Perceptron
Xavier Carreras, Mihai Surdeanu, and Lluís Màrquez
16:25-16:30 Vine Parsing and Minimum Risk Reranking for Speed and Precision
Markus Dreyer, David A. Smith, and Noah A. Smith
16:30-16:35 Dependency Parsing Based on Dynamic Local Optimization
Ting Liu, Jinshan Ma, Huijia Zhu, and Sheng Li
(could not present in New York)
16:35-16:40 Language Independent Probabilistic Context-Free Parsing Bolstered by Machine Learning
Michael Schiehlen and Kristina Spranger
4) 16:40-17:05 Multilingual Dependency Analysis with a Two-Stage Discriminative Parser
Ryan McDonald, Kevin Lerman, and Fernando Pereira
17:05-17:10 Dependency Parsing with Reference to Slovene, Spanish and Swedish
Simon Corston-Oliver and Anthony Aue
17:10-17:15 Maximum Spanning Tree Algorithm for Non-projective Labeled Dependency Parsing
Nobuyuki Shimizu
17:15-17:20 Multi-lingual Dependency Parsing with Incremental Integer Linear Programming
Sebastian Riedel, Ruket Çakıcı, and Ivan Meza-Ruiz
17:20-17:25 LingPars, a Linguistically Inspired, Language-Independent Machine Learner for Dependency Treebanks
Eckhard Bick (could not present in New York)
17:25-17:30 Dependency Parsing by Inference over High-recall Dependency Predictions
Sander Canisius, Toine Bogers, Antal van den Bosch, Jeroen Geertzen, and Erik Tjong Kim Sang
17:30-17:40 Conclusion
17:40-18:00 Discussion