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Fourteenth Conference on Computational Natural Language Learning: Shared Task (CoNLL-ST-2010)

Thursday, July 15, 2010

 Shared Task Session 1: Overview and Oral Presentations (16:00-17:30)
16:00–16:20The CoNLL-2010 Shared Task: Learning to Detect Hedges and their Scope in Natural Language Text
Richárd Farkas, Veronika Vincze, György Móra, János Csirik and György Szarvas
16:20–16:30A Cascade Method for Detecting Hedges and their Scope in Natural Language Text
Buzhou Tang, Xiaolong Wang, Xuan Wang, Bo Yuan and Shixi Fan
16:30–16:40Detecting Speculative Language Using Syntactic Dependencies and Logistic Regression
Andreas Vlachos and Mark Craven
16:40–16:50A Hedgehop over a Max-Margin Framework Using Hedge Cues
Maria Georgescul
16:50–17:00Detecting Hedge Cues and their Scopes with Average Perceptron
Feng Ji, Xipeng Qiu and Xuanjing Huang
17:00–17:10Memory-Based Resolution of In-Sentence Scopes of Hedge Cues
Roser Morante, Vincent Van Asch and Walter Daelemans
17:10–17:20Resolving Speculation: MaxEnt Cue Classification and Dependency-Based Scope Rules
Erik Velldal, Lilja Øvrelid and Stephan Oepen
17:20–17:30Combining Manual Rules and Supervised Learning for Hedge Cue and Scope Detection
Marek Rei and Ted Briscoe
 Shared Task Discussion Panel (17:30-18:00)

Friday, July 16, 2010

 Shared Task Session 2: Poster Session (11:00-12:30)
 (Systems for both Task1 and Task2)
 Hedge Detection Using the RelHunter Approach
Eraldo Fernandes, Carlos Crestana and Ruy Milidiú
 A High-Precision Approach to Detecting Hedges and their Scopes
Halil Kilicoglu and Sabine Bergler
 Exploiting Rich Features for Detecting Hedges and their Scope
Xinxin Li, Jianping Shen, Xiang Gao and Xuan Wang
 Uncertainty Detection as Approximate Max-Margin Sequence Labelling
Oscar Täckström, Sumithra Velupillai, Martin Hassel, Gunnar Eriksson, Hercules Dalianis and Jussi Karlgren
 Hedge Detection and Scope Finding by Sequence Labeling with Procedural Feature Selection
Shaodian Zhang, Hai Zhao, Guodong Zhou and Bao-Liang Lu
 Learning to Detect Hedges and their Scope Using CRF
Qi Zhao, Chengjie Sun, Bingquan Liu and Yong Cheng
 Exploiting Multi-Features to Detect Hedges and their Scope in Biomedical Texts
Huiwei Zhou, Xiaoyan Li, Degen Huang, Zezhong Li and Yuansheng Yang
 (Systems for Task1)
 A Lucene and Maximum Entropy Model Based Hedge Detection System
Lin Chen and Barbara Di Eugenio
 HedgeHunter: A System for Hedge Detection and Uncertainty Classification
David Clausen
 Exploiting CCG Structures with Tree Kernels for Speculation Detection
Liliana Mamani Sánchez, Baoli Li and Carl Vogel
 Uncertainty Learning Using SVMs and CRFs
Vinodkumar Prabhakaran
 Features for Detecting Hedge Cues
Nobuyuki Shimizu and Hiroshi Nakagawa
 A Simple Ensemble Method for Hedge Identification
Ferenc Szidarovszky, Illés Solt and Domonkos Tikk
 A Baseline Approach for Detecting Sentences Containing Uncertainty
Erik Tjong Kim Sang
 Hedge Classification with Syntactic Dependency Features Based on an Ensemble Classifier
Yi Zheng, Qifeng Dai, Qiming Luo and Enhong Chen