Proceedings of the Fourteenth Conference on Computational Natural Language Learning – Shared Task

Richárd Farkas, Veronika Vincze, György Szarvas, György Móra, János Csirik (Editors)


Anthology ID:
W10-30
Month:
July
Year:
2010
Address:
Uppsala, Sweden
Venues:
CoNLL | WS
SIG:
SIGNLL
Publisher:
Association for Computational Linguistics
URL:
https://aclanthology.org/W10-30
DOI:
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PDF:
https://aclanthology.org/W10-30.pdf

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Proceedings of the Fourteenth Conference on Computational Natural Language Learning – Shared Task
Richárd Farkas | Veronika Vincze | György Szarvas | György Móra | János Csirik

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The CoNLL-2010 Shared Task: Learning to Detect Hedges and their Scope in Natural Language Text
Richárd Farkas | Veronika Vincze | György Móra | János Csirik | György Szarvas

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A Cascade Method for Detecting Hedges and their Scope in Natural Language Text
Buzhou Tang | Xiaolong Wang | Xuan Wang | Bo Yuan | Shixi Fan

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Detecting Speculative Language Using Syntactic Dependencies and Logistic Regression
Andreas Vlachos | Mark Craven

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A Hedgehop over a Max-Margin Framework Using Hedge Cues
Maria Georgescul

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Detecting Hedge Cues and their Scopes with Average Perceptron
Feng Ji | Xipeng Qiu | Xuanjing Huang

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Memory-Based Resolution of In-Sentence Scopes of Hedge Cues
Roser Morante | Vincent Van Asch | Walter Daelemans

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Resolving Speculation: MaxEnt Cue Classification and Dependency-Based Scope Rules
Erik Velldal | Lilja Øvrelid | Stephan Oepen

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Combining Manual Rules and Supervised Learning for Hedge Cue and Scope Detection
Marek Rei | Ted Briscoe

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Hedge Detection Using the RelHunter Approach
Eraldo Fernandes | Carlos Crestana | Ruy Milidiú

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A High-Precision Approach to Detecting Hedges and their Scopes
Halil Kilicoglu | Sabine Bergler

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Exploiting Rich Features for Detecting Hedges and their Scope
Xinxin Li | Jianping Shen | Xiang Gao | Xuan Wang

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Uncertainty Detection as Approximate Max-Margin Sequence Labelling
Oscar Täckström | Sumithra Velupillai | Martin Hassel | Gunnar Eriksson | Hercules Dalianis | Jussi Karlgren

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Hedge Detection and Scope Finding by Sequence Labeling with Procedural Feature Selection
Shaodian Zhang | Hai Zhao | Guodong Zhou | Bao-Liang Lu

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Learning to Detect Hedges and their Scope Using CRF
Qi Zhao | Chengjie Sun | Bingquan Liu | Yong Cheng

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Exploiting Multi-Features to Detect Hedges and their Scope in Biomedical Texts
Huiwei Zhou | Xiaoyan Li | Degen Huang | Zezhong Li | Yuansheng Yang

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A Lucene and Maximum Entropy Model Based Hedge Detection System
Lin Chen | Barbara Di Eugenio

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HedgeHunter: A System for Hedge Detection and Uncertainty Classification
David Clausen

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Exploiting CCG Structures with Tree Kernels for Speculation Detection
Liliana Mamani Sánchez | Baoli Li | Carl Vogel

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Uncertainty Learning Using SVMs and CRFs
Vinodkumar Prabhakaran

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Features for Detecting Hedge Cues
Nobuyuki Shimizu | Hiroshi Nakagawa

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A Simple Ensemble Method for Hedge Identification
Ferenc Szidarovszky | Illés Solt | Domonkos Tikk

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A Baseline Approach for Detecting Sentences Containing Uncertainty
Erik Tjong Kim Sang

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Hedge Classification with Syntactic Dependency Features Based on an Ensemble Classifier
Yi Zheng | Qifeng Dai | Qiming Luo | Enhong Chen