en
Scientific article
Open access
English

A Hedgehop Over a Max-Margin Framework Using Hedge Cues

ContributorsGeorgescul, Maria
Publication date2010
Abstract

In this paper, we describe the experimental settings we adopted in the context of the 2010 CoNLL shared task for detecting sentences containing uncertainty. The classification results reported on are obtained using discriminative learning with features essentially incorporating lexical information. Hyper-parameters are tuned for each domain: using BioScope training data for the biomedical domain and Wikipedia training data for the Wikipedia test set. By allowing an efficient handling of combinations of large-scale input features, the discriminative approach we adopted showed highly competitive empirical results for hedge detection on the Wikipedia dataset: our system is ranked as the first with an F-score of 60.17%.

Research group
Citation (ISO format)
GEORGESCUL, Maria. A Hedgehop Over a Max-Margin Framework Using Hedge Cues. In: Proceedings of the 14th International Conference on Computational Natural Language Learning: Shared Task, 2010, p. 26–31.
Main files (1)
Article (Published version)
accessLevelPublic
Identifiers
  • PID : unige:11801
560views
607downloads

Technical informations

Creation09/06/2010 4:57:00 PM
First validation09/06/2010 4:57:00 PM
Update time03/14/2023 4:06:20 PM
Status update03/14/2023 4:06:20 PM
Last indexation01/15/2024 9:36:54 PM
All rights reserved by Archive ouverte UNIGE and the University of GenevaunigeBlack