Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Learning the scope of hedge cues in biomedical texts
BioNLP '09 Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing
A metalearning approach to processing the scope of negation
CoNLL '09 Proceedings of the Thirteenth Conference on Computational Natural Language Learning
The CoNLL-2010 shared task: learning to detect hedges and their scope in natural language text
CoNLL '10: Shared Task Proceedings of the Fourteenth Conference on Computational Natural Language Learning --- Shared Task
Developing a robust part-of-speech tagger for biomedical text
PCI'05 Proceedings of the 10th Panhellenic conference on Advances in Informatics
The CoNLL-2010 shared task: learning to detect hedges and their scope in natural language text
CoNLL '10: Shared Task Proceedings of the Fourteenth Conference on Computational Natural Language Learning --- Shared Task
UWashington: negation resolution using machine learning methods
SemEval '12 Proceedings of the First Joint Conference on Lexical and Computational Semantics - Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation
How do negation and modality impact on opinions?
ExProM '12 Proceedings of the Workshop on Extra-Propositional Aspects of Meaning in Computational Linguistics
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Detecting speculative assertions is essential to distinguish the facts from uncertain information for biomedical text. This paper describes a system to detect hedge cues and their scope using CRF model. HCDic feature is presented to improve the system performance of detecting hedge cues on BioScope corpus. The feature can make use of cross-domain resources.