Accurate unlexicalized parsing
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Overview of BioNLP'09 shared task on event extraction
BioNLP '09 Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing: Shared Task
Analyzing text in search of bio-molecular events: a high-precision machine learning framework
BioNLP '09 Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing: Shared Task
Static relations: a piece in the biomedical information extraction puzzle
BioNLP '09 Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing
Incorporating GENETAG-style annotation to GENIA corpus
BioNLP '09 Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing
SemEval-2007 task 04: classification of semantic relations between nominals
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
SemEval-2010 task 8: multi-way classification of semantic relations between pairs of nominals
DEW '09 Proceedings of the Workshop on Semantic Evaluations: Recent Achievements and Future Directions
A rich feature vector for protein-protein interaction extraction from multiple corpora
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
Overview of the entity relations (REL) supporting task of BioNLP Shared Task 2011
BioNLP Shared Task '11 Proceedings of the BioNLP Shared Task 2011 Workshop
Detecting entity relations as a supporting task for bio-molecular event extraction
BioNLP Shared Task '11 Proceedings of the BioNLP Shared Task 2011 Workshop
BioNLP '12 Proceedings of the 2012 Workshop on Biomedical Natural Language Processing
New resources and perspectives for biomedical event extraction
BioNLP '12 Proceedings of the 2012 Workshop on Biomedical Natural Language Processing
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As research on biomedical text mining is shifting focus from simple binary relations to more expressive event representations, extraction performance drops due to the increase in complexity. Recently introduced data sets specifically targeting static relations between named entities and domain terms have been suggested to enable a better representation of the biological processes underlying annotated events and opportunities for addressing their complexity. In this paper, we present the first study of integrating these static relations with event data with the aim of enhancing event extraction performance. While obtaining promising results, we will argue that an event extraction framework will benefit most from this new data when taking intrinsic differences between various event types into account.