Introduction to Algorithms
Accurate methods for the statistics of surprise and coincidence
Computational Linguistics - Special issue on using large corpora: I
Support vector machine learning for interdependent and structured output spaces
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Discriminative learning and spanning tree algorithms for dependency parsing
Discriminative learning and spanning tree algorithms for dependency parsing
Feature forest models for probabilistic hpsg parsing
Computational Linguistics
Self-training for biomedical parsing
HLT-Short '08 Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers
Extracting complex biological events with rich graph-based feature sets
BioNLP '09 Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing: Shared Task
Forest-based translation rule extraction
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Web-scale distributional similarity and entity set expansion
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2 - Volume 2
Joint inference for knowledge extraction from biomedical literature
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Any domain parsing: automatic domain adaptation for natural language parsing
Any domain parsing: automatic domain adaptation for natural language parsing
Overview of Genia event task in BioNLP Shared Task 2011
BioNLP Shared Task '11 Proceedings of the BioNLP Shared Task 2011 Workshop
BioNLP Shared Task '11 Proceedings of the BioNLP Shared Task 2011 Workshop
BioNLP Shared Task 2011: supporting resources
BioNLP Shared Task '11 Proceedings of the BioNLP Shared Task 2011 Workshop
New resources and perspectives for biomedical event extraction
BioNLP '12 Proceedings of the 2012 Workshop on Biomedical Natural Language Processing
A three-way perspective on scientific discourse annotation for knowledge extraction
ACL '12 Proceedings of the Workshop on Detecting Structure in Scholarly Discourse
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We describe the system from the Natural Language Processing group at Microsoft Research for the BioNLP 2011 Shared Task. The task focuses on event extraction, identifying structured and potentially nested events from unannotated text. Our approach follows a pipeline, first decorating text with syntactic information, then identifying the trigger words of complex events, and finally identifying the arguments of those events. The resulting system depends heavily on lexical and syntactic features. Therefore, we explored methods of maintaining ambiguities and improving the syntactic representations, making the lexical information less brittle through clustering, and of exploring novel feature combinations and feature reduction. The system ranked 4th in the GENIA task with an F-measure of 51.5%, and 3rd in the EPI task with an F-measure of 64.9%.