Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
On the algorithmic implementation of multiclass kernel-based vector machines
The Journal of Machine Learning Research
Support vector machine learning for interdependent and structured output spaces
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Coarse-to-fine n-best parsing and MaxEnt discriminative reranking
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Kernel approaches for genic interaction extraction
Bioinformatics
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
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
A local alignment kernel in the context of NLP
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
The Stanford typed dependencies representation
CrossParser '08 Coling 2008: Proceedings of the workshop on Cross-Framework and Cross-Domain Parser Evaluation
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
Two strong baselines for the BioNLP 2009 event extraction task
BioNLP '10 Proceedings of the 2010 Workshop on Biomedical Natural Language Processing
Event extraction for post-translational modifications
BioNLP '10 Proceedings of the 2010 Workshop on Biomedical Natural Language Processing
Scaling up biomedical event extraction to the entire PubMed
BioNLP '10 Proceedings of the 2010 Workshop on Biomedical Natural Language Processing
A comparative study of syntactic parsers for event extraction
BioNLP '10 Proceedings of the 2010 Workshop on Biomedical Natural Language Processing
BioNLP '10 Proceedings of the 2010 Workshop on Biomedical Natural Language Processing
Towards event extraction from full texts on infectious diseases
BioNLP '10 Proceedings of the 2010 Workshop on Biomedical Natural Language Processing
Evaluating the impact of alternative dependency graph encodings on solving event extraction tasks
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Word sense disambiguation for event trigger word detection
DTMBIO '10 Proceedings of the ACM fourth international workshop on Data and text mining in biomedical informatics
Evaluating dependency representation for event extraction
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Event extraction as dependency parsing
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Semantic parsing for biomedical event extraction
IWCS '11 Proceedings of the Ninth International Conference on Computational Semantics
EVEX: a pubmed-scale resource for homology-based generalization of text mining predictions
BioNLP '11 Proceedings of BioNLP 2011 Workshop
Towards exhaustive protein modification event extraction
BioNLP '11 Proceedings of BioNLP 2011 Workshop
Search-based structured prediction applied to biomedical event extraction
CoNLL '11 Proceedings of the Fifteenth Conference on Computational Natural Language Learning
Biomedical events extraction using the hidden vector state model
Artificial Intelligence in Medicine
A parser-based approach to detecting modification of biomedical events
Proceedings of the ACM fifth international workshop on Data and text mining in biomedical informatics
Overview of Genia event task in BioNLP Shared Task 2011
BioNLP Shared Task '11 Proceedings of the BioNLP Shared Task 2011 Workshop
Event extraction as dependency parsing for BioNLP 2011
BioNLP Shared Task '11 Proceedings of the BioNLP Shared Task 2011 Workshop
Robust biomedical event extraction with dual decomposition and minimal domain adaptation
BioNLP Shared Task '11 Proceedings of the BioNLP Shared Task 2011 Workshop
BioNLP Shared Task 2011: bacteria gene interactions and renaming
BioNLP Shared Task '11 Proceedings of the BioNLP Shared Task 2011 Workshop
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
A pattern approach for biomedical event annotation
BioNLP Shared Task '11 Proceedings of the BioNLP Shared Task 2011 Workshop
Double layered learning for biological event extraction from text
BioNLP Shared Task '11 Proceedings of the BioNLP Shared Task 2011 Workshop
MSR-NLP entry in BioNLP Shared Task 2011
BioNLP Shared Task '11 Proceedings of the BioNLP Shared Task 2011 Workshop
Generalizing biomedical event extraction
BioNLP Shared Task '11 Proceedings of the BioNLP Shared Task 2011 Workshop
Stanford's multi-pass sieve coreference resolution system at the CoNLL-2011 shared task
CONLL Shared Task '11 Proceedings of the Fifteenth Conference on Computational Natural Language Learning: Shared Task
Fast and robust joint models for biomedical event extraction
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
A framework for biological event extraction from text
Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics
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 a system for extracting complex events among genes and proteins from biomedical literature, developed in context of the BioNLP'09 Shared Task on Event Extraction. For each event, its text trigger, class, and arguments are extracted. In contrast to the prevailing approaches in the domain, events can be arguments of other events, resulting in a nested structure that better captures the underlying biological statements. We divide the task into independent steps which we approach as machine learning problems. We define a wide array of features and in particular make extensive use of dependency parse graphs. A rule-based post-processing step is used to refine the output in accordance with the restrictions of the extraction task. In the shared task evaluation, the system achieved an F-score of 51.95% on the primary task, the best performance among the participants.