A shallow parser based on closed-class words to capture relations in biomedical text
Journal of Biomedical Informatics
A rule-based approach to prepositional phrase attachment disambiguation
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 2
Medstract: creating large-scale information servers for biomedical libraries
BioMed '02 Proceedings of the ACL-02 workshop on Natural language processing in the biomedical domain - Volume 3
BioNLP '06 Proceedings of the Workshop on Linking Natural Language Processing and Biology: Towards Deeper Biological Literature Analysis
Corpus design for biomedical natural language processing
ISMB '05 Proceedings of the ACL-ISMB Workshop on Linking Biological Literature, Ontologies and Databases: Mining Biological Semantics
Syntactic dependency based heuristics for biological event extraction
BioNLP '09 Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing: Shared Task
Prepositions in applications: A survey and introduction to the special issue
Computational Linguistics
The role of nominalizations in prepositional phrase attachment in GENIA
Canadian AI'08 Proceedings of the Canadian Society for computational studies of intelligence, 21st conference on Advances in artificial intelligence
Arguments of nominals in semantic interpretation of biomedical text
BioNLP '10 Proceedings of the 2010 Workshop on Biomedical Natural Language Processing
Exploring variations across biomedical subdomains
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Customizing an information extraction system to a new domain
RELMS '11 Proceedings of the ACL 2011 Workshop on Relational Models of Semantics
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We present a small set of attachment heuristics for postnominal PPs occurring in full-text articles related to enzymes. A detailed analysis of the results suggests their utility for extraction of relations expressed by nominalizations (often with several attached PPs). The system achieves 82% accuracy on a manually annotated test corpus of over 3000 PPs from varied biomedical texts.