Complex event extraction at PubMed scale
نویسندگان
چکیده
منابع مشابه
Complex event extraction at PubMed scale
MOTIVATION There has recently been a notable shift in biomedical information extraction (IE) from relation models toward the more expressive event model, facilitated by the maturation of basic tools for biomedical text analysis and the availability of manually annotated resources. The event model allows detailed representation of complex natural language statements and can support a number of a...
متن کاملPubMed-Scale Event Extraction for Post-Translational Modifications, Epigenetics and Protein Structural Relations
Recent efforts in biomolecular event extraction have mainly focused on core event types involving genes and proteins, such as gene expression, protein-protein interactions, and protein catabolism. The BioNLP’11 Shared Task extended the event extraction approach to sub-protein events and relations in the Epigenetics and Post-translational Modifications (EPI) and Protein Relations (REL) tasks. In...
متن کاملScaling up Biomedical Event Extraction to the Entire PubMed
We present the first full-scale event extraction experiment covering the titles and abstracts of all PubMed citations. Extraction is performed using a pipeline composed of state-of-the-art methods: the BANNER named entity recognizer, the McCloskyCharniak domain-adapted parser, and the Turku Event Extraction System. We analyze the statistical properties of the resulting dataset and present evalu...
متن کاملEvent Extraction with Complex Event Classification Using Rich Features
Biomedical Natural Language Processing (BioNLP) attempts to capture biomedical phenomena from texts by extracting relations between biomedical entities (i.e. proteins and genes). Traditionally, only binary relations have been extracted from large numbers of published papers. Recently, more complex relations (biomolecular events) have also been extracted. Such events may include several entities...
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ژورنال
عنوان ژورنال: Bioinformatics
سال: 2010
ISSN: 1367-4803,1460-2059
DOI: 10.1093/bioinformatics/btq180