Multi-dimensional classification of biomedical text
Bioinformatics
Semantic annotation of papers: interface & enrichment tool (SAPIENT)
BioNLP '09 Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 3
BioNLP '10 Proceedings of the 2010 Workshop on Biomedical Natural Language Processing
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In view of the increasing need to facilitate processing the content of scientific papers, we present an annotation scheme for annotating full papers with zones of conceptualisation, reflecting the information structure and knowledge types which constitute a scientific investigation. The latter are the Core Scientific Concepts (CoreSCs) and include Hypothesis, Motivation, Goal, Object, Background, Method, Experiment, Model, Observation, Result and Conclusion. The CoreSC scheme has been used to annotate a corpus of 265 full papers in physical chemistry and biochemistry and we are currently automating the recognition of CoreSCs in papers. We discuss how the CoreSC scheme relates to other views of scientific papers and indeed how the former could be used to help identify negation and speculation in scientific texts.