Zones of conceptualisation in scientific papers: a window to negative and speculative statements

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.

[1]  Padmini Srinivasan,et al.  The Language of Bioscience: Facts, Speculations, and Statements In Between , 2004, HLT-NAACL 2004.

[2]  Jari Björne,et al.  BioInfer: a corpus for information extraction in the biomedical domain , 2007, BMC Bioinformatics.

[3]  Ross D King,et al.  An ontology of scientific experiments , 2006, Journal of The Royal Society Interface.

[4]  Maria Liakata,et al.  An ontology methodology and CISP-the proposed Core Information about Scientific Papers , 2007 .

[5]  Ted Briscoe,et al.  Weakly Supervised Learning for Hedge Classification in Scientific Literature , 2007, ACL.

[6]  Simone Teufel,et al.  Whose Idea Was This, and Why Does it Matter? Attributing Scientific Work to Citations , 2007, HLT-NAACL.

[7]  Hagit Shatkay,et al.  Multi-dimensional classification of biomedical text: Toward automated, practical provision of high-utility text to diverse users , 2008, Bioinform..

[8]  Naoaki Okazaki,et al.  Identifying Sections in Scientific Abstracts using Conditional Random Fields , 2008, IJCNLP.

[9]  Jimmy J. Lin.  Is searching full text more effective than searching abstracts? , 2009, BMC Bioinformatics.

[10]  János Csirik,et al.  The BioScope corpus: biomedical texts annotated for uncertainty, negation and their scopes , 2008, BMC Bioinformatics.

[11]  Simone Teufel,et al.  Towards Domain-Independent Argumentative Zoning: Evidence from Chemistry and Computational Linguistics , 2009, EMNLP.

[12]  Maria Liakata,et al.  The ART Corpus , 2009 .

[13]  James R. Curran,et al.  Challenges for automatically extracting molecular interactions from full-text articles , 2009, BMC Bioinformatics.

[14]  Maria Liakata,et al.  Semantic Annotation of Papers: Interface & Enrichment Tool (SAPIENT) , 2009, BioNLP@HLT-NAACL.

[15]  Simone Teufel.  Towards Discipline-Independent Argumentative Zoning : Evidence from Chemistry and Computational Linguistics , 2009 .

[16]  Simone Teufel,et al.  Corpora for the Conceptualisation and Zoning of Scientific Papers , 2010, LREC.

[17]  Roser Morante,et al.  Descriptive Analysis of Negation Cues in Biomedical Texts , 2010, LREC.

[18]  Maria Liakata,et al.  Identifying the Information Structure of Scientific Abstracts: An Investigation of Three Different Schemes , 2010, BioNLP@ACL.