The CISP annotation schema uncovers hypotheses and explanations in full-text scientific journal articles

Authors:
Elizabeth White;K. Bretonnel Cohen;Lawrence Hunter
Affiliations:
University of Colorado School of Medicine, Aurora, Colorado;University of Colorado School of Medicine, Aurora, Colorado;University of Colorado School of Medicine, Aurora, Colorado
Venue:
BioNLP '11 Proceedings of BioNLP 2011 Workshop
Year:
2011

Citing 3
Cited 0

Semantic annotation of papers: interface & enrichment tool (SAPIENT)

BioNLP '09 Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing
Automatically classifying sentences in full-text biomedical articles into Introduction, Methods, Results and Discussion

Bioinformatics
Automatically classifying sentences in full-text biomedical articles into Introduction, Methods, Results and Discussion

Bioinformatics

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Abstract

Increasingly, as full-text scientific papers are becoming available, scientific queries have shifted from looking for facts to looking for arguments. Researchers want to know when their colleagues are proposing theories, outlining evidentiary relations, or explaining discrepancies. We show here that sentence-level annotation with the CISP schema adapts well to a corpus of biomedical articles, and we present preliminary results arguing that the CISP schema is uniquely suited to recovering common types of scientific arguments about hypotheses, explanations, and evidence.