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Tracking biological relations in texts: a Referent Grammar based approach
University of Skövde, School of Humanities and Informatics.ORCID iD: 0000-0001-6233-8996
University of Skövde, School of Humanities and Informatics.
University of Skövde, School of Humanities and Informatics.
2005 (English)In: Proceedings of the workshop Biomedical Ontologies and Text Processing, in connection to ECCB/05: 4th European Conference on Computational Biology, 2005, p. 15-22Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we describe a method for extracting biological relations (in the first place, relations used in the KEGG ontology of biological pathways) from scientific texts. The main assumption is that correct syntactic analysis combined with domain-specific heuristics provides a good basis for relation extraction. We propose an algorithm that searches through the syntactic trees produced by a parser based on a formalism called Referent Grammar (inspired by Categorial Grammar), identifies relations mentioned in the sentence, and classifies them with respect to their semantic class and epistemic status (facts, counterfactuals, hypotheses).

Place, publisher, year, edition, pages
2005. p. 15-22
Identifiers
URN: urn:nbn:se:his:diva-1759OAI: oai:DiVA.org:his-1759DiVA, id: diva2:32035
Conference
4th European Conference on Computational Biology, Madrid, Spain, September 28 - October 1, 2005
Available from: 2007-10-10 Created: 2007-10-10 Last updated: 2020-10-29Bibliographically approved

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http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.124.1418&rep=rep1&type=pdf

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Gawronska, BarbaraErlendsson, BjörnOlsson, Björn

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CiteExportLink to record
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  • en-US
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  • Other locale
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Output format
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  • asciidoc
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