iSimp in BioC standard format: enhancing the interoperability of a sentence simplification system

Yifan Peng; Catalina O Tudor; Manabu Torii; Cathy H Wu; K Vijay-Shanker

doi:10.1093/database/bau038

iSimp in BioC standard format: enhancing the interoperability of a sentence simplification system

Database (Oxford). 2014 May 21:2014:bau038. doi: 10.1093/database/bau038. Print 2014.

Authors

Yifan Peng¹, Catalina O Tudor², Manabu Torii², Cathy H Wu², K Vijay-Shanker³

Affiliations

¹ Department of Computer and Information Sciences, University of Delaware, 18 Amstel Ave, Newark, DE 19716, USA and Center for Bioinformatics and Computational Biology, University of Delaware, 15 Innovation Way, Newark, DE 19711, USA yfpeng@udel.edu.
² Department of Computer and Information Sciences, University of Delaware, 18 Amstel Ave, Newark, DE 19716, USA and Center for Bioinformatics and Computational Biology, University of Delaware, 15 Innovation Way, Newark, DE 19711, USADepartment of Computer and Information Sciences, University of Delaware, 18 Amstel Ave, Newark, DE 19716, USA and Center for Bioinformatics and Computational Biology, University of Delaware, 15 Innovation Way, Newark, DE 19711, USA.
³ Department of Computer and Information Sciences, University of Delaware, 18 Amstel Ave, Newark, DE 19716, USA and Center for Bioinformatics and Computational Biology, University of Delaware, 15 Innovation Way, Newark, DE 19711, USA.

Abstract

This article reports the use of the BioC standard format in our sentence simplification system, iSimp, and demonstrates its general utility. iSimp is designed to simplify complex sentences commonly found in the biomedical text, and has been shown to improve existing text mining applications that rely on the analysis of sentence structures. By adopting the BioC format, we aim to make iSimp readily interoperable with other applications in the biomedical domain. To examine the utility of iSimp in BioC, we implemented a rule-based relation extraction system that uses iSimp as a preprocessing module and BioC for data exchange. Evaluation on the training corpus of BioNLP-ST 2011 GENIA Event Extraction (GE) task showed that iSimp sentence simplification improved the recall by 3.2% without reducing precision. The iSimp simplification-annotated corpora, both our previously used corpus and the GE corpus in the current study, have been converted into the BioC format and made publicly available at the project's Web site: http://research.bioinformatics.udel.edu/isimp/. Database URL:http://research.bioinformatics.udel.edu/isimp/

Publication types

Research Support, N.I.H., Extramural

MeSH terms

Algorithms*
Data Mining / methods*
Internet
Natural Language Processing*
Semantics*

Grants and funding

G08LM010720/LM/NLM NIH HHS/United States