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CALBC silver standard corpus.

Dietrich Rebholz-Schuhmann1, Antonio José Jimeno Yepes, Erik M Van Mulligen

  • 1EMBL Outstation-Hinxton, European Bioinformatics Institute, Hinxton, Cambridge CB101SD, UK. rebholz@ebi.ac.uk

Journal of Bioinformatics and Computational Biology
|February 26, 2010
PubMed
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The CALBC initiative harmonized biomedical text annotations from five systems. Species and disease entity recognition showed better standardization than gene and protein recognition.

Area of Science:

  • Biomedical Natural Language Processing
  • Computational Linguistics
  • Bioinformatics

Background:

  • The CALBC initiative aims to create a large-scale biomedical text corpus with semantic annotations for named entities.
  • Harmonizing annotations from diverse automatic systems is crucial for corpus development.

Purpose of the Study:

  • To harmonize annotations from five participating systems (EMBL-EBI, EMC Rotterdam, NLM, JULIE Lab Jena, Linguamatics) into a unified corpus.
  • To evaluate the performance of different annotation systems against a common standard.

Main Methods:

  • Gathering annotations from five participants using a common format with concept identifiers.
  • Integrating diverse annotations into a "silver standard" corpus via a voting scheme.
  • Applying formal boundary reconciliation and semantic matching for named entity harmonization.

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Main Results:

  • A harmonized corpus was created using a voting scheme.
  • Species and disease annotations demonstrated higher standardization among partners compared to gene and protein annotations.
  • Participant submissions were evaluated against the silver standard corpus.

Conclusions:

  • The CALBC initiative successfully produced a harmonized biomedical corpus.
  • Annotation standardization varies across entity types, with species and diseases being more consistent.
  • The corpus is available for further annotation and will be used for a public challenge to advance corpus building.