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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

Summary

The CALBC initiative harmonized biomedical text annotations from five systems. Species and disease entity recognition showed better standardization than gene and protein recognition.

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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.