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. 2005;6 Suppl 1(Suppl 1):S3.
doi: 10.1186/1471-2105-6-S1-S3. Epub 2005 May 24.

GENETAG: a tagged corpus for gene/protein named entity recognition

Affiliations

GENETAG: a tagged corpus for gene/protein named entity recognition

Lorraine Tanabe et al. BMC Bioinformatics. 2005.

Abstract

Background: Named entity recognition (NER) is an important first step for text mining the biomedical literature. Evaluating the performance of biomedical NER systems is impossible without a standardized test corpus. The annotation of such a corpus for gene/protein name NER is a difficult process due to the complexity of gene/protein names. We describe the construction and annotation of GENETAG, a corpus of 20K MEDLINE sentences for gene/protein NER. 15K GENETAG sentences were used for the BioCreAtIvE Task 1A Competition.

Results: To ensure heterogeneity of the corpus, MEDLINE sentences were first scored for term similarity to documents with known gene names, and 10K high- and 10K low-scoring sentences were chosen at random. The original 20K sentences were run through a gene/protein name tagger, and the results were modified manually to reflect a wide definition of gene/protein names subject to a specificity constraint, a rule that required the tagged entities to refer to specific entities. Each sentence in GENETAG was annotated with acceptable alternatives to the gene/protein names it contained, allowing for partial matching with semantic constraints. Semantic constraints are rules requiring the tagged entity to contain its true meaning in the sentence context. Application of these constraints results in a more meaningful measure of the performance of an NER system than unrestricted partial matching.

Conclusion: The annotation of GENETAG required intricate manual judgments by annotators which hindered tagging consistency. The data were pre-segmented into words, to provide indices supporting comparison of system responses to the "gold standard". However, character-based indices would have been more robust than word-based indices. GENETAG Train, Test and Round1 data and ancillary programs are freely available at ftp://ftp.ncbi.nlm.nih.gov/pub/tanabe/GENETAG.tar.gz. A newer version of GENETAG-05, will be released later this year.

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Figures

Figure 1
Figure 1
GENETAG Annotation Method. The annotator selects the boxes under each word in a gene/protein name and presses the "Mark" button. The resulting name is highlighted in yellow, and the marked fragments are shown in the bottom left frame. The annotator selects allowable alternatives from this list and presses "Save". Alternatives beyond the scope of the original highlighted name are input manually (along with their indices) into the text entry box. The lower right frame shows all the alternatives to the original name, along with their indices and the sentence number. A link to the abstract is provided for contextual clues.

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