Validation Data for Organization Name Recognition from PubMed Affiliations

This dataset was analyzed in a validation study for a two-stage registry-anchored approach to improve precision in recognizing organization names from PubMed affiliation strings. The dataset was created by author Inmo Kang from Science Editing. The specific row count, column count, and temporal coverage are unknown.

Use Cases

• Validate a named entity recognition model for extracting organization names from PubMed affiliation strings.
• Benchmark the precision of a two-stage registry-anchored approach for affiliation parsing.
• Analyze patterns in affiliation string formatting to inform text normalization rules.

Strengths

• Dataset is associated with a formal validation study published in Science Editing.
• The methodology is explicitly described as a two-stage registry-anchored approach for precision improvement.

Limitations

• The dataset's size, structure, and specific features are not described, preventing assessment of its scale and utility.
• Without column names or sample data, the exact data fields and their format are unknown.

Provenance

Source

Author Inmo Kang, associated with Science Editing.

Collection Method

Derived from PubMed affiliation strings using a two-stage registry-anchored approach.

Freshness

The record was last updated on 2026-02-05.