Sign inGet started
Paper · arXiv

Consensus Measures for Unstructured Biomedical Text Annotations

Biomedical literature is increasingly mined for knowledge beyond the questions it was written to answer. Because the target concepts are not known in advance, annotators prefer open-ended labels, whose agreement is hard to quantify. We study soft inter-rater reliability for annotators providing unstructured texts for biomedical annotation tasks. Synthetic experiments show that soft reliability can be quantified using a variety of semantic equivalence measures, and that the choice of measure affects failure modes of the estimation. Embeddings are scalable, but limited when differentiating similar but distinct concepts. Large language models are promising, but limited by scalability for est...

AuthorsPascal Wullschleger, Christian Kreis, Martin A. Walter et al.
Primary categorycs.CL
Published4 August 2026
Last updated at source5 August 2026
cs.CL
Embed this entry
<iframe src="https://silytics.si/embed/item/a3a22f86-27d6-498b-83e2-b66ce540ff19" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Free, no tracking. More about feeds and embeds.

Silytics shows public metadata from arXiv and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.