Datasets:
| cff-version: 1.2.0 | |
| message: "If you use this test set, please cite it as below." | |
| title: "Perch trap set: 70 clips that catch AI scribes inventing drug names" | |
| version: 1.0.0 | |
| date-released: "2026-10-02" | |
| authors: | |
| - name: "Talcoe LLC" | |
| type: dataset | |
| doi: "10.5281/zenodo.23113470" | |
| identifiers: | |
| - type: doi | |
| value: "10.5281/zenodo.23113470" | |
| description: "Version 1.0.0" | |
| - type: doi | |
| value: "10.5281/zenodo.23113469" | |
| description: "Every version" | |
| - type: url | |
| value: "https://huggingface.co/datasets/Talcoe/perch-trapset" | |
| description: "Hugging Face mirror" | |
| license: "CC-BY-4.0" | |
| repository-code: "https://github.com/perchvet/perch-trapset" | |
| abstract: >- | |
| A 70-clip blind test set (45 dictations, 25 traps) for checking whether an AI clinical | |
| scribe charts a medication that was never dictated. Clips are synthetic text to speech | |
| audio built from veterinary dictations written by an author who never saw the matching | |
| code. Ships with a generic Node scorer, a corpus file with ground truth per clip, and a | |
| full ledger of results from Talcoe LLC's own product, Perch, and one outside comparison | |
| run. | |
| keywords: | |
| - veterinary | |
| - clinical scribe | |
| - speech recognition | |
| - hallucination | |
| - benchmark | |
| - AI safety | |