A Gazetteer and Georeferencing for Historical English Documents
Bibliographic record
Abstract
We report on a newly available gazetteer of historical English place-names and de-scribe how it was created from a re-cent digitisation of the Survey of En-glish Place-Names, published by the En-glish Place-Name Society (EPNS). The gazetteer resource is accessible via a num-ber of routes, not currently as linked data but in formats that do provide connections between a number of different datasets. In particular, connections between the histor-ical gazetteer and the Unlock1 and GeoN-ames2 gazetteer services have been es-tablished along with links to the Key to English Place-Names database3. The gazetteer is available via the Unlock API and in the final part of the paper we describe how the Edinburgh Geoparser, which forms the basis of Unlock Text, has been adapted to allow users to georefer-ence historical texts. 1
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.011 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.097 | 0.042 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".