Triple
T8051863
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OS Landranger |
E187691
|
entity |
| Predicate | hasScaleDenominator |
P62522
|
FINISHED |
| Object | 50000 |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: 50000 | Statement: [OS Landranger, hasScaleDenominator, 50000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasScaleDenominator Context triple: [OS Landranger, hasScaleDenominator, 50000]
-
A.
hasScale
Indicates that one entity possesses or is characterized by a scale or graduated measurement system related to another entity.
-
B.
hasScaleHeight
Indicates the characteristic vertical distance over which a quantity (such as pressure, density, or concentration) decreases by a fixed factor in a stratified medium.
-
C.
hasScales
Indicates that an entity possesses scales as a surface covering or body feature.
-
D.
hasApproximateDistanceScale
Indicates that one entity is related to another by a distance measure that is approximate or estimated rather than exact.
-
E.
mapScale
chosen
Indicates the ratio between distances on a map and the corresponding actual distances in the real world.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca82b15e948190a62fd7af5218426a |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3f7aab6481909d4a7cb9eabcd2af |
completed | March 31, 2026, 3:28 a.m. |
| PD | Predicate disambiguation | batch_69cb049a1b9c8190811c396421ebf9c9 |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:24 p.m.