Triple
T22182251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OSGB grid |
E548197
|
entity |
| Predicate | mapScaleCompatibility |
P63248
|
FINISHED |
| Object | large-scale mapping |
—
|
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: large-scale mapping | Statement: [OSGB grid, mapScaleCompatibility, large-scale mapping]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mapScaleCompatibility Context triple: [OSGB grid, mapScaleCompatibility, large-scale mapping]
-
A.
mapScale
Indicates the ratio between distances on a map and the corresponding actual distances in the real world.
-
B.
mapScaleCategory
chosen
Indicates the classification of a map based on its scale range or level of detail.
-
C.
distanceScaleUse
Indicates that one entity uses or applies the distance scale defined or provided by another entity.
-
D.
coversScale
Indicates that one entity spans, includes, or applies across the full range or extent of another entity’s scale.
-
E.
areaScale
Indicates a proportional relationship where one area value is a scaled (enlarged or reduced) version of another by a specific factor.
- 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_69e11e3d53f88190a2b690e3f25bb062 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12aa5998081909ff35f8b5df4f92f |
completed | April 28, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69e71b48576c8190a8e93738fd9cfda5 |
completed | April 21, 2026, 6:38 a.m. |
Created at: April 16, 2026, 8:35 p.m.