Triple
T28035606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A6 |
E708396
|
entity |
| Predicate | hasRoadNumberingScheme |
P99654
|
FINISHED |
| Object | Great Britain A and B road numbering scheme |
—
|
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: Great Britain A and B road numbering scheme | Statement: [A6, hasRoadNumberingScheme, Great Britain A and B road numbering scheme]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRoadNumberingScheme Context triple: [A6, hasRoadNumberingScheme, Great Britain A and B road numbering scheme]
-
A.
hasRoadNumberSystem
chosen
Indicates that a place or region uses a specific system for assigning numbers to its roads or highways.
-
B.
hasRouteNumberingScheme
Indicates that one entity uses or is assigned a particular system or scheme for numbering its routes.
-
C.
hasJunctionNumberingScheme
Indicates the specific system or method used to assign numbers to junctions within a network (such as roads or railways).
-
D.
hasStreetNumberingSystem
Indicates that a location or area uses an organized system for assigning numbers to buildings or addresses along its streets.
-
E.
hasJunctionNumbering
Indicates that a road or route is assigned a specific numbering system for its junctions or intersections.
- 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_69ef9b6bdd9c8190bb3a574a03774ad1 |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69f7431c0eec81909ead443e07d75e18 |
completed | May 3, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69f74143cf708190a12d487884298437 |
completed | May 3, 2026, 12:36 p.m. |
Created at: April 27, 2026, 8:20 p.m.