Triple
T14206133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Britain A and B road numbering scheme |
E352098
|
entity |
| Predicate | zoneBoundaryRoad |
P24205
|
FINISHED |
| Object | A1 |
—
|
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: A1 | Statement: [Great Britain A and B road numbering scheme, zoneBoundaryRoad, A1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: zoneBoundaryRoad Context triple: [Great Britain A and B road numbering scheme, zoneBoundaryRoad, A1]
-
A.
hasRoadBoundary
Indicates that a road segment is associated with a specific boundary or edge that defines its lateral limits.
-
B.
fareBoundaryBetween
Indicates that there is a dividing line or zone where one fare region, zone, or pricing scheme ends and another begins.
-
C.
rangeOnRoad
Indicates that something extends or is distributed along the length of a road.
-
D.
boundaryName
Indicates the designated name or label assigned to a specific boundary or border between entities.
-
E.
roadNumberingZone
chosen
Indicates the designated numbering zone or area within which a particular road’s identification or route number is assigned.
- 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_69d827894ac0819097803e57f3227b23 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61f84f288190877116330bd54393 |
completed | April 14, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69de05bcd7d48190a4848d9320404aa6 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 1:05 a.m.