Triple
T12879732
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GR footpath network |
E308058
|
entity |
| Predicate | trailNumberingScheme |
P47176
|
FINISHED |
| Object | GR followed by a number |
—
|
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: GR followed by a number | Statement: [GR footpath network, trailNumberingScheme, GR followed by a number]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trailNumberingScheme Context triple: [GR footpath network, trailNumberingScheme, GR followed by a number]
-
A.
trailNumber
Indicates that an entity is associated with a specific trail identifier or route number within a trail system.
-
B.
hasRouteNumberingScheme
chosen
Indicates that one entity uses or is assigned a particular system or scheme for numbering its routes.
-
C.
routeNumberingAuthority
Indicates the authority or organization responsible for assigning and managing the official number designation of a route.
-
D.
hasJunctionNumberingScheme
Indicates the specific system or method used to assign numbers to junctions within a network (such as roads or railways).
-
E.
hasRailwayStationNumberingSystem
Indicates that a railway station is associated with a specific system for assigning it an identifying number or code.
- 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_69d7bdf69bc48190af6c2621f28ca351 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97c7f91d08190aac2f6419d3ba992 |
completed | April 10, 2026, 10:41 p.m. |
| PD | Predicate disambiguation | batch_69d96fa55b888190ab1612e93c41aec4 |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:39 p.m.