Triple
T1024273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Interstate 90 |
E22104
|
entity |
| Predicate | hasRouteNumberingType |
P13326
|
FINISHED |
| Object | primary Interstate |
—
|
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: primary Interstate | Statement: [Interstate 90, hasRouteNumberingType, primary Interstate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRouteNumberingType Context triple: [Interstate 90, hasRouteNumberingType, primary Interstate]
-
A.
hasJunctionNumbering
Indicates that a road or route is assigned a specific numbering system for its junctions or intersections.
-
B.
hasRouteType
chosen
Indicates that there is a specific kind or category of route associated with an entity (e.g., road, rail, bus line).
-
C.
routeNumberFormat
Indicates how the identifying number or code for a route is structured or formatted.
-
D.
routeNumber
Indicates the specific identifying number assigned to a route within a transportation or delivery network.
-
E.
hasRouteColorStandard
Indicates that a route is associated with a standardized color designation used for identification or classification.
- 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_69a493d6e380819097b384986ffc315c |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b7e28df08190b5be7794442a6f21 |
completed | March 1, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69a4b72619cc8190932fdfa0c74dc055 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:41 p.m.