Triple
T37635597
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bar Nunn, Wyoming |
E936479
|
entity |
| Predicate | streetLayoutFollows |
P173463
|
FINISHED |
| Object | old runways |
—
|
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: old runways | Statement: [Bar Nunn, Wyoming, streetLayoutFollows, old runways]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: streetLayoutFollows Context triple: [Bar Nunn, Wyoming, streetLayoutFollows, old runways]
-
A.
streetLayoutRole
Indicates the specific functional role an element plays within the overall layout or organization of a street.
-
B.
streetPlanBy
Indicates that a street or road layout was designed, organized, or planned by a particular agent or authority.
-
C.
streetOrientedAlong
Indicates that a street is aligned or runs in the same general direction as a specified reference feature or axis.
-
D.
urbanLayout
Indicates how the spatial arrangement, organization, and structure of buildings, streets, and public spaces relate to one another within an urban area.
-
E.
streetPatternFocusedOn
chosen
Indicates a relationship where a street pattern is organized, oriented, or designed with primary emphasis on a particular feature, area, or organizing element.
- 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_69f76ed31d8881908405da6c6d2f0463 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbaa1321b48190af92a3e7ec24ec5b |
completed | May 6, 2026, 8:52 p.m. |
| PD | Predicate disambiguation | batch_69fba8860f98819080b7bab05837b974 |
completed | May 6, 2026, 8:45 p.m. |
Created at: May 3, 2026, 4:18 p.m.