Triple
T16228280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hays μSA |
E393911
|
entity |
| Predicate | hasUrbanCoreType |
P40854
|
FINISHED |
| Object | micropolitan core |
—
|
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: micropolitan core | Statement: [Hays μSA, hasUrbanCoreType, micropolitan core]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUrbanCoreType Context triple: [Hays μSA, hasUrbanCoreType, micropolitan core]
-
A.
hasUrbanModel
Indicates that an entity is associated with or characterized by a specific urban planning or city-scale representation model.
-
B.
hasUrbanLayoutType
Indicates that an entity possesses or is characterized by a specific type or pattern of urban spatial layout.
-
C.
hasUrbanFeature
Indicates that a place or area possesses a specific urban element or infrastructure feature (such as roads, parks, or buildings) as part of its built environment.
-
D.
hasUrbanClassification
chosen
Indicates that an entity is assigned a specific urban status or category within a defined classification system.
-
E.
hasUrbanFunction
Indicates that an entity serves a specific role or purpose within an urban context, such as providing services, infrastructure, or activities typical of a city environment.
- 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_69d87f204df88190a8f88923decf9835 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e23d2785f88190ae80d5d61129d3e5 |
completed | April 17, 2026, 2:01 p.m. |
| PD | Predicate disambiguation | batch_69e219e94a448190b73a4e6aa374eb4a |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:03 a.m.