Triple
T11946959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miracle Mile (Coral Gables) |
E284321
|
entity |
| Predicate | nameUses |
P42471
|
FINISHED |
| Object | promotional branding for the district |
—
|
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: promotional branding for the district | Statement: [Miracle Mile (Coral Gables), nameUses, promotional branding for the district]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nameUses Context triple: [Miracle Mile (Coral Gables), nameUses, promotional branding for the district]
-
A.
oftenUsedAsNameFor
Indicates that something frequently serves as a name or designation for another entity.
-
B.
nameUsedIn
Indicates that a particular name is employed or referenced within a specified context, work, or usage setting.
-
C.
nameUsedFor
chosen
Indicates that a particular name is used to refer to or designate a given entity.
-
D.
usesNameDueTo
Indicates that one entity adopts or applies a particular name for another entity specifically because of some motivating reason, circumstance, or dependency.
-
E.
designationUse
Indicates how a particular designation or title is intended to be used or applied in relation to an entity.
- 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_69d6ab2db38c8190b1f0ed6663ef8ada |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903456ec0819082b8b10755a6b732 |
completed | April 10, 2026, 2:03 p.m. |
| PD | Predicate disambiguation | batch_69d8bb3e48e08190b2fee43af4f57323 |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:45 p.m.