Triple
T11946946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miracle Mile (Coral Gables) |
E284321
|
entity |
| Predicate | typicalBusinessTypes |
P68868
|
FINISHED |
| Object | fashion boutiques |
—
|
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: fashion boutiques | Statement: [Miracle Mile (Coral Gables), typicalBusinessTypes, fashion boutiques]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalBusinessTypes Context triple: [Miracle Mile (Coral Gables), typicalBusinessTypes, fashion boutiques]
-
A.
eligibleBusinessType
Indicates that a business entity qualifies under specified criteria to be considered an eligible type for a particular program, rule, or context.
-
B.
notableBusinessType
Indicates that an entity is notably associated with, characterized by, or best known for a particular type of business.
-
C.
hasTypeOfBusinesses
chosen
Indicates that an entity is associated with or contains specific categories or kinds of businesses.
-
D.
typicalEmployer
Indicates that one entity is the kind of organization or person that commonly or usually employs the other entity.
-
E.
businessBase
Indicates that one entity serves as the primary business foundation, core location, or main operational base for another 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.