Triple
T2500897
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Broward County, Florida |
E52460
|
entity |
| Predicate | hasDiversePopulation |
P38709
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Broward County, Florida, hasDiversePopulation, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDiversePopulation Context triple: [Broward County, Florida, hasDiversePopulation, true]
-
A.
hasSignificantPopulationGroup
Indicates that an entity contains or is associated with a notable or substantial subgroup of a population, distinguished by shared characteristics or attributes.
-
B.
hasMinorityIn
Indicates that one entity holds a non-controlling, minority ownership or stake in another entity.
-
C.
historicalDiversity
Indicates that there has been variation or change in the composition, characteristics, or representation of something across different historical periods.
-
D.
numberOfEthnicGroupsRepresented
Indicates the count of distinct ethnic groups that are present or represented in a given context or entity.
-
E.
isMulticulturalCity
chosen
Indicates that a city is characterized by the presence and interaction of multiple cultural, ethnic, or linguistic communities.
- 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_69ab4957b3a88190adf968ae0c1b931c |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd1b144a481909b1f8d96742a92e7 |
completed | March 7, 2026, 7:20 a.m. |
| PD | Predicate disambiguation | batch_69abd0bba5348190bb4637d3165cb339 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:46 p.m.