Triple
T989268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bay Lake, Florida |
E21349
|
entity |
| Predicate | hasVerySmallResidentPopulation |
P22797
|
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: [Bay Lake, Florida, hasVerySmallResidentPopulation, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVerySmallResidentPopulation Context triple: [Bay Lake, Florida, hasVerySmallResidentPopulation, true]
-
A.
reducedPopulationOf
Indicates a relationship where one entity has caused a decrease in the size or number of individuals in a population of another entity.
-
B.
hasPopulationApproximate
Indicates that an entity has an estimated or approximate population size, rather than an exact count.
-
C.
isLessPopulousThan
Indicates that one entity has a smaller population size than another entity.
-
D.
hasSmallBodyPopulation
Indicates that an entity has a relatively low number of small celestial bodies (such as asteroids, comets, or minor planets) associated with it.
-
E.
hasPopulationDensity
Indicates the number of individuals (e.g., people, organisms) per unit area associated with a given entity or region.
- F. None of above. chosen
Provenance (4 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_69a493c383dc8190a03257f22d4b4183 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4aa16f081909dcc7a7ce3fb1b64 |
completed | March 1, 2026, 9:50 p.m. |
| PD | Predicate disambiguation | batch_69a4b2abccbc8190a83af432f89eacf5 |
completed | March 1, 2026, 9:42 p.m. |
| PDg | Predicate description generation | batch_69a4b38630848190bd3898a4f42018ad |
completed | March 1, 2026, 9:45 p.m. |
Created at: March 1, 2026, 7:41 p.m.