Triple
T20127303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gibbstown, New Jersey |
E490791
|
entity |
| Predicate | hasPopulationAsOf2020Census |
P5555
|
FINISHED |
| Object | 3696 |
—
|
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: 3696 | Statement: [Gibbstown, New Jersey, hasPopulationAsOf2020Census, 3696]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPopulationAsOf2020Census Context triple: [Gibbstown, New Jersey, hasPopulationAsOf2020Census, 3696]
-
A.
hasPopulationAsOf
chosen
Indicates that a population count is associated with a specific point or date in time when that population figure was valid or recorded.
-
B.
staffPopulationApprox
Indicates an approximate or estimated number of staff associated with an entity.
-
C.
hasPopulationApproximate
Indicates that an entity has an estimated or approximate population size, rather than an exact count.
-
D.
populationCensus2021
Indicates that a population count or demographic data is recorded as part of the 2021 census.
-
E.
lastKnownPopulations
Indicates the most recently recorded population counts associated with an entity or set of entities.
- 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_69da62651a0c8190a3e05e95e056a66b |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e66743494c81908e63a5efca3aa3ea |
completed | April 20, 2026, 5:49 p.m. |
| PD | Predicate disambiguation | batch_69e54cfb0d0081908e789b9b57e96668 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 11:31 p.m.