Triple
T2565990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East Brunswick Township |
E57351
|
entity |
| Predicate | populationCensus1990 |
P292
|
FINISHED |
| Object | 43000 |
—
|
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: 43000 | Statement: [East Brunswick Township, populationCensus1990, 43000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: populationCensus1990 Context triple: [East Brunswick Township, populationCensus1990, 43000]
-
A.
statusIn1990
Indicates the status or condition that an entity had specifically in the year 1990.
-
B.
populationCensus2021
Indicates that a population count or demographic data is recorded as part of the 2021 census.
-
C.
populationCensusYear
chosen
Indicates the specific year in which an official population census was conducted or recorded for an entity.
-
D.
hasPopulationAsOf
Indicates that a population count is associated with a specific point or date in time when that population figure was valid or recorded.
-
E.
population
Indicates the total number of individuals living in or present within a specified area or group.
- 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_69ab4a4ef9008190a0e6d4422b9418b7 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd35ef22c8190966612cc75f69eca |
completed | March 7, 2026, 7:27 a.m. |
| PD | Predicate disambiguation | batch_69abd0cc8d308190ae7aa32b8f5ae2e5 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:48 p.m.