Triple
T22060118
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East Williston, New York |
E545127
|
entity |
| Predicate | hasLocalZoning |
P66359
|
FINISHED |
| Object | residential zoning predominance |
—
|
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: residential zoning predominance | Statement: [East Williston, New York, hasLocalZoning, residential zoning predominance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLocalZoning Context triple: [East Williston, New York, hasLocalZoning, residential zoning predominance]
-
A.
usesZoning
Indicates that one entity applies or relies on a zoning scheme, classification, or regulations established or provided by another entity.
-
B.
hasZone
Indicates that one entity possesses, contains, or is associated with a specific zone or designated area.
-
C.
hasZoningPolicy
Indicates that a governing body or authority has established or adopted a specific zoning policy that regulates land use or development within its jurisdiction.
-
D.
hasZoningApproach
chosen
Indicates the type or method of zoning policy or strategy that is applied to or associated with an entity.
-
E.
hasZoneStructure
Indicates that an entity possesses a defined internal division into zones or regions, each forming part of its overall structure.
- 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_69e11e3377c48190890c17407b9527d6 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1285ba1c88190b4bc0c73f3cf04e1 |
completed | April 28, 2026, 9:36 p.m. |
| PD | Predicate disambiguation | batch_69e6f643ca74819083e8ab78e843f243 |
completed | April 21, 2026, 4 a.m. |
Created at: April 16, 2026, 8:27 p.m.