Triple
T4601354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gurnee Mills |
E100324
|
entity |
| Predicate | hasZoningUse |
P37665
|
FINISHED |
| Object | commercial retail |
—
|
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: commercial retail | Statement: [Gurnee Mills, hasZoningUse, commercial retail]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasZoningUse Context triple: [Gurnee Mills, hasZoningUse, commercial retail]
-
A.
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.
-
B.
landUseIncludes
chosen
Indicates that a specified land area contains or permits the specified type(s) of land use within its boundaries.
-
C.
zoningCharacter
Indicates how the regulatory or functional nature of a geographic area is defined or classified in terms of land-use zoning.
-
D.
hasLandUseCharacter
Indicates that one entity possesses or is associated with a particular type or pattern of land use.
-
E.
hasZone
Indicates that one entity possesses, contains, or is associated with a specific zone or designated area.
- 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_69bd43cbc014819098b45f435908f88a |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd597346a08190b47eda3b73076f8b |
completed | March 20, 2026, 2:28 p.m. |
| PD | Predicate disambiguation | batch_69bd522c811c81909aae4feadae33174 |
completed | March 20, 2026, 1:57 p.m. |
Created at: March 20, 2026, 1:11 p.m.