Triple
T4601326
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gurnee Mills |
E100324
|
entity |
| Predicate | hasNumberOfAnchorStores |
P8902
|
FINISHED |
| Object | 15+ |
—
|
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: 15+ | Statement: [Gurnee Mills, hasNumberOfAnchorStores, 15+]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfAnchorStores Context triple: [Gurnee Mills, hasNumberOfAnchorStores, 15+]
-
A.
numberOfStores
chosen
Indicates the total count of stores associated with a given entity or context.
-
B.
numberOfFloorsInAnchorStores
Indicates the relationship specifying how many floors are contained within each anchor store.
-
C.
hasRetailPresenceIn
Indicates that an entity conducts retail operations or maintains a retail outlet, store, or sales presence within a specified location.
-
D.
hasShopsOn
Indicates that one entity (typically a street, area, or building) contains or is lined with shops located on or along it.
-
E.
hasRetailBoutiquesIn
Indicates that an entity operates or maintains retail boutiques located within a specified place or region.
- 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.