Triple
T32044073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hilltop, Minnesota |
E818290
|
entity |
| Predicate | hasNoSignificantCommercialDistrict |
P107875
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Hilltop, Minnesota, hasNoSignificantCommercialDistrict, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNoSignificantCommercialDistrict Context triple: [Hilltop, Minnesota, hasNoSignificantCommercialDistrict, true]
-
A.
hasNoCommercialZone
chosen
Indicates that the subject area or entity does not contain any designated commercial zone or commercial-use area.
-
B.
hasCommercialCenterType
Indicates that an entity has or is associated with a specific type or category of commercial center (e.g., mall, shopping district, business park).
-
C.
hasBusinessDistrict
Indicates that a place or administrative area contains or includes a designated business district within its boundaries.
-
D.
containsCommercialArea
Indicates that one entity includes within its boundaries a designated area used for commercial activities or businesses.
-
E.
hasShoppingDistrict
Indicates that a place contains or is associated with a designated area where multiple shops and commercial retail activities are concentrated.
- 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_69f348fcfb648190859f6be5e04b7cfe |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a00d76d0e0881908d83a8dcce511167 |
completed | May 10, 2026, 7:07 p.m. |
| PD | Predicate disambiguation | batch_6a00d711805881909a94cfd1f25fb331 |
completed | May 10, 2026, 7:05 p.m. |
Created at: May 1, 2026, 12:19 a.m.