Triple
T7540817
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marquette Township, Michigan |
E178268
|
entity |
| Predicate | hasRetailCorridorAlong |
P73526
|
FINISHED |
| Object | US Highway 41 |
—
|
NE NERFINISHED |
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: US Highway 41 | Statement: [Marquette Township, Michigan, hasRetailCorridorAlong, US Highway 41]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRetailCorridorAlong Context triple: [Marquette Township, Michigan, hasRetailCorridorAlong, US Highway 41]
-
A.
hasMajorRetailCorridor
Indicates that a place contains or is associated with a primary commercial street or area characterized by a high concentration of retail businesses.
-
B.
roadCorridorIncludes
chosen
Indicates that a specified road corridor spatially contains or encompasses another element or segment within its defined bounds.
-
C.
hasShoppingDistrictName
Indicates that an entity’s shopping district is identified by a specific name.
-
D.
hasRetailPresenceIn
Indicates that an entity conducts retail operations or maintains a retail outlet, store, or sales presence within a specified location.
-
E.
hasRetailArea
Indicates that an entity possesses or includes a designated space used for retail or commercial sales activities.
- 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_69c69f2be3888190a6667a27f8f195e9 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f873b17081908bb70aea0010d072 |
completed | March 27, 2026, 9:36 p.m. |
| PD | Predicate disambiguation | batch_69c6f4d8eedc81908c1ae421e0e63798 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:48 p.m.