Triple
T2832139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northfield, Minnesota |
E62262
|
entity |
| Predicate | hasDowntownFeature |
P1495
|
FINISHED |
| Object | historic commercial district |
—
|
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: historic commercial district | Statement: [Northfield, Minnesota, hasDowntownFeature, historic commercial district]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDowntownFeature Context triple: [Northfield, Minnesota, hasDowntownFeature, historic commercial district]
-
A.
hasDowntown
Indicates that a place or city possesses a central downtown area.
-
B.
isDowntownAxis
Indicates that something serves as or lies along the main central axis of a downtown area.
-
C.
isDowntownCoreOf
Indicates that a location constitutes the central, most urbanized and commercially dense area of a larger city or metropolitan region.
-
D.
hasUrbanFeature
chosen
Indicates that a place or area possesses a specific urban element or infrastructure feature (such as roads, parks, or buildings) as part of its built environment.
-
E.
nearDowntown
Indicates that one location is situated close to or within a short distance of a city’s downtown 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_69ab4c3c39188190955b9c49d98463d8 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdebe95188190bf65fb4cd88e2ec5 |
completed | March 7, 2026, 8:15 a.m. |
| PD | Predicate disambiguation | batch_69abdd0acab881909e8c25cbef83678c |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 10:01 p.m.