Triple
T27460511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Windsor–Detroit border |
E692724
|
entity |
| Predicate | separatesCity |
P1175
|
FINISHED |
| Object | Windsor, Ontario |
—
|
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: Windsor, Ontario | Statement: [Windsor–Detroit border, separatesCity, Windsor, Ontario]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: separatesCity Context triple: [Windsor–Detroit border, separatesCity, Windsor, Ontario]
-
A.
separatesMajorCities
Indicates that a geographic or political boundary lies between and divides two or more major cities from each other.
-
B.
riverSeparatingCity
Indicates that a river runs between and divides parts of a city or separates one city from another.
-
C.
separatesState
Indicates that one entity serves as a dividing boundary or barrier between two distinct states or regions.
-
D.
separates
chosen
Indicates that one entity divides, parts, or keeps other entities apart from each other.
-
E.
city2
Indicates a relationship where one entity is identified as a city associated with, located in, or otherwise linked to another entity.
- 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_69ef5207903881909427745cda05d27a |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69f64dbbaefc8190952b8320bf4397d8 |
completed | May 2, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69f64cacd2c08190aed8a1761d0da679 |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 27, 2026, 12:50 p.m.