Triple
T25594330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Windsor West |
E641605
|
entity |
| Predicate | borderingCityAcrossRiver |
P382
|
FINISHED |
| Object | Detroit, Michigan |
—
|
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: Detroit, Michigan | Statement: [Windsor West, borderingCityAcrossRiver, Detroit, Michigan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderingCityAcrossRiver Context triple: [Windsor West, borderingCityAcrossRiver, Detroit, Michigan]
-
A.
borderedByCountryAcrossRiver
Indicates that one country shares a border with another country, with the boundary specifically formed or separated by a river.
-
B.
locatedAcrossRiverFrom
chosen
Indicates that one entity is situated on the opposite side of a river relative to another entity.
-
C.
bordersAcrossRiver
Indicates that two regions or entities share a boundary with each other that is separated or defined by a river.
-
D.
nearbyCountryAcrossRiver
Indicates that one country is located close to another country with a river lying between them as a separating feature.
-
E.
oppositeTownAcrossBorder
Indicates that one town is located directly across a border from another town, positioned as its opposite counterpart.
- 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_69e75dc60d108190b7e2419e36b0134b |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f6640168948190811bd5f933a87cf5 |
completed | May 2, 2026, 8:52 p.m. |
| PD | Predicate disambiguation | batch_69f6633451948190bcc0410602bb4914 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 21, 2026, 4:26 p.m.