Triple
T21158678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Collège Boréal |
E521377
|
entity |
| Predicate | hasCampusIn |
P4623
|
FINISHED |
| Object | Welland, 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: Welland, Ontario | Statement: [Collège Boréal, hasCampusIn, Welland, Ontario]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Welland, Ontario Context triple: [Collège Boréal, hasCampusIn, Welland, Ontario]
-
A.
Welland
chosen
Welland is a city in the Niagara Region of southern Ontario, Canada, known for the Welland Canal that connects Lake Ontario and Lake Erie.
-
B.
Welland
Welland is a small rural village in Worcestershire, England, known for its scenic setting near the Malvern Hills.
-
C.
Waterford, Ontario
Waterford, Ontario is a small rural community in Norfolk County known for its agricultural surroundings, historic charm, and annual Pumpkinfest celebration.
-
D.
Wawa, Ontario
Wawa, Ontario is a small town in northern Ontario, Canada, known for its proximity to Lake Superior and its iconic giant Canada goose statue.
-
E.
Atwood, Ontario
Atwood, Ontario is a small rural community in Perth County, Canada, known for its agricultural surroundings and close-knit local character.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b50d1ea481909c07e63c3ead9316 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7252e9ef481908f4904c535f3da8b |
completed | April 21, 2026, 7:20 a.m. |
Created at: April 16, 2026, 2:59 p.m.