Triple
T21158670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Collège Boréal |
E521377
|
entity |
| Predicate | hasCampusIn |
P4623
|
FINISHED |
| Object | Sudbury, 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: Sudbury, Ontario | Statement: [Collège Boréal, hasCampusIn, Sudbury, Ontario]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sudbury, Ontario Context triple: [Collège Boréal, hasCampusIn, Sudbury, Ontario]
-
A.
Sudbury
Sudbury is a suburban area in northwest London, England, known for its residential character and proximity to Wembley.
-
B.
Sudbury
Sudbury is a historic market town in Suffolk, England, known for its medieval architecture and association with painter Thomas Gainsborough.
-
C.
Sudbury
Sudbury is a small rural town in Rutland County, Vermont, known for its scenic landscapes and quiet, agricultural character.
-
D.
Sudbury
chosen
Sudbury is a major city in northern Ontario, Canada, known for its mining industry and numerous surrounding lakes.
-
E.
Sutton, Ontario
Sutton, Ontario is a community within the town of Georgina on the southern shore of Lake Simcoe in Ontario, Canada, known as a local service and commercial hub for nearby lakeside and cottage areas.
- 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.