Triple
T7548789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brampton Transit |
E178474
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Brampton, Ontario |
E30924
|
NE 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: Brampton, Ontario | Statement: [Brampton Transit, locatedIn, Brampton, Ontario]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brampton, Ontario Context triple: [Brampton Transit, locatedIn, Brampton, Ontario]
-
A.
Brampton
chosen
Brampton is a large suburban city in the Greater Toronto Area known for its diverse population and rapidly growing economy.
-
B.
Brampton
Brampton is a market town in Cumbria, England, known for its historic architecture and proximity to Hadrian’s Wall.
-
C.
Tillsonburg, Ontario
Tillsonburg, Ontario is a small town in southwestern Ontario known historically for its tobacco farming and agricultural roots.
-
D.
Mississauga, Ontario, Canada
Mississauga, Ontario, Canada is a large suburban city west of Toronto known for its diverse population, major corporate headquarters, and proximity to Toronto Pearson International Airport.
-
E.
Oakville, Ontario
Oakville, Ontario is a suburban town on Lake Ontario in the Greater Toronto Area, known for its affluent neighborhoods, harbors, and vibrant arts and cultural scene.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c69f2cbe08819088f9eb0c03ef529b |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f89b9afc8190b3e61a8e2cea7ad7 |
completed | March 27, 2026, 9:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c9162980708190be2a347b2322c09c |
completed | March 29, 2026, 12:08 p.m. |
Created at: March 27, 2026, 3:49 p.m.