Triple
T5645579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Etobicoke Creek |
E124376
|
entity |
| Predicate | flowsFrom |
P17870
|
FINISHED |
| Object | Caledon |
E137006
|
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: Caledon | Statement: [Etobicoke Creek, flowsFrom, Caledon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Caledon Context triple: [Etobicoke Creek, flowsFrom, Caledon]
-
A.
Caledon
chosen
Caledon is a largely rural town in southern Ontario, Canada, known for its scenic landscapes and inclusion within the Greater Toronto Area.
-
B.
Etobicoke
Etobicoke is a large suburban district in the western part of Toronto, Ontario, known for its residential neighborhoods, parks, and industrial areas along the waterfront.
-
C.
Welland
Welland is a city in the Niagara Region of southern Ontario, Canada, known for the Welland Canal that connects Lake Ontario and Lake Erie.
-
D.
Willowdale
Willowdale is a large, diverse residential and commercial neighbourhood in the North York district of Toronto, Ontario, known for its high-rise condos, shopping centres, and cultural amenities.
-
E.
Vaughan
Vaughan is a rapidly growing suburban city in the Greater Toronto Area known for its diverse communities, shopping and entertainment complexes, and attractions like Canada’s Wonderland.
- 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_69c00824643c81909ffdb888a2d35189 |
completed | March 22, 2026, 3:17 p.m. |
| NER | Named-entity recognition | batch_69c022aa650c819088d9046b82fab631 |
completed | March 22, 2026, 5:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c107bf6994819089e1211ffe343094 |
completed | March 23, 2026, 9:28 a.m. |
Created at: March 22, 2026, 3:41 p.m.