Triple
T8477494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East Gwillimbury, Ontario |
E200432
|
entity |
| Predicate | hasUrbanCentres |
P11388
|
FINISHED |
| Object | true |
—
|
LITERAL 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: true | Statement: [East Gwillimbury, Ontario, hasUrbanCentres, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUrbanCentres Context triple: [East Gwillimbury, Ontario, hasUrbanCentres, true]
-
A.
isUrbanCentreFor
Indicates that one place functions as the primary urban hub or central city serving another area or population.
-
B.
isUrbanCenter
Indicates that a place functions as a primary, densely developed hub of population, services, and activities within a region.
-
C.
hasUrbanDistrictCount
Indicates the number of urban districts associated with a given entity.
-
D.
coversUrbanAreas
Indicates that something extends over, includes, or provides coverage for urban or metropolitan areas.
-
E.
containsUrbanArea
chosen
Indicates that a geographic region fully or partially encompasses an urbanized area within its boundaries.
- 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_69ca831b17988190a1f3f3413d57b820 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe51ffab881908448aff899511f2c |
completed | March 31, 2026, 3:15 p.m. |
| PD | Predicate disambiguation | batch_69cbd104250c8190b4c499dcc9937494 |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:12 p.m.