Triple
T2758077
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | York University station |
E61152
|
entity |
| Predicate | district |
P2709
|
FINISHED |
| Object | North York |
E102952
|
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: North York | Statement: [York University station, district, North York]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: North York Context triple: [York University station, district, North York]
-
A.
North York
chosen
North York is a major district in the north end of Toronto, Ontario, known for its dense urban development, shopping centers, and mixed residential and commercial areas.
-
B.
Brampton
Brampton is a large suburban city in the Greater Toronto Area known for its diverse population and rapidly growing economy.
-
C.
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.
-
D.
Vaughan
Vaughan is a surname of Welsh origin that is notably associated with influential figures such as blues guitarist Stevie Ray Vaughan.
-
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_69ab4b7a85bc819094a349b84beb1f2c |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdb8ba4688190b401b6eb5b734ac6 |
completed | March 7, 2026, 8:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b08633e4108190a783b29a10efcc76 |
completed | March 10, 2026, 8:59 p.m. |
Created at: March 6, 2026, 9:57 p.m.