Triple
T161765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. George campus |
E3302
|
entity |
| Predicate | neighborhood |
P988
|
FINISHED |
| Object | Downtown Toronto |
E18465
|
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: Downtown Toronto | Statement: [St. George campus, neighborhood, Downtown Toronto]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Downtown Toronto Context triple: [St. George campus, neighborhood, Downtown Toronto]
-
A.
Downtown Toronto
chosen
Downtown Toronto is the city’s primary central business district and cultural core, known for its dense skyline, major attractions, and vibrant urban life.
-
B.
Toronto
Toronto is the largest city in Canada and a major cultural, financial, and media hub located in the province of Ontario.
-
C.
Greater Toronto Area
The Greater Toronto Area is a large metropolitan region in Ontario, Canada, encompassing Toronto and its surrounding municipalities and suburbs.
-
D.
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.
-
E.
London, Ontario
London, Ontario is a mid-sized Canadian city in southwestern Ontario known for its educational institutions, healthcare sector, and role as a regional economic and cultural hub.
- 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_69a2527757ec819090b8becb2cf1a862 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a2585877648190a2ec320182a69343 |
completed | Feb. 28, 2026, 2:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a352734730819091211462a23204ea |
completed | Feb. 28, 2026, 8:39 p.m. |
Created at: Feb. 28, 2026, 2:31 a.m.