Triple
T239077
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Billy Bishop Toronto City Airport |
E4887
|
entity |
| Predicate | servesRegion |
P82
|
FINISHED |
| Object | Greater Toronto Area |
E18214
|
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: Greater Toronto Area | Statement: [Billy Bishop Toronto City Airport, servesRegion, Greater Toronto Area]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Greater Toronto Area Context triple: [Billy Bishop Toronto City Airport, servesRegion, Greater Toronto Area]
-
A.
Greater Toronto Area
chosen
The Greater Toronto Area is a large metropolitan region in Ontario, Canada, encompassing Toronto and its surrounding municipalities and suburbs.
-
B.
Downtown Toronto
Downtown Toronto is the city’s primary central business district and cultural core, known for its dense skyline, major attractions, and vibrant urban life.
-
C.
Toronto
Toronto is the largest city in Canada and a major cultural, financial, and media hub located in the province of Ontario.
-
D.
Southern Ontario
Southern Ontario is the densely populated, industrial and economic heartland of Ontario, Canada, encompassing major cities such as Toronto, Hamilton, and London.
-
E.
Brampton
Brampton is a large suburban city in the Greater Toronto Area known for its diverse population and rapidly growing economy.
- 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_69a257c3d0708190b0871c4269d273e6 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25ceaecdc81909e9ff49cb6a4e02a |
completed | Feb. 28, 2026, 3:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3736ff4388190b6b43a149d0003c5 |
completed | Feb. 28, 2026, 11 p.m. |
Created at: Feb. 28, 2026, 2:53 a.m.