Triple
T11518848
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen Street |
E273102
|
entity |
| Predicate | maintainedBy |
P86
|
FINISHED |
| Object | City of Toronto |
E1525
|
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: City of Toronto | Statement: [Queen Street, maintainedBy, City of Toronto]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: City of Toronto Context triple: [Queen Street, maintainedBy, City of Toronto]
-
A.
Metropolitan Toronto
Metropolitan Toronto was a former regional government in Ontario, Canada that encompassed the city of Toronto and its surrounding municipalities before their amalgamation into a single city in 1998.
-
B.
Toronto
chosen
Toronto is the largest city in Canada and a major cultural, financial, and media hub located in the province of Ontario.
-
C.
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.
-
D.
Municipality of Toronto
The Municipality of Toronto is Canada’s largest city and economic hub, located in the province of Ontario on the northwestern shore of Lake Ontario.
-
E.
City of Ontario
The City of Ontario is a major suburban city in southwestern San Bernardino County, California, known for its international airport, logistics hubs, and role as an Inland Empire commercial center.
- 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_69d6aae2c3748190bed2ea50dfb160dc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d87fcf927081908ef89eff7ad833b0 |
completed | April 10, 2026, 4:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef12d90b608190b43fc3aa138aa856 |
completed | April 27, 2026, 7:40 a.m. |
Created at: April 8, 2026, 9:36 p.m.