Triple

T19539523
Position Surface form Disambiguated ID Type / Status
Subject Roundhouse Park E488857 entity
Predicate operator P179 FINISHED
Object City of Toronto NE NERFINISHED

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: [Roundhouse Park, operator, City of Toronto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Toronto
Context triple: [Roundhouse Park, operator, 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. Toronto East
    Toronto East was a former federal electoral district in Toronto, Ontario, represented in the Canadian House of Commons.
  • D. 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.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8db5b6c8190984b61f91981f575 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e63871d00881909ed7371ae5577957 completed April 20, 2026, 2:30 p.m.
Created at: April 10, 2026, 1:41 p.m.