Triple

T23219840
Position Surface form Disambiguated ID Type / Status
Subject Jan Rubes E580855 entity
Predicate deathPlace P21 FINISHED
Object Toronto, Ontario, Canada 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: Toronto, Ontario, Canada | Statement: [Jan Rubes, deathPlace, Toronto, Ontario, Canada]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toronto, Ontario, Canada
Context triple: [Jan Rubes, deathPlace, Toronto, Ontario, Canada]
  • A. Toronto chosen
    Toronto is the largest city in Canada and a major cultural, financial, and media hub located in the province of Ontario.
  • B. Toronto East
    Toronto East was a former federal electoral district in Toronto, Ontario, represented in the Canadian House of Commons.
  • C. York, Ontario
    York, Ontario is a former municipality and now a district within the city of Toronto, Canada, known for its diverse residential neighborhoods and major north–south thoroughfares.
  • D. Kanata, Ontario, Canada
    Kanata, Ontario, Canada is a suburban community in western Ottawa known as a major high-tech hub and business center.
  • E. Mississauga, Ontario, Canada
    Mississauga, Ontario, Canada is a large suburban city west of Toronto known for its diverse population, major corporate headquarters, and proximity to Toronto Pearson International Airport.
  • 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_69e2460389408190be74f41d217799a9 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f1916870148190853874e6cf26bbc7 completed April 29, 2026, 5:04 a.m.
Created at: April 17, 2026, 4:08 p.m.