Triple

T10065439
Position Surface form Disambiguated ID Type / Status
Subject Marc Kielburger E213088 entity
Predicate basedIn P40 FINISHED
Object 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: Toronto | Statement: [Marc Kielburger, basedIn, Toronto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toronto
Context triple: [Marc Kielburger, basedIn, Toronto]
  • 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. Ottawa
    Ottawa is the capital city of Canada, located in eastern Ontario along the Ottawa River and known for its federal government institutions, cultural landmarks, and bilingual character.
  • C. Ottawa
    Ottawa are an Algonquian-speaking Indigenous people of North America historically known for their role in Great Lakes trade networks and resistance to European colonial expansion.
  • D. Toronto Centre
    Toronto Centre is a densely populated federal electoral district in downtown Toronto, Ontario, known for its diverse communities and significant political prominence.
  • E. 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.
  • 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_69ca83977128819084084eb7d1d8c52a completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdcff51b108190b6759f651d4ba2d2 completed April 2, 2026, 2:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2cbb441388190bf01925b8624377d completed April 5, 2026, 8:53 p.m.
Created at: March 30, 2026, 8:58 p.m.