Triple

T230511
Position Surface form Disambiguated ID Type / Status
Subject Cory Doctorow E4400 entity
Predicate placeOfBirth P1 FINISHED
Object Toronto, Ontario, Canada 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, Ontario, Canada | Statement: [Cory Doctorow, placeOfBirth, Toronto, Ontario, Canada]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toronto, Ontario, Canada
Context triple: [Cory Doctorow, placeOfBirth, 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. 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. London, Ontario
    London, Ontario is a mid-sized Canadian city in southwestern Ontario known for its educational institutions, healthcare sector, and role as a regional economic and cultural hub.
  • D. Markham, Ontario
    Markham, Ontario is a rapidly growing city in the Greater Toronto Area known for its diverse population, high-tech industry hub, and blend of urban and suburban communities.
  • E. Kingston, Ontario
    Kingston, Ontario is a historic Canadian city on the northeastern shore of Lake Ontario, known for its 19th-century limestone architecture, military and political heritage, and as home to Queen’s University.
  • 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_69a257363ffc81909757bde7ab3404da completed Feb. 28, 2026, 2:47 a.m.
NER Named-entity recognition batch_69a25cac7994819080b0b3b10808f8e5 completed Feb. 28, 2026, 3:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69a3c8b2a8a081908b45c15fae160d9e completed March 1, 2026, 5:03 a.m.
Created at: Feb. 28, 2026, 2:53 a.m.