Triple

T252129
Position Surface form Disambiguated ID Type / Status
Subject Naomi Klein E5170 entity
Predicate residence P75 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: [Naomi Klein, residence, Toronto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toronto
Context triple: [Naomi Klein, residence, 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. 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. PortsToronto
    PortsToronto is a government business enterprise that manages and operates key transportation and waterfront assets in Toronto, including Billy Bishop Toronto City Airport and the city’s port and marina facilities.
  • E. 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.
  • 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_69a257c4bf688190a46ebbf411ab7473 completed Feb. 28, 2026, 2:49 a.m.
NER Named-entity recognition batch_69a25d39eb3881909f435043c8697f13 completed Feb. 28, 2026, 3:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69a4366436008190b883eb9f0bfdb329 completed March 1, 2026, 12:51 p.m.
Created at: Feb. 28, 2026, 2:54 a.m.