Triple

T447069
Position Surface form Disambiguated ID Type / Status
Subject Innis College E7044 entity
Predicate region P40 FINISHED
Object Downtown Toronto E18465 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: Downtown Toronto | Statement: [Innis College, region, Downtown Toronto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Downtown Toronto
Context triple: [Innis College, region, Downtown Toronto]
  • A. Downtown Toronto chosen
    Downtown Toronto is the city’s primary central business district and cultural core, known for its dense skyline, major attractions, and vibrant urban life.
  • B. Toronto
    Toronto is the largest city in Canada and a major cultural, financial, and media hub located in the province of Ontario.
  • C. Eastern Toronto
    Eastern Toronto is the part of Toronto that includes areas such as Scarborough and other eastern neighborhoods of the city.
  • D. Greater Toronto Area
    The Greater Toronto Area is a large metropolitan region in Ontario, Canada, encompassing Toronto and its surrounding municipalities and suburbs.
  • E. 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.
  • 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_69a2e7e4676c81909ea0dbdecac0687c completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ef62c7a88190851fcd57658b4102 completed Feb. 28, 2026, 1:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69a57b51a58481909d8e602b3fe3c68c completed March 2, 2026, 11:58 a.m.
Created at: Feb. 28, 2026, 1:12 p.m.