Triple

T1148482
Position Surface form Disambiguated ID Type / Status
Subject Harbourfront Centre E23621 entity
Predicate locatedOn P40 FINISHED
Object Toronto waterfront E96322 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 waterfront | Statement: [Harbourfront Centre, locatedOn, Toronto waterfront]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toronto waterfront
Context triple: [Harbourfront Centre, locatedOn, Toronto waterfront]
  • A. Toronto Harbour chosen
    Toronto Harbour is the natural bay on Lake Ontario that forms Toronto’s waterfront, encompassing key features such as the Toronto Islands and the city’s main port facilities.
  • 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. Toronto Islands
    The Toronto Islands are a chain of small, car-free islands in Lake Ontario that form a popular recreational park area just offshore from downtown Toronto.
  • D. Toronto
    Toronto is the largest city in Canada and a major cultural, financial, and media hub located in the province of Ontario.
  • E. Harbourfront Centre
    Harbourfront Centre is a major arts, culture, and recreational hub located along Toronto’s waterfront, known for its galleries, theatres, festivals, and public events.
  • 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_69a493f0d32c8190ac74bad3c87f2641 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4bc7190308190ab104480ed208b22 completed March 1, 2026, 10:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac5eb3ec3881908c8cb39b422fcc71 completed March 7, 2026, 5:21 p.m.
Created at: March 1, 2026, 7:44 p.m.