Triple

T2448868
Position Surface form Disambiguated ID Type / Status
Subject Old Toronto E53654 entity
Predicate contains P35 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: [Old Toronto, contains, Toronto waterfront]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toronto waterfront
Context triple: [Old Toronto, contains, 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. Toronto City Marina
    Toronto City Marina is a public marina on Toronto’s waterfront that provides docking and boating services for recreational vessels near the city’s downtown core.
  • 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. waterfront Toronto
    Waterfront Toronto is a revitalized urban district along Toronto’s Lake Ontario shoreline featuring mixed-use developments, public spaces, and transit access.
  • E. Port Credit
    Port Credit is a historic waterfront neighbourhood and entertainment district along Lake Ontario in the city of Mississauga, Ontario, known for its marina, restaurants, and festivals.
  • 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_69ab495d227c8190b26ae6548eeb1019 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd0dc7ed88190920afd4817c621c9 completed March 7, 2026, 7:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69aef0c0069c8190bfb9e71aea4774d3 completed March 9, 2026, 4:09 p.m.
Created at: March 6, 2026, 9:43 p.m.