Triple

T9908013
Position Surface form Disambiguated ID Type / Status
Subject Olympic Island E185064 entity
Predicate hasViewOf P854 FINISHED
Object Toronto skyline 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 skyline | Statement: [Olympic Island, hasViewOf, Toronto skyline]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toronto skyline
Context triple: [Olympic Island, hasViewOf, Toronto skyline]
  • A. 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.
  • B. Toronto sign
    The Toronto sign is a large, illuminated public art installation that spells out the city's name and serves as an iconic photo spot and gathering place in downtown Toronto.
  • C. Toronto Centre
    Toronto Centre is a densely populated federal electoral district in downtown Toronto, Ontario, known for its diverse communities and significant political prominence.
  • D. 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.
  • E. Chicago skyline
    The Chicago skyline is the iconic, high-rise cityscape along Lake Michigan, renowned for its distinctive skyscrapers and architectural diversity.
  • 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_69ca8296165881908ca4750701af1f29 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cdb50ec61481908f42bd2aa55d9a6e completed April 2, 2026, 12:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69d20daabd5881908b02da50a640766a completed April 5, 2026, 7:22 a.m.
Created at: March 30, 2026, 8:41 p.m.