Triple

T4385070
Position Surface form Disambiguated ID Type / Status
Subject Entertainment District E99221 entity
Predicate hasLandmark P105 FINISHED
Object CN Tower E4888 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: CN Tower | Statement: [Entertainment District, hasLandmark, CN Tower]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CN Tower
Context triple: [Entertainment District, hasLandmark, CN Tower]
  • A. CN Tower chosen
    The CN Tower is a prominent communications and observation tower in downtown Toronto, Canada, and one of the city's most recognizable skyline landmarks.
  • B. Calgary Tower
    The Calgary Tower is a prominent observation tower and city landmark in downtown Calgary, Alberta, known for its panoramic views and glass-floored observation deck.
  • C. Ontario Tower
    Ontario Tower is a prominent commercial and residential skyscraper located in Dubai’s Business Bay district.
  • D. TD Canada Trust Tower
    TD Canada Trust Tower is a prominent office skyscraper in downtown Toronto that forms part of the Brookfield Place complex and houses major financial and corporate tenants.
  • E. First Canadian Place
    First Canadian Place is a prominent office and retail skyscraper in Toronto’s financial district and one of the tallest buildings in Canada.
  • 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_69b3454f739481909ff6c28331f0c0b9 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35264e44c81908dd0e0a81f1353bb completed March 12, 2026, 11:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5e526e35c8190838c59e402da3c89 completed March 14, 2026, 10:45 p.m.
Created at: March 12, 2026, 11:19 p.m.