Triple

T175021
Position Surface form Disambiguated ID Type / Status
Subject Ontario E3554 entity
Predicate containsLandmark P1098 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: [Ontario, containsLandmark, CN Tower]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CN Tower
Context triple: [Ontario, containsLandmark, 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. Toronto City Hall
    Toronto City Hall is a distinctive modernist civic complex in downtown Toronto that houses the city's municipal government and is one of its most recognizable architectural landmarks.
  • C. Sandford Fleming Building
    The Sandford Fleming Building is a prominent engineering and academic facility at the University of Toronto’s St. George campus.
  • D. Casa Loma
    Casa Loma is a historic Gothic Revival-style mansion and popular tourist attraction in Toronto, Canada, known for its castle-like architecture and expansive gardens.
  • E. Union Station, Toronto
    Union Station in Toronto is the city’s primary railway and transit hub, serving as a central gateway for regional, national, and local transportation.
  • 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_69a25374990081909766d30c79a18e0e completed Feb. 28, 2026, 2:31 a.m.
NER Named-entity recognition batch_69a25bafd5808190a0a0cb2b21ce007f completed Feb. 28, 2026, 3:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2eb7babec8190a1c1a6bcc94605ef completed Feb. 28, 2026, 1:19 p.m.
Created at: Feb. 28, 2026, 2:39 a.m.