Triple

T1400184
Position Surface form Disambiguated ID Type / Status
Subject Toronto City Centre Airport E30760 entity
Predicate servesAirline P12356 FINISHED
Object Air Canada E42187 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: Air Canada | Statement: [Toronto City Centre Airport, servesAirline, Air Canada]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Air Canada
Context triple: [Toronto City Centre Airport, servesAirline, Air Canada]
  • A. Air Canada chosen
    Air Canada is the flag carrier and largest airline of Canada, operating extensive domestic and international passenger and cargo services.
  • B. Canadian Airlines
    Canadian Airlines was a former major Canadian carrier that operated extensive domestic and international routes before being acquired by Air Canada in 2000.
  • C. WestJet
    WestJet is a major Canadian low-cost airline known for its extensive domestic and international route network and customer-friendly service.
  • D. Air Transat
    Air Transat is a Canadian leisure airline based in Montreal that operates scheduled and charter flights primarily between Canada and vacation destinations in Europe, the Caribbean, and other sun markets.
  • E. Nordair
    Nordair was a former Canadian regional airline that operated passenger and cargo services, particularly in northern and remote areas, before being absorbed into larger national carriers.
  • 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_69a498fd4e408190bd73eca30ea9754c completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c39c4c148190997150996ca26a99 completed March 1, 2026, 10:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69acde3799f881908efb4ee73d412482 completed March 8, 2026, 2:25 a.m.
Created at: March 1, 2026, 7:59 p.m.