Triple

T383933
Position Surface form Disambiguated ID Type / Status
Subject Star Alliance E8738 entity
Predicate foundingMember P446 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: [Star Alliance, foundingMember, Air Canada]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Air Canada
Context triple: [Star Alliance, foundingMember, 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. Aeroméxico
    Aeroméxico is Mexico’s flagship airline, operating domestic and international flights across the Americas, Europe, and Asia from its main hub in Mexico City.
  • D. American Airlines
    American Airlines is a major U.S.-based airline and one of the world's largest carriers, operating extensive domestic and international routes.
  • E. Copa Airlines
    Copa Airlines is the flag carrier of Panama and a major Latin American airline known for its extensive route network centered on its hub in Panama City.
  • 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_69a2e7f47dd08190a4e294ccbbe46cd4 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ec422b808190b6ddf747ef939151 completed Feb. 28, 2026, 1:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3fe95c7088190a1538eecb2ac6955 completed March 1, 2026, 8:53 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.