Triple

T1419207
Position Surface form Disambiguated ID Type / Status
Subject KLM E31984 entity
Predicate hasSubsidiary P254 FINISHED
Object Martinair E80785 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: Martinair | Statement: [KLM, hasSubsidiary, Martinair]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Martinair
Context triple: [KLM, hasSubsidiary, Martinair]
  • A. Martinair chosen
    Martinair is a Dutch airline based in the Netherlands that operates both cargo and charter passenger services, historically linked to KLM.
  • B. Brussels Airlines
    Brussels Airlines is the flag carrier airline of Belgium, operating flights across Europe, Africa, and other regions as part of the Lufthansa Group.
  • C. Transavia
    Transavia is a Dutch low-cost airline operating scheduled and charter flights across Europe and North Africa.
  • D. Transavia France
    Transavia France is a French low-cost airline and subsidiary of the Air France-KLM group, operating primarily short- and medium-haul leisure routes across Europe and the Mediterranean.
  • E. Lynx Air
    Lynx Air is a Canadian ultra-low-cost airline that operates domestic and select international flights, primarily serving major hubs such as Toronto Pearson International Airport.
  • 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_69a49919a994819086528951bc224775 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c40631e881909ddf81a2eb84af1c completed March 1, 2026, 10:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad293cb8f0819085bea7914abf0683 completed March 8, 2026, 7:46 a.m.
Created at: March 1, 2026, 7:59 p.m.