Triple

T586148
Position Surface form Disambiguated ID Type / Status
Subject Amsterdam Airport Schiphol E15161 entity
Predicate isHubFor P423 FINISHED
Object KLM E31984 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: KLM | Statement: [Amsterdam Airport Schiphol, isHubFor, KLM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: KLM
Context triple: [Amsterdam Airport Schiphol, isHubFor, KLM]
  • A. KLM chosen
    KLM is the flag carrier airline of the Netherlands and one of the world's oldest airlines still operating under its original name.
  • 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. Lufthansa
    Lufthansa is Germany’s largest airline and a major global carrier known for its extensive international network and role in shaping modern airline alliances.
  • 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. Air France-KLM
    Air France-KLM is a major Franco-Dutch airline holding company and one of Europe’s largest airline groups, operating extensive global passenger and cargo networks.
  • 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_69a4935783b8819082b77726ec10cc42 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49b9a46388190a094b9ebf8dec397 completed March 1, 2026, 8:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69a51f33e59c8190b3593b8460411fba completed March 2, 2026, 5:25 a.m.
Created at: March 1, 2026, 7:33 p.m.