Triple

T5179872
Position Surface form Disambiguated ID Type / Status
Subject Nantes Atlantique Airport E116892 entity
Predicate hasHubFor P423 FINISHED
Object Transavia France E17177 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: Transavia France | Statement: [Nantes Atlantique Airport, hasHubFor, Transavia France]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Transavia France
Context triple: [Nantes Atlantique Airport, hasHubFor, Transavia France]
  • A. Transavia France chosen
    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.
  • B. Transavia
    Transavia is a Dutch low-cost airline operating scheduled and charter flights across Europe and North Africa.
  • C. 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.
  • D. Martinair
    Martinair is a Dutch airline based in the Netherlands that operates both cargo and charter passenger services, historically linked to KLM.
  • 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_69bd446140f08190becb93c61158f27f completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd79978a208190b2e5909795108327 completed March 20, 2026, 4:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69bed9553bc0819082a37a83a3edf7e8 completed March 21, 2026, 5:45 p.m.
Created at: March 20, 2026, 1:45 p.m.