Triple

T4447136
Position Surface form Disambiguated ID Type / Status
Subject Air Union E96315 entity
Predicate mergedInto P77 FINISHED
Object Air France E16857 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 France | Statement: [Air Union, mergedInto, Air France]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Air France
Context triple: [Air Union, mergedInto, Air France]
  • A. Air France chosen
    Air France is the French flag carrier airline and one of Europe’s major international airlines, operating a global network of passenger and cargo services.
  • B. 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.
  • C. 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.
  • D. Société Générale de Transports Aériens
    Société Générale de Transports Aériens was an early French airline that became part of the consolidation of France’s civil aviation sector in the interwar period.
  • E. French Bee Airlines
    French Bee Airlines is a French low-cost, long-haul carrier known for operating budget flights primarily between France, the United States, and various leisure destinations.
  • 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_69b345415ba481908df738e7174448ba completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b355d31e10819086590b9f828d50b0 completed March 13, 2026, 12:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69bb80cd81d08190ad1d65091cecdfac completed March 19, 2026, 4:51 a.m.
Created at: March 12, 2026, 11:32 p.m.