Triple

T3483721
Position Surface form Disambiguated ID Type / Status
Subject Charlotte Perriand E73556 entity
Predicate designedFor P98 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: [Charlotte Perriand, designedFor, Air France]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Air France
Context triple: [Charlotte Perriand, designedFor, 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. 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.
  • E. 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.
  • 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_69ad85b3c9b08190857cae74c7f36da9 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adbb781e9c8190810fdd814f506127 completed March 8, 2026, 6:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69b36820c90c819091b68cff7a0a2cda completed March 13, 2026, 1:28 a.m.
Created at: March 8, 2026, 3:17 p.m.