Triple

T764930
Position Surface form Disambiguated ID Type / Status
Subject Nice Côte d’Azur Airport E16153 entity
Predicate hasFocusCityAirline P1295 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: [Nice Côte d’Azur Airport, hasFocusCityAirline, Air France]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Air France
Context triple: [Nice Côte d’Azur Airport, hasFocusCityAirline, 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. 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.
  • E. Martinair
    Martinair is a Dutch airline based in the Netherlands that operates both cargo and charter passenger services, historically linked to KLM.
  • 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_69a493684ee48190bd43b7c78da4aec8 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a69dfeb08190b54a476cfa66e6d6 completed March 1, 2026, 8:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69a65e46d86c81908bc0ea469ccb091d completed March 3, 2026, 4:06 a.m.
Created at: March 1, 2026, 7:37 p.m.