Triple

T14859714
Position Surface form Disambiguated ID Type / Status
Subject Luxembourg Airport E349455 entity
Predicate hasPassengerAirline P71580 FINISHED
Object Lufthansa E48740 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: Lufthansa | Statement: [Luxembourg Airport, hasPassengerAirline, Lufthansa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lufthansa
Context triple: [Luxembourg Airport, hasPassengerAirline, Lufthansa]
  • A. Lufthansa chosen
    Lufthansa is Germany’s largest airline and a major global carrier known for its extensive international network and role in shaping modern airline alliances.
  • B. Lufthansa Cargo
    Lufthansa Cargo is the air freight and logistics division of the Lufthansa Group, operating a global network for transporting cargo by air.
  • C. Interflug
    Interflug was the state-owned national airline of East Germany, operating international and domestic flights primarily within the Eastern Bloc during the Cold War.
  • D. S7 Airlines
    S7 Airlines is a major Russian airline based in Novosibirsk that operates extensive domestic and international routes, particularly across Russia, Europe, and Asia.
  • E. Deutsche Luft-Reederei
    Deutsche Luft-Reederei was an early German airline, founded after World War I, that operated some of the first commercial passenger and mail flights in Germany.
  • 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_69d822ed7e1881909b90fca143ad7e34 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded44598e48190b759a05ed2d9ecaf completed April 14, 2026, 11:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe650a43bc8190b836fe690d2a3c71 completed May 8, 2026, 10:34 p.m.
Created at: April 10, 2026, 1:54 a.m.