Triple

T3635100
Position Surface form Disambiguated ID Type / Status
Subject Junkers Ju 52 E77047 entity
Predicate serviceEntryOperator P5884 FINISHED
Object Deutsche Luft Hansa 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: Deutsche Luft Hansa | Statement: [Junkers Ju 52, serviceEntryOperator, Deutsche Luft Hansa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Deutsche Luft Hansa
Context triple: [Junkers Ju 52, serviceEntryOperator, Deutsche Luft Hansa]
  • 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. 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.
  • D. 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.
  • E. Swissair
    Swissair was the former national airline of Switzerland, renowned for its high service standards and extensive international route network until its collapse in 2001.
  • 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_69ad85dd0be48190b738990cb20c4731 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc325e2548190ae243ae69126e65c completed March 8, 2026, 6:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69b488320c58819088f8cc677f675ec3 completed March 13, 2026, 9:57 p.m.
Created at: March 8, 2026, 3:24 p.m.