Triple

T6501401
Position Surface form Disambiguated ID Type / Status
Subject Nicosia International Airport E148896 entity
Predicate usedBy P260 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: [Nicosia International Airport, usedBy, Lufthansa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lufthansa
Context triple: [Nicosia International Airport, usedBy, 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. Lufthansa CityLine
    Lufthansa CityLine is a German regional airline and Lufthansa subsidiary that operates short- and medium-haul routes across Europe, primarily feeding traffic into Lufthansa’s main hubs.
  • 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_69c687e9ad288190bae5bcac9c8ac855 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c68ad2e148819088be5c48ad73dc59 completed March 27, 2026, 1:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6cb2e83cc81908f07a402e8562f1a completed March 27, 2026, 6:23 p.m.
Created at: March 27, 2026, 1:42 p.m.