Triple

T8102536
Position Surface form Disambiguated ID Type / Status
Subject Cologne Bonn Airport E189148 entity
Predicate isHubFor P423 FINISHED
Object DHL Aviation E177498 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: DHL Aviation | Statement: [Cologne Bonn Airport, isHubFor, DHL Aviation]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: DHL Aviation
Context triple: [Cologne Bonn Airport, isHubFor, DHL Aviation]
  • A. DHL Aviation chosen
    DHL Aviation is the air cargo division of DHL, operating a global network of freight flights that connect major logistics hubs worldwide.
  • B. Airbus Transport International
    Airbus Transport International is a specialized cargo airline that operates Airbus Beluga aircraft to transport oversized aircraft components and other outsize freight for Airbus and its partners.
  • C. Cargolux
    Cargolux is a major Luxembourg-based cargo airline and one of the world’s leading dedicated freight carriers.
  • D. Lufthansa Cargo
    Lufthansa Cargo is the air freight and logistics division of the Lufthansa Group, operating a global network for transporting cargo by air.
  • E. Lynden Air Cargo
    Lynden Air Cargo is an American cargo airline based in Alaska that specializes in operating Hercules aircraft to provide freight services to remote and challenging destinations worldwide.
  • 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_69ca82b886d88190a9cba0d5a4a27521 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb42bd91408190880293dfdce8bef7 completed March 31, 2026, 3:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc642095a08190bcf90e6470e127cc completed April 1, 2026, 12:17 a.m.
Created at: March 30, 2026, 5:31 p.m.