Triple

T10950643
Position Surface form Disambiguated ID Type / Status
Subject Hamburg Airport E258716 entity
Predicate has hub airline P4364 FINISHED
Object Condor E258721 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: Condor | Statement: [Hamburg Airport, has hub airline, Condor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Condor
Context triple: [Hamburg Airport, has hub airline, Condor]
  • A. Condor chosen
    Condor is a German leisure airline known for operating holiday flights to popular vacation destinations, primarily from bases in Germany.
  • B. Condor
    Condor is the codename of the CIA analyst protagonist in the political thriller novel and film "Three Days of the Condor."
  • C. Condor
    Condor is the nickname of the Focke-Wulf Fw 200, a long-range German airliner later used as a maritime patrol and bomber aircraft during World War II.
  • D. Condors
    Condors is the nickname of the Bakersfield Condors, a professional ice hockey team based in Bakersfield, California.
  • E. Vultur
    Vultur is a genus of large New World vultures best known for including the Andean condor, one of the world’s largest flying birds.
  • 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_69d6aa88500c819097d7032ca578e74f completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770ed2f1c819081ec58457f57889d completed April 9, 2026, 9:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69e23c57038c819087671177c2ed5633 completed April 17, 2026, 1:57 p.m.
Created at: April 8, 2026, 9:23 p.m.