Triple

T3381794
Position Surface form Disambiguated ID Type / Status
Subject Air Berlin E71201 entity
Predicate operatedFromAirport P31126 FINISHED
Object Copenhagen Airport E67497 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: Copenhagen Airport | Statement: [Air Berlin, operatedFromAirport, Copenhagen Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Copenhagen Airport
Context triple: [Air Berlin, operatedFromAirport, Copenhagen Airport]
  • A. Copenhagen Airport Kastrup chosen
    Copenhagen Airport Kastrup is Denmark’s largest and busiest international airport, serving as the main air hub for Copenhagen and much of Scandinavia.
  • B. Bern Airport
    Bern Airport is a small regional airport in Switzerland serving the city of Bern and offering domestic and limited international flights.
  • C. Aalborg Airport
    Aalborg Airport is an international airport in northern Denmark serving the city of Aalborg and the surrounding region with domestic and European flights.
  • D. Oslo Airport, Gardermoen
    Oslo Airport, Gardermoen is Norway’s main international airport and the primary aviation hub serving the Oslo region.
  • E. Bergen Airport, Flesland
    Bergen Airport, Flesland is the main international airport serving the city of Bergen and western Norway, handling both domestic and international flights.
  • 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_69ad85a8fd9c819095ecedf838d2bf1b completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb5e9af608190bfb228ef99a87bb7 completed March 8, 2026, 5:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b34bc3f13c81909bec375bd080b7f3 completed March 12, 2026, 11:27 p.m.
Created at: March 8, 2026, 3:14 p.m.