Triple

T106186
Position Surface form Disambiguated ID Type / Status
Subject Luftbrücke E2141 entity
Predicate uses P98 FINISHED
Object Tegel Airport E2522 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: Tegel Airport | Statement: [Luftbrücke, uses, Tegel Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tegel Airport
Context triple: [Luftbrücke, uses, Tegel Airport]
  • A. Tegel chosen
    Tegel is a locality in the Reinickendorf borough of Berlin, Germany, historically known for its manor associated with the Humboldt family and later for the former Berlin Tegel Airport.
  • B. Tempelhof Airport
    Tempelhof Airport is a historic Berlin airfield best known as a central hub of the Berlin Airlift during the Cold War.
  • C. Domodedovo International Airport
    Domodedovo International Airport is one of Moscow’s major international airports and a key air transport hub in Russia.
  • D. Washington Dulles International Airport
    Washington Dulles International Airport is a major international airport serving the Washington, D.C. metropolitan area, known for its extensive global flight network and iconic Eero Saarinen–designed terminal.
  • E. Vnukovo International Airport
    Vnukovo International Airport is one of Moscow’s major international airports, serving as a key hub for both domestic and international flights in Russia.
  • 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_69a24e0a5b7c81908d52da08c60dabc4 completed Feb. 28, 2026, 2:08 a.m.
NER Named-entity recognition batch_69a256c96e5481908c67f69e99978292 completed Feb. 28, 2026, 2:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69a27c030ddc8190af2ebb672237bf18 completed Feb. 28, 2026, 5:24 a.m.
Created at: Feb. 28, 2026, 2:12 a.m.