Triple

T5691598
Position Surface form Disambiguated ID Type / Status
Subject French sector of Berlin E125438 entity
Predicate contains P35 FINISHED
Object French sector of Tegel E125438 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: French sector of Tegel | Statement: [French sector of Berlin, contains, French sector of Tegel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: French sector of Tegel
Context triple: [French sector of Berlin, contains, French sector of Tegel]
  • A. Tempelhof Airport
    Tempelhof Airport is a historic Berlin airfield best known as a central hub of the Berlin Airlift during the Cold War.
  • B. French sector of Berlin chosen
    The French sector of Berlin was one of the four Allied-occupied zones in post–World War II Berlin, administered by France in the city’s northwest during the Cold War.
  • C. Roissy-en-France
    Roissy-en-France is a commune in the northeastern suburbs of Paris best known for hosting most of Charles de Gaulle Airport, France’s largest international air hub.
  • D. Tegel
    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.
  • E. Le Bourget, Paris, France
    Le Bourget, in the northeastern suburbs of Paris, is best known as the site of major international events and transport hubs, including the historic 2015 UN climate conference (COP21) and one of the city’s main airports.
  • 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_69c0082bb19c8190823a4facd3cba79b completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c023e500ec8190bfda4f6a818aa5dc completed March 22, 2026, 5:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c05a4baea481908b4766888fd3edf1 completed March 22, 2026, 9:08 p.m.
Created at: March 22, 2026, 3:44 p.m.