Triple

T1114379
Position Surface form Disambiguated ID Type / Status
Subject Tempelhof Airport E11062 entity
Predicate partOf P40 FINISHED
Object Tempelhofer Feld E62023 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: Tempelhofer Feld | Statement: [Tempelhof Airport, partOf, Tempelhofer Feld]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tempelhofer Feld
Context triple: [Tempelhof Airport, partOf, Tempelhofer Feld]
  • A. Tempelhofer Feld chosen
    Tempelhofer Feld is a vast public park and former airport in Berlin, Germany, known for its open runways, recreational spaces, and historical significance, including its role in the Berlin Airlift.
  • B. Tegeler Forst
    Tegeler Forst is a large forested area in the Berlin district of Tegel, known for its natural landscapes, walking trails, and recreational opportunities.
  • C. Englischer Garten
    Englischer Garten is a large public park in Munich, Germany, renowned for its expansive green spaces, beer gardens, and riverside surfing on the Eisbach.
  • D. Tiergarten
    Tiergarten is a large central park in Berlin known for its expansive green spaces, monuments, and cultural landmarks.
  • E. Babelsberg Park
    Babelsberg Park is a historic landscaped park in Potsdam, Germany, known for its picturesque lakeside setting, neo-Gothic Babelsberg Palace, and 19th-century English-style garden design.
  • 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_69a493252a648190ac48f8742474a5e8 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4bba04324819090d2f8fcccc2a4c2 completed March 1, 2026, 10:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac539783188190896ab66306697b1c completed March 7, 2026, 4:34 p.m.
Created at: March 1, 2026, 7:43 p.m.