Triple

T6358518
Position Surface form Disambiguated ID Type / Status
Subject Ringbahn (Berlin) E143051 entity
Predicate hasStation P35 FINISHED
Object Tempelhof E381479 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: Tempelhof | Statement: [Ringbahn (Berlin), hasStation, Tempelhof]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tempelhof
Context triple: [Ringbahn (Berlin), hasStation, Tempelhof]
  • A. Tempelhof chosen
    Tempelhof is a historic district in Berlin, Germany, best known for the former Tempelhof Airport and its vast airfield now used as a public park.
  • 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. 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.
  • D. Alt-Tempelhof
    Alt-Tempelhof is an underground station on Berlin’s U-Bahn network serving the Tempelhof district in the southern part of the city.
  • E. Spandau
    Spandau is a western borough of Berlin, Germany, known for its historic old town, fortress, and role as an important residential and industrial district.
  • 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_69c008d7a9c4819098d647ec47776917 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c067f72f8481908f9df0c0cdf22a52 completed March 22, 2026, 10:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69c62d5f134c8190817037ad933c4d2b completed March 27, 2026, 7:10 a.m.
Created at: March 22, 2026, 4:32 p.m.