Triple

T16065032
Position Surface form Disambiguated ID Type / Status
Subject Boulevard Berlin E389709 entity
Predicate district P2709 FINISHED
Object Steglitz E13910 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: Steglitz | Statement: [Boulevard Berlin, district, Steglitz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Steglitz
Context triple: [Boulevard Berlin, district, Steglitz]
  • A. Steglitz-Zehlendorf chosen
    Steglitz-Zehlendorf is a borough in southwestern Berlin known for its affluent residential areas, lakes and forests, and historically significant sites such as the Wannsee Conference villa.
  • B. Friedrichsfelde
    Friedrichsfelde is a residential district in the Berlin borough of Lichtenberg, known for its large housing estates and proximity to Tierpark Berlin.
  • C. Reinickendorf
    Reinickendorf is a borough in the northwest of Berlin, Germany, known for its mix of residential neighborhoods, industrial areas, and green spaces including parts of Lake Tegel.
  • D. Pankow
    Pankow is a northeastern borough of Berlin known for its mix of historic neighborhoods, green spaces, and the popular district of Prenzlauer Berg.
  • E. Wilmersdorf
    Wilmersdorf is a residential district in southwestern Berlin known for its affluent neighborhoods, shopping streets like Kurfürstendamm, and a mix of historic and modern architecture.
  • 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_69d86daf32ec8190a8c0466c8f49c3c0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1837bec688190a77ad347600b6bdc completed April 17, 2026, 12:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0084a6d6308190ad57a51b380171a2 completed May 10, 2026, 1:14 p.m.
Created at: April 10, 2026, 4:57 a.m.