Triple

T17826544
Position Surface form Disambiguated ID Type / Status
Subject Wilhelmsruh E445131 entity
Predicate borderedBy P224 FINISHED
Object Niederschönhausen NE NERFINISHED

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: Niederschönhausen | Statement: [Wilhelmsruh, borderedBy, Niederschönhausen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Niederschönhausen
Context triple: [Wilhelmsruh, borderedBy, Niederschönhausen]
  • A. Niederschönhausen chosen
    Niederschönhausen is a residential district in the Berlin borough of Pankow, known for its historic villas, green spaces, and the former presidential residence Schloss Schönhausen.
  • B. Niederschöneweide
    Niederschöneweide is a locality in the Berlin borough of Treptow-Köpenick, known for its riverside setting along the Spree and its mix of residential areas and former industrial sites.
  • C. Münchholzhausen
    Münchholzhausen is a district of the city of Wetzlar in the German state of Hesse.
  • D. Schönewalde
    Schönewalde is a town in the state of Brandenburg, Germany, known for hosting a German Air Force base.
  • E. Wilhelmsdorf
    Wilhelmsdorf is a village-level subdivision of the town of Usingen in the Hochtaunus district of Hesse, Germany.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9f0de78819099395b14db75a8a6 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e48914e20481908883d1da194f446c completed April 19, 2026, 7:49 a.m.
Created at: April 10, 2026, 10:15 a.m.