Triple

T14265938
Position Surface form Disambiguated ID Type / Status
Subject Wedding, Berlin E353643 entity
Predicate borderedBy P224 FINISHED
Object Reinickendorf, Berlin E14596 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: Reinickendorf, Berlin | Statement: [Wedding, Berlin, borderedBy, Reinickendorf, Berlin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Reinickendorf, Berlin
Context triple: [Wedding, Berlin, borderedBy, Reinickendorf, Berlin]
  • A. Reinickendorf chosen
    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.
  • B. Friedrichswerder, Berlin
    Friedrichswerder is a historic inner-city quarter of Berlin known for its 19th-century architecture and cultural landmarks near the city’s political and museum districts.
  • C. Pankow
    Pankow is a northeastern borough of Berlin known for its mix of historic neighborhoods, green spaces, and the popular district of Prenzlauer Berg.
  • D. Friedrichsfelde
    Friedrichsfelde is a residential district in the Berlin borough of Lichtenberg, known for its large housing estates and proximity to Tierpark Berlin.
  • 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_69d8278c43e08190824146f4632b89a5 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de6357a8188190ba518a486521052b completed April 14, 2026, 3:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4c2e7ee081909a70c9d9b32b6ce5 completed May 8, 2026, 2:36 a.m.
Created at: April 10, 2026, 1:09 a.m.