Triple

T14295422
Position Surface form Disambiguated ID Type / Status
Subject Northern Berlin E354425 entity
Predicate hasPart P35 FINISHED
Object Französisch Buchholz E393551 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: Französisch Buchholz | Statement: [Northern Berlin, hasPart, Französisch Buchholz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Französisch Buchholz
Context triple: [Northern Berlin, hasPart, Französisch Buchholz]
  • A. Französisch Buchholz chosen
    Französisch Buchholz is a northeastern locality of Berlin known for its village-like character and incorporation into the borough of Pankow.
  • B. Riedholz
    Riedholz is a small Swiss municipality located in the canton of Solothurn.
  • C. Kestenholz
    Kestenholz is a municipality in the canton of Solothurn in Switzerland, located in the Gäu district.
  • D. Plauen
    Plauen is a historic town in eastern Germany known for its textile industry and intricate lace production.
  • E. Bramsche
    Bramsche is a town in Lower Saxony, Germany, known for its location near Osnabrück and its historical textile industry.
  • 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_69d8278e17088190b328c5a9d4be74ff completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de717b35ec81908968994e65737c66 completed April 14, 2026, 4:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd3d246ccc81909e9fe8b4487dcc88 completed May 8, 2026, 1:32 a.m.
Created at: April 10, 2026, 1:11 a.m.