Triple

T19057407
Position Surface form Disambiguated ID Type / Status
Subject Prignitz district E466433 entity
Predicate administrativeSeat P21613 FINISHED
Object Perleberg 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: Perleberg | Statement: [Prignitz district, administrativeSeat, Perleberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Perleberg
Context triple: [Prignitz district, administrativeSeat, Perleberg]
  • A. Perleberg chosen
    Perleberg is a historic town in the German state of Brandenburg, known for its medieval architecture and role as an administrative and cultural center in the Prignitz region.
  • B. Weisselberg
    Weisselberg is a surname most prominently associated with Allen Weisselberg, the longtime chief financial officer of the Trump Organization.
  • C. Wirsberg
    Wirsberg is a small market town in the Upper Franconia region of Bavaria, Germany, known for its scenic location in the Franconian Forest and its historic architecture.
  • D. Todtnau
    Todtnau is a small town in Germany’s Black Forest region, known for its mountainous scenery, outdoor recreation, and proximity to the Feldberg peak.
  • E. Voitsberg
    Voitsberg is a small town in southeastern Austria known for its industrial heritage and location within the federal state of Styria.
  • 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_69d8dd040fb881909af2a964f65ad208 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5dc0742288190a594be859184841a completed April 20, 2026, 7:55 a.m.
Created at: April 10, 2026, 12:03 p.m.