Triple

T21653694
Position Surface form Disambiguated ID Type / Status
Subject Kreis Brandenburg-Land E534402 entity
Predicate borderedBy P224 FINISHED
Object Kreis Zerbst 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: Kreis Zerbst | Statement: [Kreis Brandenburg-Land, borderedBy, Kreis Zerbst]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kreis Zerbst
Context triple: [Kreis Brandenburg-Land, borderedBy, Kreis Zerbst]
  • A. Kreis Belzig
    Kreis Belzig was a former rural district in the German Democratic Republic, located in the Potsdam region of the state of Brandenburg.
  • B. Kreis Köthen chosen
    Kreis Köthen was a former rural district in the German Democratic Republic, located within the administrative region of Bezirk Halle.
  • C. Kreis Sebnitz
    Kreis Sebnitz was a former rural district in the German Democratic Republic, located in the Bezirk Dresden region of Saxony and centered around the town of Sebnitz.
  • D. Kreis Querfurt
    Kreis Querfurt was a former rural district in the German Democratic Republic, located in the southern part of what is now the state of Saxony-Anhalt.
  • E. Kreis Apolda
    Kreis Apolda was a former rural district in the German Democratic Republic, located within the administrative region of Bezirk Erfurt.
  • 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_69e0c466aec88190ba39c7543dbc8ba2 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef59164fe081908abd2e33dcd67def completed April 27, 2026, 12:39 p.m.
Created at: April 16, 2026, 6:36 p.m.