Triple

T23158786
Position Surface form Disambiguated ID Type / Status
Subject Kreis Freiberg E578521 entity
Predicate contains P35 FINISHED
Object Niederwiesa 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: Niederwiesa | Statement: [Kreis Freiberg, contains, Niederwiesa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Niederwiesa
Context triple: [Kreis Freiberg, contains, Niederwiesa]
  • A. Niederwiesa chosen
    Niederwiesa is a municipality in the Free State of Saxony in eastern Germany, situated near the city of Chemnitz.
  • B. Weßling
    Weßling is a small municipality in Bavaria, Germany, known for its scenic lake and as a residential community near Munich.
  • C. Weilersbach
    Weilersbach is a small municipality in the Forchheim district of Bavaria, Germany, known for its rural character and proximity to the Franconian Switzerland region.
  • D. Wieseck
    Wieseck is a small river in the German state of Hesse that flows through the city of Giessen and its surrounding region.
  • E. Weschnitz
    Weschnitz is a river in southwestern Germany that flows from the Odenwald hills through Hesse and Baden-Württemberg before joining the Rhine.
  • 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_69e245fc75348190a0288401044c8af8 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f18efeddd48190b6d03d2146583dcc completed April 29, 2026, 4:54 a.m.
Created at: April 17, 2026, 4:02 p.m.