Triple

T20459282
Position Surface form Disambiguated ID Type / Status
Subject DE40 (Brandenburg) E501879 entity
Predicate containsMunicipality P852 FINISHED
Object Senftenberg 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: Senftenberg | Statement: [DE40 (Brandenburg), containsMunicipality, Senftenberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Senftenberg
Context triple: [DE40 (Brandenburg), containsMunicipality, Senftenberg]
  • A. Senftenberg chosen
    Senftenberg is a town in eastern Germany known for its lakeside recreation area and former lignite mining sites, located in the federal state of Brandenburg.
  • B. Olbernhau
    Olbernhau is a town in Germany’s Ore Mountains renowned for its traditional woodcraft industry, especially the production of Schwibbogen candle arches and other Christmas decorations.
  • C. Meißen
    Meißen is a historic town in the German state of Saxony, renowned for its porcelain manufacture and well-preserved medieval architecture along the Elbe River.
  • D. Kretzschau
    Kretzschau is a small municipality in the German state of Saxony-Anhalt that forms part of the wider Leipzig metropolitan area.
  • E. Premnitz
    Premnitz is a small town in the Havelland region of Brandenburg, Germany, situated on the Havel River and known historically for its chemical industry.
  • 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_69e0b4ad4940819098cf2ff6413574e5 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e696a4652c8190acf79fa2e285e436 completed April 20, 2026, 9:12 p.m.
Created at: April 16, 2026, 11:33 a.m.