Triple

T12877823
Position Surface form Disambiguated ID Type / Status
Subject Leipzig metropolitan region E308012 entity
Predicate containsCity P294 FINISHED
Object Burgwerben E782915 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: Burgwerben | Statement: [Leipzig metropolitan region, containsCity, Burgwerben]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Burgwerben
Context triple: [Leipzig metropolitan region, containsCity, Burgwerben]
  • A. Burgwerben chosen
    Burgwerben is a small municipality in the Weißenfels area of Saxony-Anhalt, Germany, known for its rural character and local wine-growing traditions.
  • B. Burgkunstadt
    Burgkunstadt is a small Bavarian town in northern Germany known for its historic center and location in the Upper Franconia region.
  • C. Burggrafenburg
    Burggrafenburg is a historic German castle traditionally associated with a burgrave, a medieval noble responsible for the defense and administration of a fortified town or region.
  • D. Bergheim
    Bergheim is a municipality in the Austrian state of Salzburg, located just north of the city of Salzburg and known for its suburban character and proximity to the regional capital.
  • E. Bergheim
    Bergheim is a town in western Germany situated along the Erft River, known for its historical center and proximity to the Cologne region.
  • 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_69d7bdf69bc48190af6c2621f28ca351 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d970fa8474819086a8af3c90f3ca84 completed April 10, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6cbbb199081909c32575097fbc2bf completed May 3, 2026, 4:14 a.m.
Created at: April 9, 2026, 5:38 p.m.