Triple

T12877824
Position Surface form Disambiguated ID Type / Status
Subject Leipzig metropolitan region E308012 entity
Predicate containsCity P294 FINISHED
Object Reichardtswerben E782916 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: Reichardtswerben | Statement: [Leipzig metropolitan region, containsCity, Reichardtswerben]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Reichardtswerben
Context triple: [Leipzig metropolitan region, containsCity, Reichardtswerben]
  • A. Reichardtswerben chosen
    Reichardtswerben is a small municipality in the Weißenfels area of Saxony-Anhalt in eastern Germany.
  • B. Wurmberg
    Wurmberg is a prominent mountain in the Harz range of central Germany, popular for skiing, hiking, and panoramic views.
  • C. Querbach
    Querbach is a district of the German town of Kehl in the state of Baden-Württemberg.
  • D. Zollikofen
    Zollikofen is a municipality in the canton of Bern in Switzerland, functioning as a suburban community within the greater Bern metropolitan region.
  • E. Seckbach
    Seckbach is a district in the east of Frankfurt am Main, Germany, known for its residential character and proximity to green spaces like the Lohrberg.
  • 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_69f69bb83bac8190838f7537b806317c completed May 3, 2026, 12:50 a.m.
Created at: April 9, 2026, 5:38 p.m.