Triple

T11665867
Position Surface form Disambiguated ID Type / Status
Subject Upper Saxon Circle E277244 entity
Predicate appliesToJurisdiction P82 FINISHED
Object Naumburg E210567 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: Naumburg | Statement: [Upper Saxon Circle, appliesToJurisdiction, Naumburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Naumburg
Context triple: [Upper Saxon Circle, appliesToJurisdiction, Naumburg]
  • A. Naumburg chosen
    Naumburg is a historic town in the German state of Saxony-Anhalt, known for its medieval cathedral and as the childhood home of philosopher Friedrich Nietzsche.
  • B. Nordhausen
    Nordhausen is a historic town in central Germany known for its medieval architecture, former role as a key trading center, and association with the nearby Mittelbau-Dora concentration camp site.
  • C. Halberstadt
    Halberstadt is a historic town in the German state of Saxony-Anhalt, known for its medieval architecture and role as a former episcopal seat.
  • D. Melsungen
    Melsungen is a small historic town in northern Hesse, Germany, known for its well-preserved half-timbered houses and picturesque setting on the Fulda River.
  • E. Schmalkalden
    Schmalkalden is a historic town in the German state of Thuringia, known for its well-preserved medieval architecture and role in Reformation-era politics.
  • 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_69d6aafd0a448190b44da30af8c6c519 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a43f438081909da476294a057c38 completed April 10, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef82e252fc819082b5c8a33fcf861a completed April 27, 2026, 3:38 p.m.
Created at: April 8, 2026, 9:39 p.m.