Triple

T6713016
Position Surface form Disambiguated ID Type / Status
Subject Kerpen E153193 entity
Predicate hasSubdivision P747 FINISHED
Object Kerpen (town centre) E153193 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: Kerpen (town centre) | Statement: [Kerpen, hasSubdivision, Kerpen (town centre)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kerpen (town centre)
Context triple: [Kerpen, hasSubdivision, Kerpen (town centre)]
  • A. Kerpen chosen
    Kerpen is a town in North Rhine-Westphalia, Germany, known as the birthplace of Formula 1 champion Michael Schumacher and for its proximity to Cologne.
  • B. Bernkastel-Kues
    Bernkastel-Kues is a historic wine-growing town in Germany’s Rhineland-Palatinate region, renowned for its medieval architecture and picturesque setting amid the Moselle Valley vineyards.
  • C. Wissenkerke
    Wissenkerke is a village in the Dutch province of Zeeland, located on the island and municipality of Noord-Beveland.
  • D. Küdinghoven
    Küdinghoven is a district of the Beuel borough in Bonn, Germany, known for its residential character and proximity to the Rhine.
  • E. Wermelskirchen
    Wermelskirchen is a small town in North Rhine-Westphalia, Germany, known for its location in the hilly Bergisches Land region and its traditional half-timbered architecture.
  • 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_69c68809b4608190a2509ddb5ab87f05 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d121a92c8190a03f384a8aba84da completed March 27, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69c700948788819087f9b466be337286 completed March 27, 2026, 10:11 p.m.
Created at: March 27, 2026, 2:07 p.m.