Triple

T19680240
Position Surface form Disambiguated ID Type / Status
Subject Lambersart E472562 entity
Predicate hasTwinTown P919 FINISHED
Object Viersen 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: Viersen | Statement: [Lambersart, hasTwinTown, Viersen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Viersen
Context triple: [Lambersart, hasTwinTown, Viersen]
  • A. Viersen chosen
    Viersen is a town in western Germany’s North Rhine-Westphalia, known for its proximity to Mönchengladbach and its role as a local administrative and cultural center.
  • B. Voerde
    Voerde is a town in the Wesel district of North Rhine-Westphalia, Germany, situated on the Lower Rhine in the Ruhr region.
  • C. Wesel
    Wesel is a historic city in western Germany, located on the Rhine River in the state of North Rhine-Westphalia.
  • D. Bentheim
    Bentheim is a historical county in Lower Saxony, Germany, known for its Reformed Protestant heritage and the former County of Bentheim.
  • E. Dülmen
    Dülmen is a town in western Germany’s North Rhine-Westphalia, known for its location between Münster and the Ruhr area and for the wild Dülmen ponies in the nearby nature reserve.
  • 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_69d8e514f2e08190ba70a4449519d218 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e641be90788190968a991153ef46a9 completed April 20, 2026, 3:09 p.m.
Created at: April 10, 2026, 1:45 p.m.