Triple

T16763169
Position Surface form Disambiguated ID Type / Status
Subject district of Wesel E407395 entity
Predicate containsMunicipality P852 FINISHED
Object Voerde (Niederrhein) E886732 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: Voerde (Niederrhein) | Statement: [district of Wesel, containsMunicipality, Voerde (Niederrhein)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Voerde (Niederrhein)
Context triple: [district of Wesel, containsMunicipality, Voerde (Niederrhein)]
  • A. Voerde chosen
    Voerde is a town in the Wesel district of North Rhine-Westphalia, Germany, situated on the Lower Rhine in the Ruhr region.
  • B. Viersen
    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.
  • C. Neuenkirchen-Vörden
    Neuenkirchen-Vörden is a small municipality in Lower Saxony, Germany, known for its rural character and location between the cities of Osnabrück and Bremen.
  • D. 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.
  • E. Lüdenscheid
    Lüdenscheid is a town in western Germany’s Sauerland region, historically noted for its role in World War II and known today for its metal and plastics industries.
  • 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_69d8839174188190909f190097207065 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3abee862c819086d9bf01e623a8ce completed April 18, 2026, 4:06 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00aaf7908481909af31fc2d02f33fb completed May 10, 2026, 3:57 p.m.
Created at: April 10, 2026, 5:21 a.m.