Triple

T16763430
Position Surface form Disambiguated ID Type / Status
Subject Lackhausen E407403 entity
Predicate hasMunicipalAuthority P3379 FINISHED
Object city of Wesel E972812 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: city of Wesel | Statement: [Lackhausen, hasMunicipalAuthority, city of Wesel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: city of Wesel
Context triple: [Lackhausen, hasMunicipalAuthority, city of Wesel]
  • A. City of Wesel chosen
    The City of Wesel is a historic German town on the Lower Rhine that became an important Reformation and trading center in the early modern period.
  • B. district of Wesel
    The district of Wesel is an administrative district (Kreis) in the German state of North Rhine-Westphalia, located along the lower Rhine and encompassing a mix of industrial towns and rural communities.
  • C. City of Essen
    The City of Essen is a major urban center in Germany’s Ruhr area, historically significant as a medieval ecclesiastical seat and later as an important industrial and coal-mining hub.
  • D. Wuppertal
    Wuppertal is a city in western Germany known for its steep slopes, extensive parks, and the unique suspended monorail Wuppertal Schwebebahn.
  • E. Oberhausen
    Oberhausen is an industrial city in Germany’s Ruhr region, historically known for its coal and steel production and heavily affected by World War II bombing.
  • 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_6a00cfc0dcd081909f715e0f2aad67c7 completed May 10, 2026, 6:34 p.m.
Created at: April 10, 2026, 5:21 a.m.