Triple

T4003343
Position Surface form Disambiguated ID Type / Status
Subject Wesel E89464 entity
Predicate hasLandmark P105 FINISHED
Object Pegeluhr Wesel E89464 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: Pegeluhr Wesel | Statement: [Wesel, hasLandmark, Pegeluhr Wesel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pegeluhr Wesel
Context triple: [Wesel, hasLandmark, Pegeluhr Wesel]
  • A. Rheinhausen
    Rheinhausen is a district of the German city of Duisburg, located on the western bank of the Rhine in North Rhine-Westphalia.
  • B. 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.
  • C. Rheydt
    Rheydt is a district of the German city of Mönchengladbach in North Rhine-Westphalia, historically an independent town in the Rhineland.
  • D. Wesel chosen
    Wesel is a historic city in western Germany, located on the Rhine River in the state of North Rhine-Westphalia.
  • E. Radevormwald
    Radevormwald is a small historic town in North Rhine-Westphalia, western Germany, known for its hilly Bergisches Land landscape and traditional textile and metalworking 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_69aed9585e788190bec2d39deba3750f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefa5de98c8190a95b21a75fffdef3 completed March 9, 2026, 4:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69b54c61bad48190a5115dbd4a3457d6 completed March 14, 2026, 11:54 a.m.
Created at: March 9, 2026, 3:34 p.m.