Triple

T9930460
Position Surface form Disambiguated ID Type / Status
Subject Kaiser Wilhelm Museum E192633 entity
Predicate ownedBy P347 FINISHED
Object City of Krefeld E398502 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 Krefeld | Statement: [Kaiser Wilhelm Museum, ownedBy, City of Krefeld]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Krefeld
Context triple: [Kaiser Wilhelm Museum, ownedBy, City of Krefeld]
  • A. Krefeld chosen
    Krefeld is a city in western Germany near the Rhine River, known historically for its textile and silk industry.
  • B. 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.
  • C. Krefeld, Germany
    Krefeld, Germany is an industrial city in North Rhine-Westphalia known historically for its textile and silk production.
  • D. Kleve
    Kleve is a historic town in western Germany near the Dutch border, known for its medieval castle and role as the former capital of the Duchy of Cleves.
  • E. Remscheid
    Remscheid is a city in North Rhine-Westphalia, Germany, known historically for its metalworking industry and as the birthplace of physicist Wilhelm Röntgen.
  • 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_69ca82dd978c8190947124ab0d3315ac completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb5b4196881909a004091a4203c45 completed April 2, 2026, 12:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69d269d24ac4819081683e6ac5db7015 completed April 5, 2026, 1:55 p.m.
Created at: March 30, 2026, 8:43 p.m.