Triple

T6630351
Position Surface form Disambiguated ID Type / Status
Subject Cologne Bonn metropolitan region E149906 entity
Predicate containsCity P294 FINISHED
Object Solingen E286549 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: Solingen | Statement: [Cologne Bonn metropolitan region, containsCity, Solingen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Solingen
Context triple: [Cologne Bonn metropolitan region, containsCity, Solingen]
  • A. Solingen chosen
    Solingen is a city in western Germany renowned for its centuries-old blade-making tradition and production of high-quality knives and swords.
  • B. Remscheid
    Remscheid is a city in North Rhine-Westphalia, Germany, known historically for its metalworking industry and as the birthplace of physicist Wilhelm Röntgen.
  • C. Bergkamen
    Bergkamen is a town in North Rhine-Westphalia, Germany, known for its coal mining heritage and post-war planned urban development.
  • D. Bruchsal
    Bruchsal is a town in the state of Baden-Württemberg in southwestern Germany, known for its baroque palace and asparagus cultivation.
  • E. Hennef
    Hennef is a town in North Rhine-Westphalia, Germany, situated on the river Sieg near Bonn and known for its mix of residential areas, industry, and surrounding countryside.
  • 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_69c687ee50048190aa151765bef16193 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6afa5c9b48190b645be96d446d0ca completed March 27, 2026, 4:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c988df1e4c8190a46c971a3f9b2d49 completed March 29, 2026, 8:17 p.m.
Created at: March 27, 2026, 1:59 p.m.