Triple

T6630352
Position Surface form Disambiguated ID Type / Status
Subject Cologne Bonn metropolitan region E149906 entity
Predicate containsCity P294 FINISHED
Object Bergisch Gladbach E584520 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: Bergisch Gladbach | Statement: [Cologne Bonn metropolitan region, containsCity, Bergisch Gladbach]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bergisch Gladbach
Context triple: [Cologne Bonn metropolitan region, containsCity, Bergisch Gladbach]
  • A. Bergisch Gladbach chosen
    Bergisch Gladbach is a city in North Rhine-Westphalia, western Germany, known for its paper industry, proximity to Cologne, and surrounding Bergisches Land countryside.
  • B. Mönchengladbach
    Mönchengladbach is a city in western Germany known for its textile industry heritage and its football club Borussia Mönchengladbach.
  • C. Remscheid
    Remscheid is a city in North Rhine-Westphalia, Germany, known historically for its metalworking industry and as the birthplace of physicist Wilhelm Röntgen.
  • D. Gelsenkirchen
    Gelsenkirchen is a city in western Germany known for its strong football culture and modern stadium, Veltins-Arena, home to FC Schalke 04.
  • E. Krefeld
    Krefeld is a city in western Germany near the Rhine River, known historically for its textile and silk industry.
  • 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_69c6cbeb04348190957b8e5f098b72bf completed March 27, 2026, 6:26 p.m.
Created at: March 27, 2026, 1:59 p.m.