Triple

T6712992
Position Surface form Disambiguated ID Type / Status
Subject Kerpen E153193 entity
Predicate locatedIn P40 FINISHED
Object Cologne region E149906 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: Cologne region | Statement: [Kerpen, locatedIn, Cologne region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cologne region
Context triple: [Kerpen, locatedIn, Cologne region]
  • A. Kaiserslautern region
    The Kaiserslautern region is an area in the German state of Rhineland-Palatinate known for its city of Kaiserslautern, surrounding rural districts, and strong football and military presence.
  • B. Bergisches Land
    Bergisches Land is a hilly, forested region in western Germany, east of the Rhine, known for its river valleys, reservoirs, and historic industrial towns.
  • C. Cologne Bonn metropolitan region chosen
    The Cologne Bonn metropolitan region is a major urban and economic area in western Germany centered around the cities of Cologne and Bonn and their surrounding municipalities.
  • D. Rhine-Weser region
    The Rhine-Weser region is a historical area in western Germany associated with the early homeland and formation of the Frankish people.
  • E. South Westphalia
    South Westphalia is a region in western Germany known for its mixed industrial and rural character, encompassing parts of North Rhine-Westphalia including the Arnsberg area.
  • 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_69c68809b4608190a2509ddb5ab87f05 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d121a92c8190a03f384a8aba84da completed March 27, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69c72f8255ac81909e7732947d2a5f53 completed March 28, 2026, 1:31 a.m.
Created at: March 27, 2026, 2:07 p.m.