Triple

T6630363
Position Surface form Disambiguated ID Type / Status
Subject Cologne Bonn metropolitan region E149906 entity
Predicate containsCity P294 FINISHED
Object Lohmar E688098 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: Lohmar | Statement: [Cologne Bonn metropolitan region, containsCity, Lohmar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lohmar
Context triple: [Cologne Bonn metropolitan region, containsCity, Lohmar]
  • A. Lohmar chosen
    Lohmar is a town in the Rhein-Sieg district of North Rhine-Westphalia, Germany, situated near Cologne and known for its green surroundings and residential character.
  • B. Andernach
    Andernach is a historic German town on the Rhine River in Rhineland-Palatinate, known for its medieval architecture and one of the world’s highest cold-water geysers.
  • C. Fritzlar
    Fritzlar is a historic town in northern Hesse, Germany, known for its well-preserved medieval old town and its significance in early German Christian history.
  • D. Lemgo
    Lemgo is a historic town in the Lippe district of North Rhine-Westphalia, Germany, known for its well-preserved medieval architecture and Hanseatic heritage.
  • E. Boppard
    Boppard is a historic town on the Rhine River in Germany, renowned for its well-preserved medieval architecture, wine culture, and scenic river landscapes.
  • 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_69c9952ebfec819096a393b1231a1703 completed March 29, 2026, 9:10 p.m.
Created at: March 27, 2026, 1:59 p.m.