Triple

T2429321
Position Surface form Disambiguated ID Type / Status
Subject Rhöndorf E52804 entity
Predicate partOf P40 FINISHED
Object Bad Honnef urban area E53223 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: Bad Honnef urban area | Statement: [Rhöndorf, partOf, Bad Honnef urban area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bad Honnef urban area
Context triple: [Rhöndorf, partOf, Bad Honnef urban area]
  • A. Bad Honnef chosen
    Bad Honnef is a spa town on the Rhine in North Rhine-Westphalia, Germany, known for its scenic setting near the Siebengebirge hills and its historical associations with prominent political figures.
  • B. Lünen
    Lünen is a town in North Rhine-Westphalia, Germany, known as an industrial and commuter city in the Ruhr area.
  • C. Bergkamen
    Bergkamen is a town in North Rhine-Westphalia, Germany, known for its coal mining heritage and post-war planned urban development.
  • D. Radevormwald
    Radevormwald is a small historic town in North Rhine-Westphalia, western Germany, known for its hilly Bergisches Land landscape and traditional textile and metalworking industries.
  • E. Hattingen
    Hattingen is a historic town in North Rhine-Westphalia, Germany, known for its well-preserved medieval old town and its location in the Ruhr industrial region.
  • 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_69ab4959bcc0819083246f9fb10439e3 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abc99e1b548190aca9a0ba72a9b0f7 completed March 7, 2026, 6:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69aef0a5fc208190a2479de4b1344759 completed March 9, 2026, 4:09 p.m.
Created at: March 6, 2026, 9:43 p.m.