Triple

T21555371
Position Surface form Disambiguated ID Type / Status
Subject Mödrath E531876 entity
Predicate hasLocalGovernment P2820 FINISHED
Object Kerpen city council NE NERFINISHED

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: Kerpen city council | Statement: [Mödrath, hasLocalGovernment, Kerpen city council]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kerpen city council
Context triple: [Mödrath, hasLocalGovernment, Kerpen city council]
  • A. Kerpen chosen
    Kerpen is a town in North Rhine-Westphalia, Germany, known as the birthplace of Formula 1 champion Michael Schumacher and for its proximity to Cologne.
  • B. Kürten
    Kürten is a small municipality in North Rhine-Westphalia, Germany, situated in the hilly Bergisches Land region east of Cologne.
  • C. Neunkirchen
    Neunkirchen is an industrial town in Austria’s Lower Austria region, known historically for its manufacturing and metalworking industries.
  • D. Neunkirchen
    Neunkirchen is a town in southwestern Germany known as one of the major urban centers and former industrial hubs of the state of Saarland.
  • E. Kierspe
    Kierspe is a small town in the Märkischer Kreis district of North Rhine-Westphalia, western Germany, known for its rural character and location in the Sauerland region.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c460232c81908de2c3819d17c00e completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69eed2df48c88190894b6b08a5cb6390 completed April 27, 2026, 3:07 a.m.
Created at: April 16, 2026, 6:29 p.m.