Triple

T9870758
Position Surface form Disambiguated ID Type / Status
Subject Bad Karlshafen E239949 entity
Predicate locatedOnRiver P165 FINISHED
Object Diemel E255721 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: Diemel | Statement: [Bad Karlshafen, locatedOnRiver, Diemel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Diemel
Context triple: [Bad Karlshafen, locatedOnRiver, Diemel]
  • A. Diemel chosen
    The Diemel is a river in central Germany that flows through Hesse and North Rhine-Westphalia before joining the Weser.
  • B. Rhens
    Rhens is a historic town on the Rhine River in western Germany, known for its medieval role as a meeting place of the prince-electors of the Holy Roman Empire.
  • C. Rheine
    Rheine is a German city in the state of North Rhine-Westphalia, known for its historical town center and location along the River Ems.
  • D. Dommel
    The Dommel is a river in the southern Netherlands and northern Belgium that flows through cities including Eindhoven before joining the Dieze.
  • E. Meuse
    The Meuse is a major European river flowing through France, Belgium, and the Netherlands, historically important for transport, trade, and the development of surrounding regions.
  • 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_69ca84e7506c819095cbde4ff16512bb completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb3d62628819094786a49b9bcd09b completed April 2, 2026, 12:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69e15435faa881909b1a124f8027deeb completed April 16, 2026, 9:27 p.m.
Created at: March 30, 2026, 8:36 p.m.