Triple

T13679437
Position Surface form Disambiguated ID Type / Status
Subject Dinslaken E327959 entity
Predicate hasNeighbouringMunicipality P224 FINISHED
Object Voerde E886732 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: Voerde | Statement: [Dinslaken, hasNeighbouringMunicipality, Voerde]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Voerde
Context triple: [Dinslaken, hasNeighbouringMunicipality, Voerde]
  • A. Voerde chosen
    Voerde is a town in the Wesel district of North Rhine-Westphalia, Germany, situated on the Lower Rhine in the Ruhr region.
  • B. Friesoythe
    Friesoythe is a small town in Lower Saxony, Germany, known for its rural character and location within the Cloppenburg district.
  • C. Werl
    Werl is a town in North Rhine-Westphalia, Germany, known for its historical significance and regional correctional facility.
  • D. Soest
    Soest is a Dutch town and municipality in the central Netherlands known for its green surroundings and proximity to the Utrechtse Heuvelrug.
  • E. Soest
    Soest is a historic town in North Rhine-Westphalia, Germany, known for its well-preserved medieval architecture and former significance as a Hanseatic trading center.
  • 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_69d8076f1fa8819094664a59b55010df completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc66cbb088190907cb89dda8e4ebd completed April 12, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7944347a08190bc1386e78ddb3e71 completed May 3, 2026, 6:30 p.m.
Created at: April 9, 2026, 9:53 p.m.