Triple

T21417798
Position Surface form Disambiguated ID Type / Status
Subject Berghuizen E528351 entity
Predicate hasSubdivisionName P12497 FINISHED
Object De Wolden 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: De Wolden | Statement: [Berghuizen, hasSubdivisionName, De Wolden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: De Wolden
Context triple: [Berghuizen, hasSubdivisionName, De Wolden]
  • A. De Wolden chosen
    De Wolden is a rural municipality in the northeastern Netherlands known for its scenic landscapes, small villages, and agricultural character.
  • B. Holwierde
    Holwierde is a small village in the province of Groningen in the northern Netherlands, known for its historic terp (artificial dwelling mound) and medieval church.
  • C. Wassenberg
    Wassenberg is a historic town in western Germany near the Dutch border, known for its medieval origins and association with the noble House of Wassenberg.
  • D. Woudenberg
    Woudenberg is a small Dutch municipality and town located in the central Netherlands.
  • E. Overdinkel
    Overdinkel is a village in the municipality of Losser in the province of Overijssel in the eastern Netherlands, near the German border.
  • 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_69e0c454c248819093425d1099101c09 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ee62d29f948190b820c92014d1c53a completed April 26, 2026, 7:09 p.m.
Created at: April 16, 2026, 5:46 p.m.