Triple

T22565460
Position Surface form Disambiguated ID Type / Status
Subject Doldersum E557936 entity
Predicate hasNearbySettlement P4647 FINISHED
Object Vledder 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: Vledder | Statement: [Doldersum, hasNearbySettlement, Vledder]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vledder
Context triple: [Doldersum, hasNearbySettlement, Vledder]
  • A. Vledder chosen
    Vledder is a village in the Dutch province of Drenthe, known for its rural character and location within the municipality of Westerveld.
  • B. Vitlycke
    Vitlycke is a renowned Bronze Age rock carving site in Tanum, Sweden, noted for its extensive petroglyphs and archaeological significance.
  • C. Dverberg
    Dverberg is a small village and former municipal center located on the island of Andøya in Nordland county, Norway.
  • D. Vellberg
    Vellberg is a small historic town in the German state of Baden-Württemberg, known for its well-preserved medieval architecture and picturesque setting.
  • E. Veddesta
    Veddesta is an industrial and commercial area in Järfälla Municipality, northwest of central Stockholm, Sweden.
  • 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_69e11e5ae4ac8190b1f503457603d969 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15fa9ebc8819098d74fb41e14bd7e completed April 29, 2026, 1:32 a.m.
Created at: April 16, 2026, 8:52 p.m.