Triple

T13964303
Position Surface form Disambiguated ID Type / Status
Subject William Louis, Count of Nassau-Dillenburg E335880 entity
Predicate region P40 FINISHED
Object Drenthe E171047 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: Drenthe | Statement: [William Louis, Count of Nassau-Dillenburg, region, Drenthe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Drenthe
Context triple: [William Louis, Count of Nassau-Dillenburg, region, Drenthe]
  • A. Drenthe chosen
    Drenthe is a rural province in the northeastern Netherlands known for its prehistoric dolmens, heathlands, and forests.
  • B. Midden-Drenthe
    Midden-Drenthe is a rural municipality in the northeastern Netherlands known for its villages, natural landscapes, and location in the province of Drenthe.
  • C. Overijssel
    Overijssel is a province in the eastern Netherlands known for its historic Hanseatic cities, rivers, and varied landscapes of forests, heathlands, and farmland.
  • D. Flevoland
    Flevoland is the youngest Dutch province, largely created through land reclamation from the IJsselmeer in the central Netherlands.
  • E. Gelderland
    Gelderland is a large province in the eastern Netherlands known for its varied landscapes, including the forested Veluwe region and the river areas along the Rhine, Waal, and IJssel.
  • 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_69d81c61f3508190aaf2ca0dc0002c59 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2e7e24f08190ba939a8044860033 completed April 14, 2026, 12:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a014819dfbc8190b39a10647f9ba64c completed May 11, 2026, 3:08 a.m.
Created at: April 9, 2026, 10:18 p.m.