Triple

T5807473
Position Surface form Disambiguated ID Type / Status
Subject Achterhoek E128780 entity
Predicate borderWith P224 FINISHED
Object Salland E128791 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: Salland | Statement: [Achterhoek, borderWith, Salland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Salland
Context triple: [Achterhoek, borderWith, Salland]
  • A. Salland chosen
    Salland is a historical and rural region in the Dutch province of Overijssel, known for its scenic landscapes, small towns, and agricultural character.
  • B. Vechta
    Vechta is a town in Lower Saxony, Germany, known for its historical significance, university, and annual Stoppelmarkt fair.
  • C. Sappemeer
    Sappemeer is a town in the province of Groningen in the northeastern Netherlands, historically known for its peat colonies and waterways.
  • D. Flevoland
    Flevoland is the youngest Dutch province, largely created through land reclamation from the IJsselmeer in the central Netherlands.
  • E. Zuiderwoude
    Zuiderwoude is a small historic village in the Dutch province of North Holland, known for its traditional wooden houses and watery polder landscape near Amsterdam.
  • 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_69c0084788848190bcf71f6bc5d71597 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c02b17417081908779741b9bfbb720 completed March 22, 2026, 5:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69c107e64edc819080b3ebf9b9137749 completed March 23, 2026, 9:29 a.m.
Created at: March 22, 2026, 3:52 p.m.