Triple

T8794566
Position Surface form Disambiguated ID Type / Status
Subject N208 road E209255 entity
Predicate passesThrough P225 FINISHED
Object Santpoort E408912 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: Santpoort | Statement: [N208 road, passesThrough, Santpoort]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Santpoort
Context triple: [N208 road, passesThrough, Santpoort]
  • A. Kaatsheuvel
    Kaatsheuvel is a Dutch village best known as the home of the Efteling theme park, one of Europe’s largest and oldest amusement parks.
  • B. Blokhuispoort
    Blokhuispoort is a former prison complex in Leeuwarden, Netherlands, that has been transformed into a cultural and creative hub with museums, studios, and public spaces.
  • C. Numansdorp
    Numansdorp is a village in the western Netherlands known for its rural character and location on the island of Hoeksche Waard.
  • D. Santpoort-Noord chosen
    Santpoort-Noord is a village in the Dutch province of North Holland, situated within the municipality of Velsen near the North Sea coast.
  • E. Koepoort
    Koepoort is a historic Dutch city gate known as one of the traditional entrances to a fortified town in the Netherlands.
  • 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_69ca836240888190a62b262e56a69d2f completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5fa0c6008190a5c4d87510ad5bbd completed March 31, 2026, 11:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf6f532ed48190a21996f865428831 completed April 3, 2026, 7:42 a.m.
Created at: March 30, 2026, 6:43 p.m.