Triple

T3351653
Position Surface form Disambiguated ID Type / Status
Subject Rockanje E70507 entity
Predicate partOfRegion P285 FINISHED
Object Voorne E213647 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: Voorne | Statement: [Rockanje, partOfRegion, Voorne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Voorne
Context triple: [Rockanje, partOfRegion, Voorne]
  • A. Voorne-Putten chosen
    Voorne-Putten is an island and region in the province of South Holland in the Netherlands, known for its mix of coastal landscapes, nature reserves, and historic towns.
  • B. Sappemeer
    Sappemeer is a town in the province of Groningen in the northeastern Netherlands, historically known for its peat colonies and waterways.
  • C. Vechta
    Vechta is a town in Lower Saxony, Germany, known for its historical significance, university, and annual Stoppelmarkt fair.
  • D. Monnickendam
    Monnickendam is a historic fishing town in North Holland, Netherlands, known for its well-preserved old harbor and traditional Dutch architecture.
  • E. Oegstgeest
    Oegstgeest is a suburban town in the western Netherlands, known for its leafy residential character and proximity to the city of Leiden.
  • 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_69ad85a4ef7c8190a29e2bbd6fa454e4 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb221a7d8819086cd0f826eca0fe8 completed March 8, 2026, 5:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69b360a07dec819094b0645d0e2a91da completed March 13, 2026, 12:56 a.m.
Created at: March 8, 2026, 3:12 p.m.