Triple

T8534237
Position Surface form Disambiguated ID Type / Status
Subject Nissewaard E202035 entity
Predicate sharesIslandWith P5790 FINISHED
Object Voorne aan Zee E699983 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 aan Zee | Statement: [Nissewaard, sharesIslandWith, Voorne aan Zee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Voorne aan Zee
Context triple: [Nissewaard, sharesIslandWith, Voorne aan Zee]
  • A. Voorne aan Zee chosen
    Voorne aan Zee is a municipality in the Dutch province of South Holland that includes the historic port town of Hellevoetsluis and other nearby communities on the island of Voorne.
  • B. Voorne-Putten
    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.
  • C. Loosduinen
    Loosduinen is a district in the southwest of The Hague in the Netherlands, historically a separate village known for its former abbey and more rural character.
  • D. Londerzeel
    Londerzeel is a municipality in the Flemish Brabant province of Belgium, known for its residential character and proximity to both Brussels and Antwerp.
  • E. Wessum
    Wessum is a village and district within the town of Ahaus in the state of North Rhine-Westphalia, Germany.
  • 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_69ca832355b08190b8b6a4ab4a4a3554 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe6a0ccd4819097b41d0dfb1c5018 completed March 31, 2026, 3:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce890eb0b48190aa76cc955d00ec18 completed April 2, 2026, 3:19 p.m.
Created at: March 30, 2026, 6:17 p.m.