Triple

T11288682
Position Surface form Disambiguated ID Type / Status
Subject De Marne E267264 entity
Predicate hadSettlement P16159 FINISHED
Object Pieterburen E599127 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: Pieterburen | Statement: [De Marne, hadSettlement, Pieterburen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pieterburen
Context triple: [De Marne, hadSettlement, Pieterburen]
  • A. Pieterburen chosen
    Pieterburen is a village in the Dutch province of Groningen, best known for its seal rehabilitation center and as a starting point for mudflat hiking tours across the Wadden Sea.
  • B. Oudeschild
    Oudeschild is a small fishing village and harbor on the Dutch island of Texel, known for its maritime heritage and coastal tourism.
  • C. Papendrecht
    Papendrecht is a Dutch town situated on the river Merwede in the province of South Holland, known for its residential character and proximity to the city of Dordrecht.
  • D. Hoogeveen
    Hoogeveen is a town and municipality in the northeastern Netherlands known for its historical peat colonies and location in the province of Drenthe.
  • E. Alblasserdam
    Alblasserdam is a town and municipality in the western Netherlands, situated along the Noord River and known for its proximity to the Kinderdijk windmills.
  • 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_69d6aac993a08190a6f36445ebaf9a43 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e98875a08190b8509fe55e49d52d completed April 9, 2026, 6:01 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00679214208190a9ee4cce882f59cb completed May 10, 2026, 11:10 a.m.
Created at: April 8, 2026, 9:32 p.m.