Triple

T5000548
Position Surface form Disambiguated ID Type / Status
Subject Volkeraksluizen E112360 entity
Predicate nearbyCity P350 FINISHED
Object Bergen op Zoom E77581 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: Bergen op Zoom | Statement: [Volkeraksluizen, nearbyCity, Bergen op Zoom]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bergen op Zoom
Context triple: [Volkeraksluizen, nearbyCity, Bergen op Zoom]
  • A. Bergen op Zoom chosen
    Bergen op Zoom is a historic city in the Dutch province of North Brabant, known for its medieval center, fortifications, and location near the Scheldt estuary.
  • B. Blokzijl
    Blokzijl is a historic former trading town and harbor in the Dutch province of Overijssel, known for its picturesque canals and well-preserved old center.
  • C. De Baarsjes
    De Baarsjes is a residential neighborhood in Amsterdam, Netherlands, known for its diverse population, early 20th-century architecture, and canalside urban character.
  • D. De Akkers
    De Akkers is a metro station in Spijkenisse, Netherlands, serving as a terminus on the Rotterdam Metro network.
  • E. Krimpen aan den IJssel
    Krimpen aan den IJssel is a Dutch town and municipality situated along the Hollandse IJssel river, forming part of the Rotterdam metropolitan area.
  • 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_69bd4432b32c81909f3b3c6bd10f0653 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd72bd90948190bf6ca21237402949 completed March 20, 2026, 4:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69be8a3a5a108190a028920b1ae0be7a completed March 21, 2026, 12:08 p.m.
Created at: March 20, 2026, 1:34 p.m.