Triple

T21183364
Position Surface form Disambiguated ID Type / Status
Subject Roosendaal E522007 entity
Predicate formedByMergerOf P77 FINISHED
Object Roosendaal en Nispen NE NERFINISHED

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: Roosendaal en Nispen | Statement: [Roosendaal, formedByMergerOf, Roosendaal en Nispen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Roosendaal en Nispen
Context triple: [Roosendaal, formedByMergerOf, Roosendaal en Nispen]
  • A. Roosendaal chosen
    Roosendaal is a city in the southern Netherlands known as a regional center for commerce and transport near the Belgian border.
  • B. Nijkerk
    Nijkerk is a historic town and municipality in the Dutch province of Gelderland in the central Netherlands.
  • C. Weesp
    Weesp is a historic town in the province of North Holland in the Netherlands, known for its canals, fortified structures, and traditional Dutch architecture.
  • D. Naarden
    Naarden is a historic Dutch fortified town in North Holland, renowned for its well-preserved star-shaped fortifications and moats.
  • E. Woerden
    Woerden is a historic Dutch city and municipality in the central Netherlands, known for its medieval fortifications and traditional cheese market.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b50ef1d48190b063aa342667df22 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7301f7f1c81908686866fdee57127 completed April 21, 2026, 8:06 a.m.
Created at: April 16, 2026, 3:05 p.m.