Triple

T5893357
Position Surface form Disambiguated ID Type / Status
Subject Boxtel E131042 entity
Predicate region P40 FINISHED
Object Kempenland E261690 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: Kempenland | Statement: [Boxtel, region, Kempenland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kempenland
Context triple: [Boxtel, region, Kempenland]
  • A. Dinkelland
    Dinkelland is a rural municipality in the eastern Netherlands, located in the Twente region of the province of Overijssel near the German border.
  • B. Kempen chosen
    Kempen is a historical region in the Low Countries, spanning parts of present-day Belgium and the Netherlands, known for its sandy soils, heathlands, and rural character.
  • C. Lansingerland
    Lansingerland is a Dutch municipality in the province of South Holland, known for its suburban communities and greenhouse horticulture near the city of Rotterdam.
  • D. Kamperland
    Kamperland is a village in the Dutch province of Zeeland, located on the island of Noord-Beveland and known as a coastal and recreational destination.
  • E. Rietlanden
    Rietlanden is a waterfront area in Amsterdam’s Eastern Docklands, known for its former industrial port functions and subsequent urban redevelopment.
  • 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_69c00857439c819095950754176aa58a completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c036b5c68481909fdcba428238c74d completed March 22, 2026, 6:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0c000dfb481908cf37e5c143f4cae completed March 23, 2026, 4:22 a.m.
Created at: March 22, 2026, 3:58 p.m.