Triple

T22415513
Position Surface form Disambiguated ID Type / Status
Subject Netersel E554112 entity
Predicate locatedInRegion P40 FINISHED
Object Kempen 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: Kempen | Statement: [Netersel, locatedInRegion, Kempen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kempen
Context triple: [Netersel, locatedInRegion, Kempen]
  • A. 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.
  • B. Kempen, Germany
    Kempen is a historic town in western Germany’s North Rhine-Westphalia region, known for its well-preserved medieval center and cultural ties to other European cities.
  • C. Kampenhout
    Kampenhout is a municipality in the Flemish Brabant province of Belgium, known for its rural character and proximity to Brussels.
  • D. Rolandswerth
    Rolandswerth is a district of the German town of Remagen, situated along the Rhine River in the state of Rhineland-Palatinate.
  • E. Herkinge
    Herkinge is a small settlement located in the Dutch province of South Holland.
  • 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_69e11e4e6ce8819085a1e06d886bf21c completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f1594615f881909688b02548ee83eb completed April 29, 2026, 1:05 a.m.
Created at: April 16, 2026, 8:46 p.m.