Triple

T22657318
Position Surface form Disambiguated ID Type / Status
Subject De Kempen E559261 entity
Predicate hasSettlement P1068 FINISHED
Object Hulshout 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: Hulshout | Statement: [De Kempen, hasSettlement, Hulshout]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hulshout
Context triple: [De Kempen, hasSettlement, Hulshout]
  • A. Hulshout chosen
    Hulshout is a small municipality in the Belgian province of Antwerp, known for its rural character and village communities.
  • B. Hudde
    Hudde is a Dutch surname most notably associated with Johannes Hudde, a 17th-century mathematician and mayor of Amsterdam known for his contributions to algebra and optics.
  • C. Harskamp
    Harskamp is a village in the Dutch province of Gelderland, known for its rural character and proximity to the Hoge Veluwe National Park.
  • D. Harksheide
    Harksheide was a former municipality in Schleswig-Holstein, Germany, that later became part of the city of Norderstedt.
  • E. Schollevaar
    Schollevaar is a residential district in the Dutch municipality of Capelle aan den IJssel, located near Rotterdam in the 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_69e245489dd88190b1f674acf61c8769 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f1765c62bc8190b3fcde76d6b6dfb6 completed April 29, 2026, 3:09 a.m.
Created at: April 17, 2026, 3:06 p.m.