Triple

T22657302
Position Surface form Disambiguated ID Type / Status
Subject De Kempen E559261 entity
Predicate hasSettlement P1068 FINISHED
Object Herentals 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: Herentals | Statement: [De Kempen, hasSettlement, Herentals]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Herentals
Context triple: [De Kempen, hasSettlement, Herentals]
  • A. Herentals chosen
    Herentals is a historic city in the Belgian province of Antwerp, known for its medieval architecture and role as a regional commercial center.
  • B. Knokke-Heist
    Knokke-Heist is a Belgian coastal resort town known for its beaches, upscale tourism, and proximity to the Dutch border.
  • C. Badhoevedorp
    Badhoevedorp is a village in North Holland, Netherlands, located just southwest of Amsterdam and known for its proximity to Schiphol Airport.
  • D. ’s-Heerenbroek
    ’s-Heerenbroek is a small village in the Netherlands, known as the birthplace of mathematician Diederik Johannes Korteweg.
  • E. Bezuidenhout
    Bezuidenhout is a neighborhood in The Hague, Netherlands, known for its residential character and proximity to major government and business districts.
  • 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.