Triple

T10688628
Position Surface form Disambiguated ID Type / Status
Subject Knokke-Heist E251947 entity
Predicate hasPart P35 FINISHED
Object Knokke E251947 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: Knokke | Statement: [Knokke-Heist, hasPart, Knokke]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Knokke
Context triple: [Knokke-Heist, hasPart, Knokke]
  • A. Knokke-Heist chosen
    Knokke-Heist is a Belgian coastal resort town known for its beaches, upscale tourism, and proximity to the Dutch border.
  • B. Edegem
    Edegem is a municipality in the Belgian province of Antwerp, known as a residential suburb south of the city of Antwerp.
  • C. Schaerbeek
    Schaerbeek is a multicultural municipality in the Brussels-Capital Region of Belgium, known for its Art Nouveau architecture and urban character.
  • D. Koekelberg
    Koekelberg is a small municipality in the Brussels-Capital Region of Belgium, known for the National Basilica of the Sacred Heart that dominates its skyline.
  • E. Kleine-Brogel
    Kleine-Brogel is a village in the municipality of Peer in the Belgian province of Limburg, known for hosting a major military air base.
  • 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_69d6aa5bd7c08190a816e733b4045c23 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fd1aef888190ba92474af3a49e36 completed April 9, 2026, 1:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69d9889d1f988190938be54771161b00 completed April 10, 2026, 11:32 p.m.
Created at: April 8, 2026, 9:11 p.m.