Triple

T9211910
Position Surface form Disambiguated ID Type / Status
Subject Machelen E221140 entity
Predicate hasNeighbour P5707 FINISHED
Object Vilvoorde E26610 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: Vilvoorde | Statement: [Machelen, hasNeighbour, Vilvoorde]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vilvoorde
Context triple: [Machelen, hasNeighbour, Vilvoorde]
  • A. Vilvoorde chosen
    Vilvoorde is a city in the Flemish Region of Belgium, located just north of Brussels and known as part of the capital’s broader metropolitan area.
  • B. Edegem
    Edegem is a municipality in the Belgian province of Antwerp, known as a residential suburb south of the city of Antwerp.
  • C. Mechelen
    Mechelen is a historic city in the Flemish region of Belgium, known for its rich architectural heritage, medieval center, and prominent role in the Low Countries’ political and religious history.
  • D. Hasselt
    Hasselt is a historic small city in the Dutch province of Overijssel, known for its medieval center and canals.
  • E. Hasselt
    Hasselt is a city in northeastern Belgium that serves as the capital of the province of Limburg in the Flemish region.
  • 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_69ca83e9d0e081908bdb71097201a06c completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccd9b69838819088f33ca995fce222 completed April 1, 2026, 8:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69d19f50f1c4819099a9c511f58e9873 completed April 4, 2026, 11:31 p.m.
Created at: March 30, 2026, 7:27 p.m.