Triple

T1426415
Position Surface form Disambiguated ID Type / Status
Subject West Flanders E30340 entity
Predicate hasMunicipality P847 FINISHED
Object Roeselare E251142 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: Roeselare | Statement: [West Flanders, hasMunicipality, Roeselare]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Roeselare
Context triple: [West Flanders, hasMunicipality, Roeselare]
  • A. Roeselare chosen
    Roeselare is a city in western Belgium known as an economic and commercial center in the province of West Flanders.
  • B. Vilvoorde
    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.
  • C. Hasselt
    Hasselt is a historic small city in the Dutch province of Overijssel, known for its medieval center and canals.
  • D. Hasselt
    Hasselt is a city in northeastern Belgium that serves as the capital of the province of Limburg in the Flemish region.
  • E. 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.
  • 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_69a498fb823c8190a67ce4c4837e641a completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c4be7d208190bcfb46239bd72e56 completed March 1, 2026, 10:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69ae95d2a03881908433209da4af73a2 completed March 9, 2026, 9:41 a.m.
Created at: March 1, 2026, 8 p.m.