Triple

T7371097
Position Surface form Disambiguated ID Type / Status
Subject Kanaal Brussel-Schelde E170004 entity
Predicate flowsThrough P225 FINISHED
Object Willebroek E646321 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: Willebroek | Statement: [Kanaal Brussel-Schelde, flowsThrough, Willebroek]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Willebroek
Context triple: [Kanaal Brussel-Schelde, flowsThrough, Willebroek]
  • A. Willebroek chosen
    Willebroek is a municipality in northern Belgium known for its canal connections and location between Brussels and Antwerp.
  • B. Borgerhout
    Borgerhout is a densely populated, multicultural district of the Belgian city of Antwerp, known for its vibrant street life and diverse communities.
  • C. Lembeek
    Lembeek is a village in the Belgian municipality of Halle, located along the Senne River in the province of Flemish Brabant.
  • D. Diepenbeek
    Diepenbeek is a municipality in the Belgian province of Limburg, known for its blend of residential areas, industry, and the campus of Hasselt University.
  • E. Zonhoven
    Zonhoven is a municipality in the Belgian province of Limburg, known for its green surroundings and proximity to the city of Hasselt.
  • 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_69c68a5bfaac81909ce7f001dfb70c76 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f182df5c81908964fbaa3f8ec790 completed March 27, 2026, 9:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69c9ea3f8a20819096ae41db21c8da0e completed March 30, 2026, 3:13 a.m.
Created at: March 27, 2026, 3:07 p.m.