Triple

T7620359
Position Surface form Disambiguated ID Type / Status
Subject Arrondissement of Antwerp E172475 entity
Predicate contains P35 FINISHED
Object Aartselaar
Aartselaar is a municipality in the Belgian province of Antwerp, known for its residential character and proximity to the city of Antwerp.
 E692457 NE FINISHED

How this triple was built (4 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: Aartselaar | Statement: [Arrondissement of Antwerp, contains, Aartselaar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Aartselaar
Context triple: [Arrondissement of Antwerp, contains, Aartselaar]
  • A. Roeselare
    Roeselare is a city in western Belgium known as an economic and commercial center in the province of West Flanders.
  • 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. Izegem
    Izegem is a town in the Belgian province of West Flanders, known historically for its shoe and brush industries.
  • E. 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.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Aartselaar
Triple: [Arrondissement of Antwerp, contains, Aartselaar]
Generated description
Aartselaar is a municipality in the Belgian province of Antwerp, known for its residential character and proximity to the city of Antwerp.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Aartselaar
Target entity description: Aartselaar is a municipality in the Belgian province of Antwerp, known for its residential character and proximity to the city of Antwerp.
  • A. Roeselare
    Roeselare is a city in western Belgium known as an economic and commercial center in the province of West Flanders.
  • 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. Izegem
    Izegem is a town in the Belgian province of West Flanders, known historically for its shoe and brush industries.
  • E. 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.
  • F. None of above. chosen

Provenance (5 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_69c699506b308190826894dab1d9ea86 completed March 27, 2026, 2:50 p.m.
NER Named-entity recognition batch_69c6fa62870c8190b17f44eb7a3ff2ad completed March 27, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69ca293158d4819091918490eec7eb5b completed March 30, 2026, 7:41 a.m.
NEDg Description generation batch_69ca2a1960bc81908f7ce7cf45bf08e2 completed March 30, 2026, 7:45 a.m.
NED2 Entity disambiguation (via description) batch_69ca2aae21688190bf04df7a43935420 completed March 30, 2026, 7:47 a.m.
Created at: March 27, 2026, 3:55 p.m.