Triple

T5658841
Position Surface form Disambiguated ID Type / Status
Subject Flemish Limburg E124685 entity
Predicate hasMunicipality P847 FINISHED
Object Zonhoven
Zonhoven is a municipality in the Belgian province of Limburg, known for its green surroundings and proximity to the city of Hasselt.
E632155 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: Zonhoven | Statement: [Flemish Limburg, hasMunicipality, Zonhoven]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zonhoven
Context triple: [Flemish Limburg, hasMunicipality, Zonhoven]
  • A. 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.
  • B. Rupelmonde
    Rupelmonde is a village in Belgium best known as the birthplace of the renowned cartographer Gerardus Mercator.
  • C. Lembeek
    Lembeek is a village in the Belgian municipality of Halle, located along the Senne River in the province of Flemish Brabant.
  • D. Oudenarde
    Oudenarde (Oudenaarde) is a historic town in East Flanders, Belgium, known for its medieval architecture, tapestry production, and role in early modern European conflicts.
  • E. Borgerhout
    Borgerhout is a densely populated, multicultural district of the Belgian city of Antwerp, known for its vibrant street life and diverse communities.
  • 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: Zonhoven
Triple: [Flemish Limburg, hasMunicipality, Zonhoven]
Generated description
Zonhoven is a municipality in the Belgian province of Limburg, known for its green surroundings and proximity to the city of Hasselt.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Zonhoven
Target entity description: Zonhoven is a municipality in the Belgian province of Limburg, known for its green surroundings and proximity to the city of Hasselt.
  • A. 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.
  • B. Rupelmonde
    Rupelmonde is a village in Belgium best known as the birthplace of the renowned cartographer Gerardus Mercator.
  • C. Lembeek
    Lembeek is a village in the Belgian municipality of Halle, located along the Senne River in the province of Flemish Brabant.
  • D. Oudenarde
    Oudenarde (Oudenaarde) is a historic town in East Flanders, Belgium, known for its medieval architecture, tapestry production, and role in early modern European conflicts.
  • E. Borgerhout
    Borgerhout is a densely populated, multicultural district of the Belgian city of Antwerp, known for its vibrant street life and diverse communities.
  • 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_69c0082774a481909d7e63fb2aad56ac completed March 22, 2026, 3:17 p.m.
NER Named-entity recognition batch_69c022fd9b148190bd4aa9c43500949f completed March 22, 2026, 5:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69c761601814819092889a7d6ba74a02 completed March 28, 2026, 5:04 a.m.
NEDg Description generation batch_69c76265a77881908d3e698e2e1c53c5 completed March 28, 2026, 5:08 a.m.
NED2 Entity disambiguation (via description) batch_69c762d1be208190ae5831c2a5e5655c completed March 28, 2026, 5:10 a.m.
Created at: March 22, 2026, 3:42 p.m.