Triple

T17053043
Position Surface form Disambiguated ID Type / Status
Subject Losser E413748 entity
Predicate hasHamlet P12354 FINISHED
Object Zandbergen
Zandbergen is a small hamlet in the municipality of Losser in the province of Overijssel in the eastern Netherlands.
E1251075 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: Zandbergen | Statement: [Losser, hasHamlet, Zandbergen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zandbergen
Context triple: [Losser, hasHamlet, Zandbergen]
  • A. Zandbergen
    Zandbergen is a village in East Flanders, Belgium, that forms part of the municipality of Geraardsbergen.
  • B. Woudenberg
    Woudenberg is a small Dutch municipality and town located in the central Netherlands.
  • C. Destelbergen
    Destelbergen is a municipality in the Belgian province of East Flanders, located just east of the city of Ghent.
  • D. Kortenberg
    Kortenberg is a municipality in the Flemish Brabant province of Belgium, located between Brussels and Leuven and known for its residential character and green surroundings.
  • E. Rotselaar
    Rotselaar is a municipality in the Flemish Brabant province of Belgium, known for its residential character and proximity to the city of Leuven.
  • 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: Zandbergen
Triple: [Losser, hasHamlet, Zandbergen]
Generated description
Zandbergen is a small hamlet in the municipality of Losser in the province of Overijssel in the eastern Netherlands.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Zandbergen
Target entity description: Zandbergen is a small hamlet in the municipality of Losser in the province of Overijssel in the eastern Netherlands.
  • A. Zandbergen
    Zandbergen is a village in East Flanders, Belgium, that forms part of the municipality of Geraardsbergen.
  • B. Woudenberg
    Woudenberg is a small Dutch municipality and town located in the central Netherlands.
  • C. Destelbergen
    Destelbergen is a municipality in the Belgian province of East Flanders, located just east of the city of Ghent.
  • D. Kortenberg
    Kortenberg is a municipality in the Flemish Brabant province of Belgium, located between Brussels and Leuven and known for its residential character and green surroundings.
  • E. Rotselaar
    Rotselaar is a municipality in the Flemish Brabant province of Belgium, known for its residential character and proximity to the city of Leuven.
  • 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_69d886cde3d481908d4d01ba88ba7eb7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3daa491008190ad013ee37532aa51 completed April 18, 2026, 7:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0139f346f0819094a430a11e361bac completed May 11, 2026, 2:07 a.m.
NEDg Description generation batch_6a013a9e70c8819081b11ad8db246223 completed May 11, 2026, 2:10 a.m.
NED2 Entity disambiguation (via description) batch_6a013b6824888190853cf36548507e1b completed May 11, 2026, 2:14 a.m.
Created at: April 10, 2026, 5:34 a.m.