Triple

T22207188
Position Surface form Disambiguated ID Type / Status
Subject Tervuren E548842 entity
Predicate hasSubdivision P747 FINISHED
Object Vossem
Vossem is a village in the Flemish Brabant province of Belgium, known as a sub-municipality of Tervuren.
 E1524395 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: Vossem | Statement: [Tervuren, hasSubdivision, Vossem]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Vossem
Context triple: [Tervuren, hasSubdivision, Vossem]
  • A. Vosso
    Vosso is a river in western Norway known for flowing through Voss municipality and contributing to the region’s scenic fjord landscape.
  • B. Voksa
    Voksa is a small Norwegian island located in Sande Municipality in Møre og Romsdal county, known for its coastal landscape and rural character.
  • C. Vos
    Vos is a Dutch surname borne by various notable individuals, including theologian Geerhardus Vos.
  • D. Vos
    Vos is a major Transformer city on the planet Cybertron, traditionally depicted as the militaristic home of the Decepticon-aligned Seekers.
  • E. Verran
    Verran is a former municipality in Trøndelag county, Norway, known for its rural landscapes, forestry, and fjord-side settlements.
  • 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: Vossem
Triple: [Tervuren, hasSubdivision, Vossem]
Generated description
Vossem is a village in the Flemish Brabant province of Belgium, known as a sub-municipality of Tervuren.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Vossem
Target entity description: Vossem is a village in the Flemish Brabant province of Belgium, known as a sub-municipality of Tervuren.
  • A. Vosso
    Vosso is a river in western Norway known for flowing through Voss municipality and contributing to the region’s scenic fjord landscape.
  • B. Voksa
    Voksa is a small Norwegian island located in Sande Municipality in Møre og Romsdal county, known for its coastal landscape and rural character.
  • C. Vos
    Vos is a Dutch surname borne by various notable individuals, including theologian Geerhardus Vos.
  • D. Vos
    Vos is a major Transformer city on the planet Cybertron, traditionally depicted as the militaristic home of the Decepticon-aligned Seekers.
  • E. Verran
    Verran is a former municipality in Trøndelag county, Norway, known for its rural landscapes, forestry, and fjord-side settlements.
  • 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_69e11e3f7e04819089806d81d5ac431e completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f12b2936a481909aa84c7983ed49ee completed April 28, 2026, 9:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0aa61b30248190b5097435ade9aea0 completed May 18, 2026, 5:39 a.m.
NEDg Description generation batch_6a0aa6d1f634819082d1edd70217b70c completed May 18, 2026, 5:42 a.m.
NED2 Entity disambiguation (via description) batch_6a0aa7879e048190bd4b8e7f7cfbaec4 completed May 18, 2026, 5:45 a.m.
Created at: April 16, 2026, 8:36 p.m.