Triple

T13713587
Position Surface form Disambiguated ID Type / Status
Subject Schengen E328834 entity
Predicate hasTwinTown P919 FINISHED
Object Boussu
Boussu is a municipality in the province of Hainaut in Wallonia, Belgium.
 E1068190 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: Boussu | Statement: [Schengen, hasTwinTown, Boussu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Boussu
Context triple: [Schengen, hasTwinTown, Boussu]
  • A. Boussens
    Boussens is a commune in southwestern France, located in the Haute-Garonne department within the Occitanie region.
  • B. Booué
    Booué is a small town in central Gabon situated along the Ogooué River, known as a local transport and trading hub in the region.
  • C. Béraud
    Béraud is a French surname most notably associated with the 19th-century painter Jean Béraud, renowned for his vivid depictions of Parisian life during the Belle Époque.
  • D. Patouès
    Patouès is a regional Romance dialect of the Franco-Provençal language traditionally spoken in parts of France, Switzerland, and Italy.
  • E. Vauvert
    Vauvert is a commune in southern France known for its location in the Gard department near the Camargue region.
  • 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: Boussu
Triple: [Schengen, hasTwinTown, Boussu]
Generated description
Boussu is a municipality in the province of Hainaut in Wallonia, Belgium.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Boussu
Target entity description: Boussu is a municipality in the province of Hainaut in Wallonia, Belgium.
  • A. Boussens
    Boussens is a commune in southwestern France, located in the Haute-Garonne department within the Occitanie region.
  • B. Booué
    Booué is a small town in central Gabon situated along the Ogooué River, known as a local transport and trading hub in the region.
  • C. Béraud
    Béraud is a French surname most notably associated with the 19th-century painter Jean Béraud, renowned for his vivid depictions of Parisian life during the Belle Époque.
  • D. Patouès
    Patouès is a regional Romance dialect of the Franco-Provençal language traditionally spoken in parts of France, Switzerland, and Italy.
  • E. Vauvert
    Vauvert is a commune in southern France known for its location in the Gard department near the Camargue region.
  • 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_69d80770b9bc81909f70c8c317d53cff completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dd4395e8c0819098719c8cd344aa33 completed April 13, 2026, 7:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7c6fcddf08190bee3dce22be39a34 completed May 3, 2026, 10:06 p.m.
NEDg Description generation batch_69f7c93a3d0c8190a6417f0db54119f5 completed May 3, 2026, 10:16 p.m.
NED2 Entity disambiguation (via description) batch_69f7c9b2930c8190983f2c55a0dd35f6 completed May 3, 2026, 10:18 p.m.
Created at: April 9, 2026, 9:54 p.m.