Triple

T12443087
Position Surface form Disambiguated ID Type / Status
Subject Wattrelos E297324 entity
Predicate twinTown P1072 FINISHED
Object Mouscron E1027756 NE FINISHED

How this triple was built (2 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: Mouscron | Statement: [Wattrelos, twinTown, Mouscron]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mouscron
Context triple: [Wattrelos, twinTown, Mouscron]
  • A. Mouscron chosen
    Mouscron is a Belgian city in the province of Hainaut, near the French border in the region of Wallonia.
  • B. Gosselies
    Gosselies is a district of the city of Charleroi in Wallonia, Belgium, known for its proximity to Brussels South Charleroi Airport and its industrial and aeronautical activities.
  • C. Izegem
    Izegem is a town in the Belgian province of West Flanders, known historically for its shoe and brush industries.
  • D. Mechelen
    Mechelen is a historic city in the Flemish region of Belgium, known for its rich architectural heritage, medieval center, and prominent role in the Low Countries’ political and religious history.
  • E. St. Truiden
    St. Truiden is a historic Belgian city in the Limburg region, known for its medieval architecture and fruit-growing countryside.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d6ada166c48190b902972cd2408fa3 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94d8fd9848190a83410353d88ea8d completed April 10, 2026, 7:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f70a16408081909097d7e3ab750a27 completed May 3, 2026, 8:40 a.m.
Created at: April 8, 2026, 9:55 p.m.