Triple

T8168421
Position Surface form Disambiguated ID Type / Status
Subject Namur Province E190753 entity
Predicate capital P234 FINISHED
Object Namur E107798 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: Namur | Statement: [Namur Province, capital, Namur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Namur
Context triple: [Namur Province, capital, Namur]
  • A. Namur chosen
    Namur is a historic Belgian city and the capital of Wallonia, located at the confluence of the Meuse and Sambre rivers.
  • B. Nivelles
    Nivelles is a historic town in present-day Belgium known for its medieval architecture, including the Romanesque Collegiate Church of Saint Gertrude.
  • C. Durbuy
    Durbuy is a small, picturesque town in the Belgian Ardennes often promoted as one of the “smallest cities in the world,” known for its medieval architecture and tourism.
  • D. Binche
    Binche is a historic town in the Walloon region of Belgium, renowned for its well-preserved medieval architecture and its UNESCO-recognized Carnival of Binche.
  • E. Liège
    Liège is a major city in eastern Belgium known for its industrial heritage, vibrant cultural scene, and position along the Meuse River.
  • 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_69ca82c0ef14819083713f4473dd847c completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb466abfe48190b4eb2f23b1e28668 completed March 31, 2026, 3:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69cf8855a9c081909721a2efdc06d778 completed April 3, 2026, 9:28 a.m.
Created at: March 30, 2026, 5:39 p.m.