Triple

T18449734
Position Surface form Disambiguated ID Type / Status
Subject Vendlincourt E450747 entity
Predicate hasNeighboringMunicipality P224 FINISHED
Object Courcelles (France) NE NERFINISHED

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: Courcelles (France) | Statement: [Vendlincourt, hasNeighboringMunicipality, Courcelles (France)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Courcelles (France)
Context triple: [Vendlincourt, hasNeighboringMunicipality, Courcelles (France)]
  • A. Courcelles
    Courcelles is a district in Brussels, Belgium, known for being served by the city's metro system.
  • B. Courcelles chosen
    Courcelles is a municipality in the Walloon region of Belgium, known historically as part of the industrial coal-mining area around Charleroi.
  • C. Fourchambault, France
    Fourchambault, France is a small industrial town in the Nièvre department of central France, historically known for its steelworks and metallurgical industry.
  • D. Gouvieux, France
    Gouvieux, France is a commune in the Oise department in northern France, known for its affluent residential character and association with the Aga Khan IV.
  • E. Béthune, France
    Béthune is a historic town in northern France’s Pas-de-Calais department, known for its belfry, reconstructed town center, and role in both World Wars.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d38345688190b565eac2e4cd7935 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5264748dc8190984501af3e4b2036 completed April 19, 2026, 7 p.m.
Created at: April 10, 2026, 11:30 a.m.