Triple

T7323456
Position Surface form Disambiguated ID Type / Status
Subject Halle, Belgium E168808 entity
Predicate borderedBy P224 FINISHED
Object Hainaut E86438 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: Hainaut | Statement: [Halle, Belgium, borderedBy, Hainaut]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hainaut
Context triple: [Halle, Belgium, borderedBy, Hainaut]
  • A. Hainaut chosen
    Hainaut is a historical region in western Europe, now divided between Belgium and France, known for its medieval heritage and role as a frequent battleground in European conflicts.
  • B. Putot-en-Bessin
    Putot-en-Bessin is a small commune in the Calvados department of Normandy in northwestern France, known for its rural character and World War II history.
  • C. Brionnais
    Brionnais is a historic rural region in eastern France known for its Romanesque churches, traditional stone villages, and Charolais cattle farming.
  • D. Langrois
    Langrois is the French term for an inhabitant or native of the town of Langres in northeastern France.
  • E. Auberjonois
    Auberjonois is a surname most prominently associated with René Auberjonois, an American actor known for roles in film, television, and voice work.
  • 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_69c68a54cacc81908e3b773441f19566 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f046b93c8190a80dd48ee409ec5d completed March 27, 2026, 9:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7ef0609dc81909f298d3963fc88af completed March 28, 2026, 3:08 p.m.
Created at: March 27, 2026, 3:03 p.m.