Triple

T14815859
Position Surface form Disambiguated ID Type / Status
Subject Esneux E348311 entity
Predicate neighboringMunicipality P17964 FINISHED
Object Neupré E905673 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: Neupré | Statement: [Esneux, neighboringMunicipality, Neupré]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Neupré
Context triple: [Esneux, neighboringMunicipality, Neupré]
  • A. Neupré chosen
    Neupré is a municipality in the province of Liège in Wallonia, Belgium.
  • B. La Neuveville
    La Neuveville is a historic Swiss town on the shores of Lake Biel in the canton of Bern, known for its well-preserved medieval old town and wine-growing region.
  • C. Chautemps
    Chautemps is a French surname most notably associated with Camille Chautemps, a prominent Radical politician and three-time Prime Minister of France during the Third Republic.
  • D. Neuhaus
    Neuhaus is a locality within the municipality of Möhnesee in North Rhine-Westphalia, Germany.
  • E. Mauprat
    Mauprat is a 1837 novel by French writer George Sand that blends romantic adventure with social and psychological themes, often seen as an early feminist and proto–Bildungsroman 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_69d822eb8f588190bf53445e730a934f completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69decfe2c1ec81908b3dff7a5d0e85d0 completed April 14, 2026, 11:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe389598848190ba15e6eea2ba2903 completed May 8, 2026, 7:25 p.m.
Created at: April 10, 2026, 1:49 a.m.