Triple

T21557099
Position Surface form Disambiguated ID Type / Status
Subject Vilvoorde E531920 entity
Predicate hasTwinTown P919 FINISHED
Object Maurepas 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: Maurepas | Statement: [Vilvoorde, hasTwinTown, Maurepas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maurepas
Context triple: [Vilvoorde, hasTwinTown, Maurepas]
  • A. Maurepas chosen
    Maurepas is a commune in the Yvelines department in the Île-de-France region of north-central France, known as a residential suburb southwest of Paris.
  • B. Lépaud
    Lépaud is a small rural commune in central France’s Creuse department, known for its traditional countryside setting within the Nouvelle-Aquitaine region.
  • C. Vaugines
    Vaugines is a small commune in southeastern France, located in the Vaucluse department within the Provence-Alpes-Côte d'Azur region.
  • D. Vauvert
    Vauvert is a commune in southern France known for its location in the Gard department near the Camargue region.
  • E. Bévilard
    Bévilard is a village in the Bernese Jura region of the canton of Bern in Switzerland.
  • 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_69e0c460232c81908de2c3819d17c00e completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69eed2e04b048190ac3a9913094b4625 completed April 27, 2026, 3:07 a.m.
Created at: April 16, 2026, 6:29 p.m.