Triple

T3912464
Position Surface form Disambiguated ID Type / Status
Subject arrondissement of Sarcelles E87354 entity
Predicate administrativeCenter P1474 FINISHED
Object Sarcelles E450439 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: Sarcelles | Statement: [arrondissement of Sarcelles, administrativeCenter, Sarcelles]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sarcelles
Context triple: [arrondissement of Sarcelles, administrativeCenter, Sarcelles]
  • A. Sarcelles chosen
    Sarcelles is a northern suburb of Paris in the Île-de-France region, known for its large housing estates and diverse, multicultural population.
  • B. Aulnay-sous-Bois
    Aulnay-sous-Bois is a suburban commune in the northeastern outskirts of Paris, France, known for its residential neighborhoods and industrial zones within the Seine-Saint-Denis department.
  • C. Aire-la-Ville
    Aire-la-Ville is a small municipality in the canton of Geneva in southwestern Switzerland, situated along the Rhône River.
  • D. Boulogne-Billancourt
    Boulogne-Billancourt is a densely populated suburban city just southwest of central Paris, known as a major economic and media hub in the Île-de-France region.
  • E. Bobigny
    Bobigny is a northeastern suburb of Paris that serves as an administrative and transport hub within the Île-de-France region.
  • 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_69aed9424514819086e9c58adde6652d completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeed37b19c81908e690c495d96607f completed March 9, 2026, 3:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7239e1ea481908c64d8a2d600aa30 completed March 28, 2026, 12:41 a.m.
Created at: March 9, 2026, 3:22 p.m.