Triple

T2923894
Position Surface form Disambiguated ID Type / Status
Subject ASVEL Basket E78797 entity
Predicate basedIn P40 FINISHED
Object Villeurbanne E96069 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: Villeurbanne | Statement: [ASVEL Basket, basedIn, Villeurbanne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Villeurbanne
Context triple: [ASVEL Basket, basedIn, Villeurbanne]
  • A. Villeurbanne chosen
    Villeurbanne is a major suburban city adjacent to Lyon in eastern France, known for its dense urban character and role as part of the Lyon metropolitan area.
  • B. Saint-Priest
    Saint-Priest is a suburban commune in eastern France that forms part of the metropolitan area of Lyon.
  • C. 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.
  • D. Meyzieu
    Meyzieu is a suburban commune in eastern France, located near Lyon and known for its residential character and proximity to major transport links.
  • E. Lyon
    Lyon is a major city in east-central France known for its historical and architectural landmarks, gastronomy, and role as a key economic and cultural center.
  • 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_69ad8b0d40b481908bc2a5fa2e73c3fb completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad97bf2df88190bd4f1e90d4656507 completed March 8, 2026, 3:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69b57f0432e081908110ede1c2b7a54a completed March 14, 2026, 3:30 p.m.
Created at: March 8, 2026, 2:55 p.m.