Triple

T5933431
Position Surface form Disambiguated ID Type / Status
Subject AXA E131989 entity
Predicate formerName P65 FINISHED
Object Mutuelles Unies E131989 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: Mutuelles Unies | Statement: [AXA, formerName, Mutuelles Unies]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mutuelles Unies
Context triple: [AXA, formerName, Mutuelles Unies]
  • A. Harmonie Mutuelle Semi de Paris
    Harmonie Mutuelle Semi de Paris is a major annual half marathon held in Paris, France, attracting tens of thousands of runners from around the world.
  • B. Caisse des Dépôts et Consignations
    Caisse des Dépôts et Consignations is a French public financial institution that manages long-term investments and savings on behalf of the state and public interest missions.
  • C. AXA chosen
    AXA is a major French multinational insurance and asset management company headquartered in Paris.
  • D. Caisse d’Epargne
    Caisse d’Epargne was a French professional road cycling team, sponsored by the French savings bank group of the same name, that competed at the highest level of the sport in the 2000s.
  • E. Allianz
    Allianz is a leading global financial services company, best known as one of the world’s largest insurance and asset management providers.
  • 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_69c0085c55dc8190aa90e242c956e2fa completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0389f6fc881909527b928838ffcdd completed March 22, 2026, 6:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0c064d2a4819096085668182cfde1 completed March 23, 2026, 4:24 a.m.
Created at: March 22, 2026, 4 p.m.