Triple

T11954629
Position Surface form Disambiguated ID Type / Status
Subject Steve Barclay E284518 entity
Predicate workedFor P1910 FINISHED
Object Axa Insurance 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: Axa Insurance | Statement: [Steve Barclay, workedFor, Axa Insurance]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Axa Insurance
Context triple: [Steve Barclay, workedFor, Axa Insurance]
  • A. AXA chosen
    AXA is a major French multinational insurance and asset management company headquartered in Paris.
  • B. Allianz
    Allianz is a leading global financial services company, best known as one of the world’s largest insurance and asset management providers.
  • C. Swiss Re
    Swiss Re is a leading global reinsurance company headquartered in Zurich, Switzerland, providing risk transfer and insurance solutions worldwide.
  • D. Helvetia General Insurance Company
    Helvetia General Insurance Company is a Swiss insurance firm known for its role in the origins of Swiss Re, one of the world’s leading reinsurance companies.
  • E. Munich Re
    Munich Re is a leading global reinsurance company based in Germany, known for providing risk management and insurance solutions worldwide.
  • 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_69d6ab2db38c8190b1f0ed6663ef8ada completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d90366fda8819083168c93abad27d4 completed April 10, 2026, 2:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69f459175f808190974ac70431f35c74 completed May 1, 2026, 7:41 a.m.
Created at: April 8, 2026, 9:45 p.m.