Triple

T20272770
Position Surface form Disambiguated ID Type / Status
Subject Euler Hermes E502931 entity
Predicate parentCompany P254 FINISHED
Object Allianz SE 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: Allianz SE | Statement: [Euler Hermes, parentCompany, Allianz SE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Allianz SE
Context triple: [Euler Hermes, parentCompany, Allianz SE]
  • A. Allianz chosen
    Allianz is a leading global financial services company, best known as one of the world’s largest insurance and asset management providers.
  • B. Munich Re
    Munich Re is a leading global reinsurance company based in Germany, known for providing risk management and insurance solutions worldwide.
  • C. Swiss Re
    Swiss Re is a leading global reinsurance company headquartered in Zurich, Switzerland, providing risk transfer and insurance solutions worldwide.
  • D. Nürnberger Versicherung
    Nürnberger Versicherung is a German insurance company based in Nuremberg, offering a range of life, health, and property insurance and financial services.
  • E. AXA
    AXA is a major French multinational insurance and asset management company headquartered in Paris.
  • 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_69e0b4b0e79c8190bd61f22ef1329fa8 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e675dff3c4819098ba45eba4e7b296 completed April 20, 2026, 6:52 p.m.
Created at: April 16, 2026, 10:15 a.m.