Triple

T5208310
Position Surface form Disambiguated ID Type / Status
Subject Allianz E117565 entity
Predicate hasCompetitor P1375 FINISHED
Object AXA 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 | Statement: [Allianz, hasCompetitor, AXA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: AXA
Context triple: [Allianz, hasCompetitor, AXA]
  • 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. Munich Re
    Munich Re is a leading global reinsurance company based in Germany, known for providing risk management and insurance solutions worldwide.
  • E. AIG
    AIG (American International Group) is a global insurance and financial services corporation known for its extensive property-casualty, life insurance, and retirement products.
  • 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_69bd4463dd3c81909966123f20b79d57 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7a6d70d081908c74e86b3bca9ba2 completed March 20, 2026, 4:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69beefd4b75c8190b1b87b8d93925245 completed March 21, 2026, 7:21 p.m.
Created at: March 20, 2026, 1:47 p.m.