Triple

T1533329
Position Surface form Disambiguated ID Type / Status
Subject Dennis Haysbert E32493 entity
Predicate employer P7 FINISHED
Object Allstate E76573 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: Allstate | Statement: [Dennis Haysbert, employer, Allstate]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Allstate
Context triple: [Dennis Haysbert, employer, Allstate]
  • A. Allstate chosen
    Allstate is a major American insurance company best known for its auto and home insurance services and its long-running national advertising campaigns.
  • B. GEICO
    GEICO is a major American auto insurance company best known for its direct-to-consumer model and iconic advertising campaigns featuring the GEICO Gecko.
  • C. Allianz
    Allianz is a leading global financial services company, best known as one of the world’s largest insurance and asset management providers.
  • D. Marsh & McLennan
    Marsh & McLennan is a global professional services firm specializing in insurance brokerage, risk management, and consulting.
  • E. Swiss Re
    Swiss Re is a leading global reinsurance company headquartered in Zurich, Switzerland, providing risk transfer 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_69a885ea86308190998f6bc14bb91f8e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a9081835e4819093dee004fdb027ff completed March 5, 2026, 4:35 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad295a03d881909071fb437c2d19ba completed March 8, 2026, 7:46 a.m.
Created at: March 4, 2026, 7:26 p.m.