Triple

T2779173
Position Surface form Disambiguated ID Type / Status
Subject Jamie Dimon E61650 entity
Predicate name P16 FINISHED
Object Jamie Dimon E61650 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: Jamie Dimon | Statement: [Jamie Dimon, name, Jamie Dimon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jamie Dimon
Context triple: [Jamie Dimon, name, Jamie Dimon]
  • A. Jamie Dimon chosen
    Jamie Dimon is an American business executive best known as the long-serving chairman and CEO of JPMorgan Chase, one of the world’s largest financial institutions.
  • B. Howard Lutnick
    Howard Lutnick is an American businessman best known as the longtime chairman and CEO who rebuilt the financial services firm Cantor Fitzgerald after the September 11 attacks.
  • C. Sanford I. Weill
    Sanford I. Weill is an American banker and philanthropist best known for building Citigroup into a financial giant and for his major philanthropic contributions to education and medicine.
  • D. Dave Corzine
    Dave Corzine is a former American professional basketball center best known for his NBA career, particularly with the Chicago Bulls in the 1980s.
  • E. Robert Kravis
    Robert Kravis is a film producer best known for his work on the crime thriller "Lucky Number Slevin."
  • 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_69ab4b7e43c48190997b8fc8fb1663ab completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdd97e9988190a9065a70b878a675 completed March 7, 2026, 8:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69afc05cf84881908e771471dbda4c8d completed March 10, 2026, 6:55 a.m.
Created at: March 6, 2026, 9:57 p.m.