Triple

T1775446
Position Surface form Disambiguated ID Type / Status
Subject Chiat/Day E38965 entity
Predicate notableEmployee P304 FINISHED
Object Lee Clow E136674 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: Lee Clow | Statement: [Chiat/Day, notableEmployee, Lee Clow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lee Clow
Context triple: [Chiat/Day, notableEmployee, Lee Clow]
  • A. Lee Clow chosen
    Lee Clow is a legendary American advertising executive best known for his groundbreaking work at TBWA\Chiat\Day, where he helped create iconic campaigns for Apple and other major brands.
  • B. Ray Cusick
    Ray Cusick was a British designer best known for creating the iconic look of the Daleks in the long-running science fiction television series Doctor Who.
  • C. Dan Dailey
    Dan Dailey was an American actor and dancer best known for his roles in Hollywood musicals of the 1940s and 1950s.
  • D. Terry Tumey
    Terry Tumey is an American college athletics administrator and former UCLA football player and NFL defensive lineman who serves as the athletic director at Fresno State.
  • E. Lyle Bettger
    Lyle Bettger was an American character actor best known for his frequent portrayals of suave villains in mid-20th-century Hollywood films and television.
  • 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_69a8862e61708190af97b9838cc3f5de completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa64b6c4a88190ab2f75c8d4814f11 completed March 6, 2026, 5:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae516bbbf48190ae87ec3344da64d1 completed March 9, 2026, 4:49 a.m.
Created at: March 4, 2026, 7:31 p.m.