Triple

T12382649
Position Surface form Disambiguated ID Type / Status
Subject Timeless E295780 entity
Predicate producer P490 FINISHED
Object Bojangles E140544 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: Bojangles | Statement: [Timeless, producer, Bojangles]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bojangles
Context triple: [Timeless, producer, Bojangles]
  • A. Bojangles chosen
    Bojangles is a 2001 television biographical film in which Gregory Hines portrays legendary tap dancer and entertainer Bill "Bojangles" Robinson.
  • B. Mycoskie
    Mycoskie is the surname of Blake Mycoskie, the American entrepreneur best known as the founder of TOMS Shoes and pioneer of the “One for One” social entrepreneurship model.
  • C. Tibbett
    Tibbett is a surname of English origin borne by various notable individuals in fields such as music, sports, and the arts.
  • D. Chattanooga Moccasins
    Chattanooga Moccasins was the former name of the University of Tennessee at Chattanooga’s athletic teams, now known as the Chattanooga Mocs.
  • E. Burdine
    Burdine is the respondent in the U.S. Supreme Court employment discrimination case Texas Department of Community Affairs v. Burdine, which clarified the burden of proof framework in Title VII disparate treatment claims.
  • 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_69d6ad9e653c8190b1473c860ee53dae completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d93fbb3a2481908c2fcb5e6488eb3c completed April 10, 2026, 6:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f62ac78c5c81909fb3d63bc6c9cc01 completed May 2, 2026, 4:48 p.m.
Created at: April 8, 2026, 9:54 p.m.