Triple

T4854973
Position Surface form Disambiguated ID Type / Status
Subject Hannah Jeter E108513 entity
Predicate hasWorkedForBrand P11675 FINISHED
Object Ralph Lauren E39842 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: Ralph Lauren | Statement: [Hannah Jeter, hasWorkedForBrand, Ralph Lauren]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ralph Lauren
Context triple: [Hannah Jeter, hasWorkedForBrand, Ralph Lauren]
  • A. Ralph Lauren chosen
    Ralph Lauren is an American fashion designer and business executive best known for founding the Ralph Lauren Corporation and its iconic Polo Ralph Lauren brand.
  • B. David Lauren
    David Lauren is an American businessman and executive at the fashion company Ralph Lauren, founded by his father Ralph Lauren.
  • C. Tommy Hilfiger
    Tommy Hilfiger is an American fashion brand and designer known for his classic, preppy clothing and accessories that blend traditional Americana with modern style.
  • D. Halston
    Halston is a biographical drama miniseries that chronicles the rise and fall of the iconic American fashion designer Roy Halston Frowick.
  • E. Thomas Jacob Hilfiger
    Thomas Jacob Hilfiger is an American fashion designer best known as the founder of the global lifestyle brand Tommy Hilfiger.
  • 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_69bd440a89548190a5f14ba6da6b97dc completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd7162427c81908a67a07545f698ae completed March 20, 2026, 4:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69be5ce7385c8190897fd2343c0ebeed completed March 21, 2026, 8:55 a.m.
Created at: March 20, 2026, 1:26 p.m.