Triple

T1751322
Position Surface form Disambiguated ID Type / Status
Subject Red Door spa network E38448 entity
Predicate associatedWith P37 FINISHED
Object Elizabeth Arden E1396 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: Elizabeth Arden | Statement: [Red Door spa network, associatedWith, Elizabeth Arden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elizabeth Arden
Context triple: [Red Door spa network, associatedWith, Elizabeth Arden]
  • A. Elizabeth Arden chosen
    Elizabeth Arden was a pioneering Canadian-American businesswoman who founded the Elizabeth Arden cosmetics empire and helped shape the modern beauty industry.
  • B. Lancôme
    Lancôme is a French luxury cosmetics and skincare brand renowned for its high-end perfumes, makeup, and beauty products.
  • C. Yves Saint Laurent Beauté
    Yves Saint Laurent Beauté is a luxury cosmetics and fragrance brand known for its high-end makeup, skincare, and iconic perfumes.
  • D. Nina Ricci
    Nina Ricci is a French luxury fashion house renowned for its elegant haute couture, ready-to-wear collections, and iconic fragrances.
  • E. Helena Rubinstein
    Helena Rubinstein was a pioneering Polish-American businesswoman and cosmetics entrepreneur who founded one of the world’s first global beauty empires.
  • 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_69a8862bdb2081908aefe831c8aa8017 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa6411cc788190a052b029dbffa7ca completed March 6, 2026, 5:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada0e40cb88190953c639ee2464a54 completed March 8, 2026, 4:16 p.m.
Created at: March 4, 2026, 7:31 p.m.