Triple

T1880552
Position Surface form Disambiguated ID Type / Status
Subject Ralph Lauren E39842 entity
Predicate familyName P18 FINISHED
Object Lauren E90841 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: Lauren | Statement: [Ralph Lauren, familyName, Lauren]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lauren
Context triple: [Ralph Lauren, familyName, Lauren]
  • A. Lauren chosen
    Lauren is a central female protagonist in the romantic comedy film "Think Like a Man," portrayed as a successful, relationship-seeking woman whose love life is influenced by Steve Harvey’s dating advice.
  • B. Laurene
    Laurene is the first name of Laurene Powell Jobs, an American businesswoman, philanthropist, and widow of Apple co-founder Steve Jobs.
  • C. Lindsay
    Lindsay is the fugitive Australian protagonist of Gregory David Roberts' novel "Shantaram," who rebuilds his life in the underworld of Bombay.
  • D. Lindsey
    Lindsey is a given name commonly used in English-speaking countries for both females and males.
  • E. Nicole
    Nicole is a central character in Margaret Atwood's dystopian novel "The Testaments," whose story helps expose and challenge the oppressive regime of Gilead.
  • 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_69a88633e4fc8190b7eb40463e048ec5 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb0fa3d388190993073ffb0f60a84 completed March 7, 2026, 5 a.m.
NED1 Entity disambiguation (via context triple) batch_69adfba6e94c8190ad1daafbe7f70a44 completed March 8, 2026, 10:43 p.m.
Created at: March 4, 2026, 7:34 p.m.