Triple

T13684295
Position Surface form Disambiguated ID Type / Status
Subject Tadashi Yanai E328080 entity
Predicate hasGlobalInfluenceIn P63153 FINISHED
Object fashion industry LITERAL 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: fashion industry | Statement: [Tadashi Yanai, hasGlobalInfluenceIn, fashion industry]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasGlobalInfluenceIn
Context triple: [Tadashi Yanai, hasGlobalInfluenceIn, fashion industry]
  • A. hasRegionalInfluenceFrom
    Indicates that one entity’s influence, impact, or authority in a region is derived from or shaped by another entity.
  • B. hasSignificantInfluenceIn chosen
    Indicates that one entity exerts a substantial impact or shaping effect on another entity within a particular domain, context, or outcome.
  • C. hasInfluenceScope
    Indicates the range or extent within which an entity’s influence, impact, or authority is effective or applicable.
  • D. hasPoliticalInfluenceBeyondLocalArea
    Indicates that an entity exerts political influence or impact extending beyond its immediate local community or region.
  • E. hasHistoricalInfluenceFrom
    Indicates that one entity’s characteristics, development, or significance have been shaped or affected by the past actions, ideas, or legacy of another entity.
  • F. None of above.

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_69d8076f1fa8819094664a59b55010df completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc66f8acc8190b2a82b722930b995 completed April 12, 2026, 4:21 p.m.
PD Predicate disambiguation batch_69dbbe9059488190a8113177c83e1481 completed April 12, 2026, 3:47 p.m.
Created at: April 9, 2026, 9:53 p.m.