Triple

T31650629
Position Surface form Disambiguated ID Type / Status
Subject Kristine Holding E807720 entity
Predicate hasFamilyBusinessInterestIn P8006 FINISHED
Object hospitality 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: hospitality industry | Statement: [Kristine Holding, hasFamilyBusinessInterestIn, hospitality industry]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasFamilyBusinessInterestIn
Context triple: [Kristine Holding, hasFamilyBusinessInterestIn, hospitality industry]
  • A. hasFamilyBusinessIn
    Indicates that an entity owns, operates, or is significantly involved in a family-run business located in a specified place.
  • B. relatedFamilyBusiness chosen
    Indicates that there is a connection between entities through ownership, management, or involvement in the same family-run business or businesses.
  • C. hasParentCompanyBusiness
    Indicates that one company operates as a business owned or controlled by another company that serves as its parent company.
  • D. hasBusinessIn
    Indicates that one entity conducts, operates, or maintains business activities within the jurisdiction, location, or domain of another entity.
  • E. hasEconomicInterest
    Indicates that one entity stands to gain or lose financially or materially from the performance, decisions, or outcomes associated with 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_69f348daf95c81908b4c985b7ddcd0b3 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69fcef654d588190b29ecc76678d1aa0 completed May 7, 2026, 8 p.m.
PD Predicate disambiguation batch_69fcecdb97f48190b382b7d13be92dc0 completed May 7, 2026, 7:49 p.m.
Created at: April 30, 2026, 10:53 p.m.