Triple

T577493
Position Surface form Disambiguated ID Type / Status
Subject Hellman & Friedman E13786 entity
Predicate targetCompanyType P3580 FINISHED
Object market-leading companies 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: market-leading companies | Statement: [Hellman & Friedman, targetCompanyType, market-leading companies]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: targetCompanyType
Context triple: [Hellman & Friedman, targetCompanyType, market-leading companies]
  • A. employerType
    Indicates the classification or category of an employer in relation to the entity (e.g., public, private, nonprofit, self-employed).
  • B. employmentType
    Indicates the specific kind or category of employment relationship that exists between an individual and an employer (e.g., full-time, part-time, contract).
  • C. typicalEmployerUnit
    Indicates that one entity is the standard or characteristic organizational unit that employs or is expected to employ another entity.
  • D. organizationType chosen
    Indicates the specific category or classification of an organization in terms of its nature, structure, or primary function.
  • E. parentOrganizationType
    Indicates the classification or category of the organization that serves as the parent in a hierarchical relationship.
  • 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_69a4933fa4d88190a7949cc83c08c5c1 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49b68cc808190b1ba45bdad78443d completed March 1, 2026, 8:02 p.m.
PD Predicate disambiguation batch_69a494c692288190b88f30299516b5ba completed March 1, 2026, 7:34 p.m.
Created at: March 1, 2026, 7:33 p.m.