Triple

T38284882
Position Surface form Disambiguated ID Type / Status
Subject B Corporation certification E1022176 entity
Predicate targetsCompanySizeRange P74492 FINISHED
Object small enterprises 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: small enterprises | Statement: [B Corporation certification, targetsCompanySizeRange, small enterprises]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: targetsCompanySizeRange
Context triple: [B Corporation certification, targetsCompanySizeRange, small enterprises]
  • A. typicalCompanySize
    Indicates the usual or most common number of employees associated with a company.
  • B. associatedWithCompanySize
    Indicates that an entity has a relationship to, or is characterized or categorized by, the size of a company (e.g., small, medium, large).
  • C. appliesToEmployerSize chosen
    Indicates that something (such as a rule, policy, or condition) is applicable only to employers of a specified size or within a defined employer size range.
  • D. targetCompanies
    Indicates that certain companies are the intended focus or recipients of a particular action, effort, or objective.
  • E. hasNumberOfCompanies
    Indicates the quantitative relationship specifying how many companies are associated with a given 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_69f76df0cddc81908d16c1556ff4097f completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69ff5b233e9c8190adc06cca0758986b completed May 9, 2026, 4:04 p.m.
PD Predicate disambiguation batch_69ff5a5682108190a006b23c4fcdcc7c completed May 9, 2026, 4:01 p.m.
Created at: May 3, 2026, 4:30 p.m.