Triple

T35149479
Position Surface form Disambiguated ID Type / Status
Subject Richard Dana Fairbank E1014944 entity
Predicate hasEmployerNumberOfEmployeesScope P74492 FINISHED
Object large publicly traded corporation (Capital One) 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: large publicly traded corporation (Capital One) | Statement: [Richard Dana Fairbank, hasEmployerNumberOfEmployeesScope, large publicly traded corporation (Capital One)]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasEmployerNumberOfEmployeesScope
Context triple: [Richard Dana Fairbank, hasEmployerNumberOfEmployeesScope, large publicly traded corporation (Capital One)]
  • A. 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.
  • B. hasEmployeeRange
    Indicates the range or limits on the number of employees associated with an entity.
  • C. hasEmployees
    Indicates that one entity employs one or more other entities as its workers or staff.
  • D. employsApproximateNumberOfPeople
    Indicates that an entity employs a roughly estimated or approximate number of people, rather than an exact headcount.
  • 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_69f76dda7c108190a2ffd93eb6c341a7 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78f63c8788190b253a18de5ca1312 completed May 3, 2026, 6:09 p.m.
PD Predicate disambiguation batch_69f78e2d71248190b850c2802ec170c0 completed May 3, 2026, 6:04 p.m.
Created at: May 3, 2026, 4:02 p.m.