Triple

T1467581
Position Surface form Disambiguated ID Type / Status
Subject non-appropriated fund bureau E27059 entity
Predicate financingModel P59 FINISHED
Object self-generated revenues 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: self-generated revenues | Statement: [non-appropriated fund bureau, financingModel, self-generated revenues]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: financingModel
Context triple: [non-appropriated fund bureau, financingModel, self-generated revenues]
  • A. fundingModel chosen
    Indicates how an entity is financially supported or sustained, such as through specific revenue sources, payment structures, or funding mechanisms.
  • B. operatingModel
    Indicates how an organization structures and manages its processes, resources, and governance to deliver its products or services.
  • C. loanType
    Indicates the specific category or kind of loan associated with an entity or transaction.
  • D. marketingModel
    Indicates a relationship where an entity uses or is associated with a specific marketing model, framework, or strategy to guide promotional or market-related decisions.
  • E. ownershipModel
    Indicates the type or structure of ownership relationship that governs how control, rights, or shares are held between entities.
  • 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_69a496d25d6881909dbd84f86d763992 completed March 1, 2026, 7:43 p.m.
NER Named-entity recognition batch_69a4c5bcfa0881909d6137c69825bc7a completed March 1, 2026, 11:03 p.m.
PD Predicate disambiguation batch_69a4c48121e48190946c23c583e5fb64 completed March 1, 2026, 10:58 p.m.
Created at: March 1, 2026, 8:01 p.m.