Triple

T16918271
Position Surface form Disambiguated ID Type / Status
Subject AFU E410375 entity
Predicate hasProfessionalComponent P124709 FINISHED
Object yes 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: yes | Statement: [AFU, hasProfessionalComponent, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasProfessionalComponent
Context triple: [AFU, hasProfessionalComponent, yes]
  • A. hasProfessionalSection
    Indicates that an entity includes or is associated with a designated professional section, division, or category within its structure or content.
  • B. hasProfessionalCore
    Indicates that an entity possesses a central set of professional skills, knowledge, or competencies that define its primary professional function or expertise.
  • C. hasProfessionalSystem
    Indicates that an entity is associated with or utilizes a particular professional system, framework, or structured method in carrying out its activities or services.
  • D. hasProfessionalApplication
    Indicates that something is used or applied within a professional, occupational, or work-related context.
  • E. hasProfessionalRequirement
    Indicates that one entity imposes or specifies a professional qualification, credential, or condition that must be met by another entity.
  • F. None of above. chosen

Provenance (4 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_69d886c7b1e481908c3766dfa8c13458 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3cdec3d0c8190994a0fca335c65d6 completed April 18, 2026, 6:31 p.m.
PD Predicate disambiguation batch_69e32b982f548190b08414d55810de19 completed April 18, 2026, 6:58 a.m.
PDg Predicate description generation batch_69e32d7aae948190bc238d765795688c completed April 18, 2026, 7:06 a.m.
Created at: April 10, 2026, 5:30 a.m.