Triple

T11189876
Position Surface form Disambiguated ID Type / Status
Subject Peter Akemann E264767 entity
Predicate hasProfessionalFocus P86052 FINISHED
Object AAA game development 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: AAA game development | Statement: [Peter Akemann, hasProfessionalFocus, AAA game development]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasProfessionalFocus
Context triple: [Peter Akemann, hasProfessionalFocus, AAA game development]
  • A. hasProfessionalOrientation
    Indicates that an entity is directed toward, focused on, or aligned with a particular profession, career field, or occupational domain.
  • B. hasProfessionalSection
    Indicates that an entity includes or is associated with a designated professional section, division, or category within its structure or content.
  • C. hasProfessionalStatus
    Indicates that an entity holds a particular professional standing, rank, or qualification within a field or occupation.
  • D. hasProfessionalCore
    Indicates that an entity possesses a central set of professional skills, knowledge, or competencies that define its primary professional function or expertise.
  • E. hasProfessionalDomain chosen
    Indicates that an entity operates, specializes, or is active within a particular professional field or domain.
  • 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_69d6aa9eb9248190b20211772621b4bc completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8af18e4819091811bca657c9cb0 completed April 9, 2026, 5:58 p.m.
PD Predicate disambiguation batch_69d75cf4461c8190af84060f7db83211 completed April 9, 2026, 8:01 a.m.
Created at: April 8, 2026, 9:29 p.m.