Triple

T13515159
Position Surface form Disambiguated ID Type / Status
Subject Faculty of Business Administration, Setsunan University E322740 entity
Predicate educationAndResearchFocus P6235 FINISHED
Object business 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: business | Statement: [Faculty of Business Administration, Setsunan University, educationAndResearchFocus, business]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: educationAndResearchFocus
Context triple: [Faculty of Business Administration, Setsunan University, educationAndResearchFocus, business]
  • A. academicFocus
    Indicates the primary field of study, discipline, or subject area that an entity concentrates on academically.
  • B. regionOfAcademicFocus
    Indicates the academic subject area or discipline that an entity (such as a person or program) primarily concentrates on or specializes in.
  • C. researchTopic
    Indicates that a subject conducts or focuses research on a particular topic or area of study.
  • D. educationalFocus chosen
    Indicates the primary subject area or theme that an educational activity, program, or resource is centered on.
  • E. regionOfAcademicInterest
    Indicates that an entity has a particular academic field or subject area as its focus of interest or study.
  • 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_69d80766a21881909f21a1b7421d3b8a completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafa0ed508190b2855171b1945e84 completed April 12, 2026, 2:43 p.m.
PD Predicate disambiguation batch_69dbae0b63748190b5e207f84b2532ea completed April 12, 2026, 2:36 p.m.
Created at: April 9, 2026, 9:44 p.m.