Triple

T13449474
Position Surface form Disambiguated ID Type / Status
Subject VIVES University of Applied Sciences E320569 entity
Predicate hasFocusField P34683 FINISHED
Object Technology 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: Technology | Statement: [VIVES University of Applied Sciences, hasFocusField, Technology]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasFocusField
Context triple: [VIVES University of Applied Sciences, hasFocusField, Technology]
  • A. haveFocusSystem
    Indicates that an entity is currently the primary target or active focus within a system or context.
  • B. hasFocusSystem
    Indicates that one entity is the primary system or subsystem that another entity is currently directing its attention, control, or processing resources toward.
  • C. hasCharacterFocus
    Indicates that a work, scene, or segment centers primarily on a particular character’s experiences, perspective, or development.
  • D. hasFocusGroup
    Indicates that an entity is associated with or participates in a specific focus group for targeted discussion, feedback, or research.
  • E. hasProgramFocus chosen
    Indicates that an entity (such as a program or initiative) is oriented around or primarily concerned with a particular thematic area, topic, or objective.
  • 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_69d80761e6cc8190a90c844589998ecc completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaef973b08190a3d7fe1c2a913cff completed April 12, 2026, 2:40 p.m.
PD Predicate disambiguation batch_69d9a03ce03481908c61094f0cc0c158 completed April 11, 2026, 1:13 a.m.
Created at: April 9, 2026, 9:41 p.m.