Triple

T9857248
Position Surface form Disambiguated ID Type / Status
Subject Lublin University of Technology E239617 entity
Predicate hasRDFocus P90921 FINISHED
Object engineering applications 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: engineering applications | Statement: [Lublin University of Technology, hasRDFocus, engineering applications]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasRDFocus
Context triple: [Lublin University of Technology, hasRDFocus, engineering applications]
  • A. hasVisualFocus
    Indicates that one entity is currently directing its visual attention or gaze toward another entity.
  • B. hasAccessibilityFocus
    Indicates that a user interface element is currently the primary target of accessibility tools, such as screen readers or keyboard navigation, receiving focused attention for interaction.
  • C. hasPrimaryFocus
    Indicates that something is the main subject, concern, or area of attention for an entity or activity.
  • D. hasActingFocus
    Indicates that an entity is the primary performer or focal agent carrying out an action in a given context.
  • E. hasGlobalFocus
    Indicates that something is oriented toward, concerned with, or applicable to worldwide or international scope rather than a local or regional one.
  • 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_69ca84e6493081909cf58c8d42ea856b completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb39864188190a2d8c0ee911f00c2 completed April 2, 2026, 12:08 a.m.
PD Predicate disambiguation batch_69cd1d7621d48190aa6a6f34399514b0 completed April 1, 2026, 1:28 p.m.
PDg Predicate description generation batch_69cd3581a9688190a00cef4c3eebb0ae completed April 1, 2026, 3:10 p.m.
Created at: March 30, 2026, 8:35 p.m.