Triple

T997738
Position Surface form Disambiguated ID Type / Status
Subject University of the West of Scotland E21531 entity
Predicate hasSpecialisation P466 FINISHED
Object health and nursing 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: health and nursing | Statement: [University of the West of Scotland, hasSpecialisation, health and nursing]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasSpecialisation
Context triple: [University of the West of Scotland, hasSpecialisation, health and nursing]
  • A. hasSpecialty chosen
    Indicates that an entity possesses a particular area of expertise, focus, or professional specialization.
  • B. hasSpecification
    Indicates that an entity is associated with a particular specification that defines or constrains its properties, behavior, or requirements.
  • C. hasSpecialUnit
    Indicates that an entity possesses or is associated with a distinct, designated unit that has a special role, function, or status.
  • D. hasSubdiscipline
    Indicates that one discipline includes another, more specialized field of study as a subordinate branch.
  • E. hasSpecialVersion
    Indicates that an entity possesses or is associated with a distinct or customized version of another entity, differing from the standard or default form.
  • 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_69a493c476b48190b41fc5e793171cc6 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b4e0f0d081908b888c246d001786 completed March 1, 2026, 9:51 p.m.
PD Predicate disambiguation batch_69a4b2b057c48190b9e42df9246b3757 completed March 1, 2026, 9:42 p.m.
Created at: March 1, 2026, 7:41 p.m.