Triple

T987289
Position Surface form Disambiguated ID Type / Status
Subject Heriot-Watt University E21306 entity
Predicate hasQSSubjectStrength P22781 FINISHED
Object engineering and 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: engineering and technology | Statement: [Heriot-Watt University, hasQSSubjectStrength, engineering and technology]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasQSSubjectStrength
Context triple: [Heriot-Watt University, hasQSSubjectStrength, engineering and technology]
  • A. isSubjectTo
    Indicates that one entity is governed, affected, or constrained by the authority, rules, conditions, or influence of another entity.
  • B. estimatedStrength
    Indicates that a value represents an approximate or inferred level, magnitude, or intensity of something rather than a precisely measured strength.
  • C. hasSubdiscipline
    Indicates that one discipline includes another, more specialized field of study as a subordinate branch.
  • D. hasQualifier
    Indicates that one entity serves as a qualifier or modifier that further specifies or restricts the meaning or scope of another entity or statement.
  • E. hasLegalSubject
    Indicates that an entity serves as the legal subject (e.g., rights-holder or obligated party) in a legal relationship or context.
  • 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_69a493c383dc8190a03257f22d4b4183 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b4a7754c8190a10ba0587bd8323d completed March 1, 2026, 9:50 p.m.
PD Predicate disambiguation batch_69a4b2abccbc8190a83af432f89eacf5 completed March 1, 2026, 9:42 p.m.
PDg Predicate description generation batch_69a4b38630848190bd3898a4f42018ad completed March 1, 2026, 9:45 p.m.
Created at: March 1, 2026, 7:41 p.m.