Triple

T4289430
Position Surface form Disambiguated ID Type / Status
Subject Canadian Mennonite University E97350 entity
Predicate hasReligiousStudiesComponent P45331 FINISHED
Object yes 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: yes | Statement: [Canadian Mennonite University, hasReligiousStudiesComponent, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasReligiousStudiesComponent
Context triple: [Canadian Mennonite University, hasReligiousStudiesComponent, yes]
  • A. religiousScholarship
    Indicates a relationship where an entity provides or is associated with financial or institutional support specifically for religious study or education.
  • B. hasAcademicComponent chosen
    Indicates that something includes, involves, or is associated with an academic or educational element as part of its structure or content.
  • C. hasSubjectOfStudy
    Indicates that an entity (such as a person or organization) focuses on, researches, or specializes in a particular field or topic of study.
  • D. hasAssociatedReligion
    Indicates that an entity is connected with or linked to a particular religion.
  • E. hasLanguageOfStudy
    Indicates that an entity studies or is engaged in learning a particular language.
  • 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_69b3454595848190a0e6bbb6a2bea040 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35061f5448190b3356b29a9129160 completed March 12, 2026, 11:46 p.m.
PD Predicate disambiguation batch_69b347fc4c0c8190a7fcd814e27308a5 completed March 12, 2026, 11:10 p.m.
Created at: March 12, 2026, 11:08 p.m.