Triple

T5546553
Position Surface form Disambiguated ID Type / Status
Subject Yvonne de Gaulle E145421 entity
Predicate associatedReligionView P45 FINISHED
Object support for Catholic moral teaching 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: support for Catholic moral teaching | Statement: [Yvonne de Gaulle, associatedReligionView, support for Catholic moral teaching]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: associatedReligionView
Context triple: [Yvonne de Gaulle, associatedReligionView, support for Catholic moral teaching]
  • A. associatedReligionText
    Indicates that there is a textual work (such as a scripture or religious document) that is specifically associated with, or pertains to, a given religion.
  • B. associatedReligionRole
    Indicates that one entity holds a specific religious role, office, or function in relation to another entity.
  • C. associatedReligionInTexts
    Indicates that a particular religion is mentioned or linked in written texts in connection with the given entity.
  • D. sharesReligionWith
    Indicates that two entities follow or are associated with the same religion or religious tradition.
  • E. religiousAffiliation chosen
    Indicates that one entity has a specified religious association, belief system, or denominational membership.
  • 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_69c008fb879c81909f5bfa56fadc1d46 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01fdec3588190b0af7d2ca8e8ee9b completed March 22, 2026, 4:59 p.m.
PD Predicate disambiguation batch_69c01b0e72f08190bf705d8fe1639401 completed March 22, 2026, 4:38 p.m.
Created at: March 22, 2026, 3:35 p.m.